1. family and parenting
2. children

COMPARING THE DEVELOPMENT OF A SAMPLE OF SOUTH AFRICAN
PRE-SCHOOL BOYS AND GIRLS UTILIZING THE GRIFFITHS MENTAL
DEVELOPMENT SCALES–EXTENDED REVISED
TAMARIN ASHLEA JAKINS
Submitted in partial fulfillment of the requirements for the degree of
MAGISTER ARTIUM
IN
COUNSELLING PSYCHOLOGY
in the Department of Psychology, Faculty of Health Sciences at the
Nelson Mandela Metropolitan University
January 2009
Supervisor: Doctor Louise Stroud
Co-Supervisor: Professor Cheryl Foxcroft
ii
ACKNOWLEDGEMENTS
The completion of this treatise would not have been possible without the involvement,
expertise, guidance, support and encouragement of many individuals. I would therefore like to
express my heartfelt gratitude and appreciation to the following people:
My supervisor, Dr. Louise Stroud – thank you for sharing your invaluable assistance,
expertise and knowledge with me throughout the course of this research. Your constructive
feedback and insight paved each step of the way and you taught me to expand my thinking
not only on this topic, but also more broadly around the field of child development and
developmental assessment. Thank you for your guidance, encouragement and support. You
believed in me and it made the difference.
To my co-supervisor, Prof. Cheryl Foxcroft - your invaluable guidance and expertise provided
throughout the duration of this study is greatly appreciated. Thank you for your guidance
especially with the methodology and statistical analysis. I have learnt a great deal in the
process.
To Ms. Dalray de la Harpe - thank you for conducting the statistical analysis and for your
patience in fielding the many questions in this regard.
To the testers who assisted me with the data collection for this study - thank you for your
professionalism, enthusiasm and dedication towards the assessment of the children.
To the National Research Foundation (NRF) - thank you for the financial assistance provided
towards this study. Opinions expressed and conclusions arrived at are those of the researcher
and are not attributed to the NRF.
To Mr. Risdon Harding, Marketing Director of Pearson Education South Africa - my sincerest
appreciation for your generosity in donating the school readiness workbooks and parent
guides for the children classified within the low socio-economic status group in this study.
To the principals of the pre-schools - thank you for allowing the children from your preschool to participate in this study during school time. Your co-operation greatly facilitated the
completion of the data collection process and I sincerely appreciate it.
iii
To the boys and girls who participated in the study - thank you for your co-operation and
willingness to be assessed and most importantly for making a study such as this worthwhile. I
dedicate this work to you.
To the parents of the children – without your consent, this study would not have been
possible. Thank you for trusting us with the assessment of your ‘little treasures’.
To Dr. André de Jager and colleagues - thank you for your support, understanding and
encouragement.
To my parents - thank you for the continual love, empathy, support, and comfort you provided
throughout the research process. Most importantly thank you for the sacrifices you have made
to enable me to see this study through to fruition. I love you.
To my friends - thank you for your support, patience and humour.
To my personal Saviour, Lord Jesus Christ, with you all things are possible. Thank you for
being my pillar of strength, for never leaving nor forsaking me and for guiding me throughout
the course of this study.
iv
CONTENTS
ACKNOWLEDGEMENTS
ii
TABLE OF CONTENTS
iv
LIST OF TABLES
ix
LIST OF FIGURES
x
DECLARATION
xi
ABSTRACT
xii
CHAPTER ONE: INTRODUCTION
1
1.1 Gender
1
1.2 Child development
2
1.3 Child developmental assessment and the Griffiths Mental Development
Scales-Extended Revised (GMDS-ER)
4
1.4 Problem formulation and aims
7
1.5 Chapters of the study
8
CHAPTER TWO: GENDER
10
2.1 Introduction
10
2.2 Clarification of the terms ‘sex’ and ‘gender’
10
2.3 Historical influences on the research of children’s gender development
11
2.3.1 Meta-analysis
2.4 Gender differences
13
14
2.4.1 Gender differences within language development and verbal skills
16
2.4.2 Gender differences within quantitative ability
18
2.4.3 Gender differences within visual-spatial ability
19
2.4.4 Gender differences in aggression
21
2.5 Gender similarities
22
2.5.1 Gender similarities within language development and verbal ability
23
2.5.2 Gender similarities within quantitative ability
24
2.5.3 Gender similarities within visual-spatial ability
25
2.5.4 The influence of gender on motor development and motor skills
26
2.6 Influence of gender on the performance of South African children on the
Griffiths Scales
27
v
2.7 Towards a contemporary cognitive view of understanding gender performance
29
2.8 Chapter overview
31
CHAPTER THREE: CHILD DEVELOPMENT
32
3.1 Introduction
32
3.2 Child development
32
3.3 The impact of early development on subsequent development
33
3.4 Concept of intelligence
35
3.4.1 The psychometric approach to intelligence
37
3.5 Griffiths’ theoretical view of child development
38
3.6 Brief review of developmental theories
40
3.7 Piaget’s theory of cognitive development
43
3.8 Demetriou’s developmental model of information processing
45
3.8.1 Demetriou’s architecture of the developing mind
45
3.8.2 Demetriou’s model of working memory
49
3.8.3 Specialised capacity systems (SCSs)
51
3.9
3.8.3.1 The system of categorical thought
51
3.8.3.2 The system of quantitative thought
52
3.8.3.3 The system of causal thought
53
3.8.3.4 The system of spatial thought
54
3.8.3.5 The system of verbal-propositional thought
55
3.8.3.6 The system of social-interpersonal thought
56
3.8.3.7 The drawing-pictographic system
57
The nature of development
57
3.10 Continuity-discontinuity debate
58
3.11 Chapter overview
59
CHAPTER FOUR: CHILD DEVELOPMENTAL ASSESSMENT AND THE
GRIFFITHS MENTAL DEVELOPMENT SCALES-EXTENDED REVISED
(GMDS-ER)
61
4.1 Introduction
61
4.2 Child developmental assessment
61
4.3 Child developmental assessment within a multi-cultural context
63
4.4 Psychological assessment measures utilized with infants and young children in
South Africa
65
vi
4.5 Developmental assessment measures utilized in South Africa
66
4.5.1 The Junior South African Individual Scales (JSAIS)
66
4.5.2 Grover-Counter Scale of Cognitive Development
66
4.5.3 Educationally-focused developmental screening measures
67
4.5.3.1 School-readiness Evaluation by Trained Testers (SETT)
67
4.5.3.2 School-entry Group Screening Measure (SGSM)
68
4.5.3.3 Aptitude Test for School Beginners (ASB)
68
4.6 International developmental assessment measures adapted for use in South Africa
69
4.6.1 The Wecshler Scales
69
4.6.2 McCarthy Scales of Children’s Abilities (McCarthy Scales)
71
4.6.3 Bayley Scales of Infant Development-Second Edition (BSID-II)
71
4.6.4 Griffiths Scales of Mental Development (GMSD)
72
4.7 Griffiths Mental Development Scales-Extended Revised (GMDS-ER)
72
4.7.1 The development of the GMDS-ER: A historical journey
73
4.7.2 Description of the GMDS-ER Subscales
76
4.7.2.1 Subscale A: Locomotor
77
4.7.2.2 Subscale B: Personal-Social
77
4.7.2.3 Subscale C: Language
77
4.7.2.4 Subscale D: Eye and Hand Co-ordination
78
4.7.2.5 Subscale E: Performance
78
4.7.2.6 Subscale F: Practical Reasoning
78
4.7.3 Scoring and administration of the GMDS-ER
79
4.7.4 Reliability
80
4.7.5 Validity
82
4.7.6 The need for South African research on the Griffiths Mental Development
Scales-Extended Revised (GMDS-ER)
84
4.7.7 Research studies conducted on the Griffiths Mental Development Scales and
Griffiths Mental Development Scales-Extended Revised (GMDS-ER)
85
4.7.7.1 Clinical studies
86
4.7.7.2 Technical studies
88
4.8 Chapter overview
90
CHAPTER FIVE: RESEARCH METHODOLOGY
92
5.1 Introduction
92
5.2 Problem formulation and aims of the study
92
vii
5.3 Research method
93
5.4 Sampling procedure
99
5.5 Participants
100
5.5.1 Matched-pairs procedure
101
5.5.2 Description of the sample
102
5.6 Assessment measures
106
5.6.1 The Griffiths Mental Development Scales-Extended Revised (GMDS-ER)
106
5.6.2 Biographical Questionnaire
107
5.7 Research procedure
108
5.8 Ethical considerations
109
5.8.1 Informed consent
109
5.8.2 Confidentiality and privacy
110
5.8.3 Fairness
110
5.8.4 Inclusion criteria
110
5.8.5 Investigator competence
111
5.8.6 Feedback
111
5.9 Data analysis
111
5.9.1 The first aim of the study
112
5.9.2 The second aim of the study
113
5.10 Chapter overview
113
CHAPTER SIX: RESULTS AND DISCUSSION
114
6.1 Introduction
114
6.2 Comparison of gender groups in terms of age
115
6.3 Descriptive analysis of the sample’s performance on the GMDS-ER (Aim 1)
116
6.3.1 Mean developmental profile of the whole sample
116
6.3.2 Mean developmental profiles of the 5-year-old boys and girls
119
6.3.3 Mean developmental profiles of the 6-year-old boys and girls
121
6.4 Comparisons of the sample’s performance on the GMDS-ER (Aim 2)
6.4.1 Comparison of overall performance of the gender groups
6.5 Comparison of the Subscale profiles on the GMDS-ER (Aim 2)
123
123
125
6.5.1 Locomotor Subscale
127
6.5.2 Personal-Social Subscale
128
6.5.3 Language Subscale
130
6.5.4 Eye and Hand Co-ordination Subscale
131
viii
6.5.5 Performance Subscale
132
6.5.6 Practical Reasoning Subscale
133
6.6 Chapter overview
134
CHAPTER SEVEN: CONCLUSIONS, LIMITATIONS AND RECOMMENDATIONS
FOR FUTURE RESEARCH
137
7.1 Introduction
137
7.2 Conclusions
137
7.3 Limitations
139
7.3.1 Limitations of the research method
139
7.3.2 Limitations of the sampling procedure
139
7.3.3 Limitations regarding various test administrators utilized in the study
140
7.3.4 Limitations regarding the lack of norms for the South African population on
the GMDS-ER
140
7.4 Recommendations for future research
141
7.5 Chapter overview
142
REFERENCE LIST
144
APPENDIXES
Appendix A: Information and Informed Consent Form
169
Appendix B: Covering letter to principals of pre-primary schools
174
Appendix C: Covering letter to parents of participants
176
Appendix D: Biographical Questionnaire
178
Appendix E: Report template
182
ix
LIST OF TABLES
Table 1
Description of the GMDS-ER Subscales
6
Table 2
Classification of breadwinner’s education
97
Table 3
Classification of breadwinner’s occupation
98
Table 4
Classification of socio-economic status
98
Table 5
Sample breakdown in terms of age, gender, cultural group and socio-economic
status
Table 6
Independent sample t-test comparing the mean chronological age of the boys
and girls in the whole sample
Table 7
Table 9
115
Independent sample t-test comparing the 5-year-old boys and girls on mean
chronological age
Table 8
103
115
Independent sample t-test comparing the 6-year-old boys and girls on mean
chronological age
116
Overall mean and Subscale performance of the whole sample
116
Table 10 Mean developmental profile for the 5-year-old boys
119
Table 11 Mean developmental profile for the 5-year-old girls
119
Table 12 Mean developmental profile for the 6-year-old boys
121
Table 13 Mean developmental profile for the 6-year-old girls
121
Table 14 Independent sample t-test comparing the GQ of the pre-school boys and girls
in the whole sample
123
Table 15 Independent sample t-test comparing the GQ of the pre-school boys and girls
in the 5-year-old age group
124
Table 16 Independent sample t-test comparing the GQ of the pre-school boys and girls
in the 6-year-old age group
124
Table 17 Summary of the sample’s mean performance in terms of GQ and sub-quotients
across the 5- and 6-year-old age groups
126
x
LIST OF FIGURES
Figure 1
Griffiths’ basic avenues of learning
38
Figure 2
Demetriou’s general model of the architecture of the developing mind
46
Figure 3
Demetriou’s model of working memory
49
Figure 4
Demetriou’s model of working memory (Adapted)
50
Figure 5
Sample breakdown in terms of age categories
104
Figure 6
Sample breakdown in terms of cultural group
105
Figure 7
Sample breakdown in terms of socio-economic status
106
Figure 8
Developmental mean performance of the whole sample on the GMDS-ER
117
Figure 9
Mean chronological ages and mental ages of the 5-year-old sample
120
Figure 10 Mean chronological ages and mental ages of the 6-year-old sample
122
Figure 11 The comparative Subscale performances of the 5- and 6-year-old boys and
girls
126
xi
DECLARATION BY STUDENT
FULL NAME:
TAMARIN ASHLEA JAKINS
STUDENT NUMBER:
201346117
QUALIFICATION:
MAGISTER ARTIUM IN COUNSELLING PSYCHOLOGY
DECLARATION:
In accordance with Rule G4.6.3, I hereby declare that the above-mentioned treatise is my own
work and that it has not previously been submitted for assessment to another University or for
another qualification.
SIGNATURE:
________________
DATE:
27 MARCH 2009
xii
ABSTRACT
Both children and adults share a common, culturally distinct view of what it means to
be male or female. These gender stereotypes are pervasive in society and daily social
interactions, and influence all aspects of gender development (Golombok & Fivush, 1994).
The inherent physical differences of boys and girls may have triggered the speculation and
accompanying myths surrounding the existence of gender differences in childhood
development. Many people believe that boys and girls follow a different developmental path
that lead to gender differences in intellectual ability. An up-to-date and integrative review of
theory and research on gender indicates two opposing perspectives on the topic, with
substantial information supporting each view. However, this is the first study to examine and
compare a sample of South African pre-school boys and girls from a truly holistic
developmental perspective on the recently released Griffiths Mental Development ScalesExtended Revised (GMDS-ER).
Developmental theorists have emphasized the profound impact early childhood
development has on subsequent development, as it shapes the course of an individual’s life.
Contemporary cognitive developmental theories, such as Demetriou’s (2000; 2004)
developmental model of cognitive development, advance that child development does not
progress in a fixed and predictable manner. Instead, Demetriou proposes that development
occurs in a wave-like fashion, where the processes and functions of the various levels of the
mind may be at differing points in their cycle of development. When one function progresses
to a higher level, it unlocks the possibility for another function to advance to a different point
in its cycle (Demetriou et al., 2002).
As the significance of understanding the process of early childhood development more
fully increases, so does the need to establish with more confidence the value and role of
developmental assessment in the early identification of problems. The overall purpose of this
study was to generate comparative information regarding the general development of a
sample of 5- and 6-year-old South African pre-school boys and girls. Specifically, the study
aimed to explore and describe the developmental profiles of pre-school boys and girls within
the abovementioned age group with respect to their overall performance on the GMDS-ER as
well as their performance on the six Subscales. Then, the mean General Quotients (GQ) and
developmental profiles of the pre-school boys and girls obtained on the GMDS-ER were
compared.
An exploratory-descriptive quantitative research method was used. The sample (N =
64) was selected through a combination of non-probability, purposive and convenience
xiii
sampling. Within this framework, a between-subjects design in which matching was used to
control extraneous variables, was employed. Data was analysed using descriptive statistics
and independent sample t-tests to compare the GQs of the gender groups. A Hotellings T2 was
used to compare the Subscale profiles. No significant gender differences were found when
comparing the overall developmental and Subscale profiles of the boys and girls on the
GMDS-ER. However, certain interesting trends did emerge from a review of the findings
when compared to the literature review and previous studies. The information generated from
this study has contributed to our knowledge base of the performance of South African
children on the recently released GMDS-ER.
Key concepts: Gender, Child Development, Child Developmental Assessment,
Griffiths Mental Development Scales, Griffiths Mental Development Scales-Extended
Revised, Demetriou’s developmental model of cognitive development.
1
CHAPTER ONE
INTRODUCTION
The present study focuses on comparing the developmental profiles of a sample of
South African pre-school boys and girls between the ages of 5- and 6-years-old on the
Griffiths Mental Development Scales-Extended Revised (GMDS-ER). Thus, this study falls
within the broad field of child development as it essentially explores whether the gender
groups in this sample differ developmentally. This chapter aims to contextualise the present
study by providing the reader with a review of the concepts of gender and child development,
followed by a discussion of a holistic and multi-cultural perspective of child developmental
assessment in the South African context. Particular attention is paid to the GMDS-ER, as it is
the assessment measure utilized for the present study. The problem formulation and aims of
the study are provided, followed by an outline of the chapters of the study.
1.1
Gender
Starting at the life-changing announcement at birth of the child’s gender, boys and
girls are expected to differ from each other in all kinds of ways (Golombok & Fivush, 1994).
Research has suggested that knowing a person’s gender causes assumptions and predictions to
be made about a whole host of other characteristics about that person, and that very early in
development, children themselves learn culturally prescribed gender stereotypes (Golombok
& Fivush, 1994). The majority of the research conducted on gender development occurred
around the 1960s and 1970s. During that time, the psychometric conceptions of intelligence
held a substantial influence on psychometric measurement for the next three generations, and
focused narrowly on verbal, visual-spatial and quantitative abilities (Luiz et al., 2006a). The
existence of gender stereotypes prompted several researchers to investigate whether gender
differences existed within these intellectual domains, generating a substantial amount of
research.
However, it is important to note that historically many psychologists were opposed to
gender comparisons of any nature, fearing that when differences were found, the data would
be interpreted and misused in ways that supported a misogynist agenda (Halpern, 1997). As a
result, research conducted on gender differences in intelligence has been the topic of much
controversy and sensitivity, reflected by the contradictory evidence documented in chapter
two of this study.
2
Research findings on children’s gender development have been categorized according
to those findings that reveal gender differences and those findings that reveal gender
similarities. When intelligence or IQ tests were originally constructed, they were intentionally
designed to avoid producing any overall differences in male and female performance (Hyde &
McKinley, 1997; Snow & Weinstock, 1990). Careful analyses have concluded that there is no
difference in the overall performance between males and females in intelligence tests (Flynn,
1998; Halpern & La May, 2000). However, a pattern of differences have been found
indicating that boys are better at some tasks and skills, whereas girls are better at other tasks
and skills (Arceneaux, Cheramie & Smith, 1996; Blakemore, Berenbaum & Liben, 2009;
Born, Bleichrodt & Van Der Vlier, 1987; Halpern, 2000). In 1974, Maccoby and Jacklin
reviewed the results of more than 1,600 studies that compared males and females on some
behaviour or psychological characteristic. They were as interested in similarities as they were
in differences between the genders, and found that gender differences were well-established in
areas of verbal, visual-spatial, quantitative ability and aggression. In chapter two, literature
and research studies that have recorded gender differences and similarities between boys and
girls will be described according to these areas.
The influence of gender on the performance of South African boys and girls on the
Griffiths Scales has not received considerable interest. A review of the research conducted on
the different versions of the Griffiths Scales indicate that there are more studies reflecting a
pattern of gender differences, as opposed to those that have not. Interestingly, a literature
survey as well as a conclusive NEXUS search revealed that to date there are no recorded
studies in South Africa comparing the development of boys and girls in their early childhood
years on the recently released GMDS-ER.
1.2
Child development
The growth and development that pre-school children must cover between the ages of
two and six in order to develop the thought processes necessary for them to begin school is
vast (Fraiberg, 1959; Craig, 1996). Along this cognitive journey, children may encounter
several obstacles and challenges, which could hinder their developmental progression.
Therefore, one of the goals of studying development is to furnish the practitioner with the
theoretical information needed to identify developmental delays as early as possible. Other
goals include understanding changes that appear to be universal regardless of culture,
explaining individual differences, and understanding how children’s behaviour is influenced
by the environmental context or situation (Newcombe, 1996). The growth and development
3
that occurs during the early years of development has an impact on subsequent development.
Therefore, the earlier developmental problems are identified and the earlier the intervention
can be implemented, the greater the child’s chances are in overcoming their developmental
difficulties. Sadly, if developmental problems are not detected in early childhood, the future
development of the child can be significantly stunted thus resulting in a lifetime of lowered,
untapped potential (Schröder, 2004). Research conducted on gender development attempts to
understand whether boys and girls undergo the same pattern of developmental growth.
Dr. Griffiths was bestowed the title of the “architect of the most carefully constructed
infant scales for her development of the Griffiths Scales” (Luiz, 1994, p.5). She believed that
the assessment of mental development should involve a comprehensive investigation of a
child’s abilities, including motor, social and cognitive abilities by direct observation, testing
and reports from caregivers (Luiz et al., 2006a). Griffiths’ theoretical view of child
development contrasted with the psychometric conceptions of intelligence that emerged
during the time that the original Griffiths Scales was being produced. She was mindful of the
importance of interactions between the various learning avenues and developed a broad-based
approach to the developmental assessment of children (Luiz et al., 2006a). The learning
avenues of development were operationalised by developing corresponding Subscales. Whilst
Griffiths’ theoretical approach may appear somewhat dated, it remains fundamentally sound,
and its value is further reflected by the fact that her systemic view is consistent with current
theory of child development (Stewart, 2005).
A controversy that has existed for several years among developmental theorists is
whether development occurs gradually in small increments or dramatically in large periodic
steps followed by periods of levelling out. Many of the older developmental theories
subscribe to a continuous view of development characterised by stages, whereas
contemporary developmental theories are advancing that child development does not progress
in such a fixed and predictable manner. Demetriou’s (2000; 2004) developmental model of
cognitive development originates from the information-processing perspective, and subscribes
to development occurring in a wave-like fashion thereby reflecting a modern systemic
approach to child development. Stewart (personal communication, June 30, 2008) considers
this modern developmental theory to be the most appropriate theoretical update to the
Griffiths Scales. Therefore, this theory serves as the theoretical basis for this study.
4
1.3
Child developmental assessment and the Griffiths Mental Development ScalesExtended Revised (GMDS-ER)
A holistic view of child development is emphasized in chapter three and similarly a
holistic perspective to the developmental assessment of South African children is vital in view
of the poor social conditions the majority of children in South Africa have experienced (Luiz,
1994). Brooks-Gunn (1990) stressed that the measurement of the well-being of a child should
include the assessment of the physical, cognitive, social and emotional developmental arenas.
Therefore, a comprehensive developmental assessment should include these four aspects of
functioning, which are not mutually exclusive (Luiz & Jansen, 2001). “If one accepts the
definition of child well-being offered by Brooks-Gunn as the goal we wish South African
children to attain, by implication a comprehensive measure of development is required” (Luiz,
1994, p.9). The GMDS-ER plays a key role in this regard as it paints a complete picture of the
child’s developmental abilities.
Developmental measures are valuable tools practitioners use to guide therapeutic and
remedial interventions. Developmental measures can be categorized as either screening or
diagnostic measures (Foxcroft & Roodt, 2001; 2006). Screening measures usually provide an
overall view of the child’s development, rather than information relating to specific areas.
Diagnostic measures are more comprehensive in that they provide numerical scores and age
equivalents for both overall performance as well as for each specific area assessed (Luiz &
Jansen, 2001).
In review of the state of the developmental measures in South Africa, Foxcroft and
Roodt (2001; 2006) have found that during the last decade, there has been a concerted effort
made by researchers to attend to the need for more reliable and valid developmental measures
for use with South African children. Researchers have focused on the construction of new
culture-reduced tests and adapting, revising and norming assessment measures that have been
extensively used in other countries and thus proved to be reliable and valid (Foxcroft &
Roodt, 2001; 2006). According to Jansen (1991) there is no such thing as a ‘culture-free’ test
as psychological tests are samples of behaviour, which are affected by the cultural milieu in
which the individual is reared. Thus, a more realistic approach to developing a culture-free
test is to develop a test with content that is based on experiences which are common across
cultures and thus proves to be ‘culture-fair’ (Baker, 2005). The concept of play, whilst
perhaps in different forms across cultures, is a universal behaviour, and the Griffiths Scales
were developed by observing children in their natural environments, and whilst engaged in
natural activities (Allan, Luiz & Foxcroft, 1992). Furthermore, several studies conducted
5
within different parts of the world have demonstrated the Griffiths Scales applicability to
diverse population groups as they tap into experiences that are common to different cultures
(Luiz, Collier, Stewart, Barnard & Kotras, 2000).
The GMDS-ER was selected as the psychometric measure to generate the
developmental profiles of the boys and girls in the present study. The Griffiths Scales were
originally developed to assess child development across five Subscales, from birth to two
years of age. In the 1960s, the Scales were revised and extended to cover the period from
birth to eight years four months. A sixth Subscale, named Practical Reasoning, was added to
the Extended Griffiths Scales.
Whilst there is an extensive amount of support for the Griffiths Scales, several
comprehensive reviews in the 1980s and 1990s identified areas in which they could be
improved (Allan, 1988; 1992; Bhamjee, 1991; Hanson, 1982; 1983; Hanson & Aldridge
Smith, 1982; 1987; Hanson, Aldridge-Smith & Humes, 1985; Luiz et al., 1995). These studies
found that various items of the Scales were outdated and several items were culturally biased
and ambiguous (Kotras, 2003). Therefore, the original Griffiths Scales were no longer
providing the practitioner with reliable and valid results on the current evaluations of the
child. This provided the rationale for the revision of the Scales. The revision process began in
March 1994 and proceeded over a ten-year period. The GMDS-ER was launched in the
United Kingdom in 2004.
The GMDS-ER assesses the following Subscales, namely: Locomotor (Subscale A);
Personal-Social (Subscale B); Language (Subscale C), Eye and Hand Co-ordination (Subscale
D); Performance (Subscale E); and Practical Reasoning (Subscale F). A description of these
six Subscales, including examples of tasks, is provided in Table 1. These six Subscales
constitute the General Quotient (GQ) and produce a Mental Age (MA), which is the child’s
developmental age equivalent as measured by the GMDS-ER.
6
Table 1:
Description of the GMDS-ER Subscales
Subscales
Example of tasks
Description
Locomotor
This scale assesses gross motor
The ability to run fast
(Subscale A)
skills including the ability to
outdoors, bounce and catch a
balance, co-ordinate and control
ball, hop on one foot etc.
movements.
Personal-Social
This scale assesses proficiency in
The ability to give a home
(Subscale B)
the activities of daily living,
address, to fasten a shoe buckle
independence and an ability to
and to eat with a knife and fork
interact with other children.
etc.
Language
This scale assesses verbal ability,
Naming colours, relating a
(Subscale C)
the understanding of the meaning
story about a given picture and
of words and the ability to use
repeating 6-16 syllable
language effectively (receptive and
sentences etc.
expressive language).
Eye and Hand
This scale assesses fine-motor
Drawing, writing, threading
Co-ordination
skills and relates to visual abilities
beads and cutting with scissors
(Subscale D)
with handwork.
etc.
Performance
This scale assesses manipulation
Working with form boards of
(Subscale E)
skills including speed of working
4, 6 and 11 shapes, building
and precision.
blocks to resemble given
patterns etc.
Practical
This scale assesses problem-solving
Memory recall and repetition
Reasoning
ability, basic mathematical
of 1 to 5 digits, picture
(Subscale F)
comprehension and moral
arrangements of cards to tell a
reasoning. It indicates the child’s
story, visual memory etc.
ability to benefit from formal
schooling.
(Note: This table is based on Luiz et al., 2006a, p.3)
7
Research on the Griffiths Scales has primarily been conducted in two areas, namely
clinical and technical studies. Since the revision of the Scales, several studies have focused on
the performance of clinical and normal populations on the original Griffiths Scales and on the
GMSD-ER. In addition, technical studies have been conducted on the Subscales of the
GMDS-ER, its psychometric properties and its validity and reliability as a developmental
assessment. Research relating to the clinical utility of the Scales has provided evidence that
the Scales are useful in the clinical assessment and diagnosis of children from normal as well
as diverse population groups. Stewart (2005) has agreed that the value of the Griffiths Scales
is illustrated in the fact that they can be administered across all clinical populations and “have
proved to be a most effective and efficient tool in the assessment of young children, in a
diversity of cultural and social contexts” (p.25).
Since the introduction of the GMDS-ER, this updated measure has significantly
contributed to our growing knowledge base of child development within clinical samples.
Clinical studies utilizing the GMDS-ER have focused on: autistic children (Gowar, 2003),
HIV positive/AIDS infants (Kotras, 2001; Sandison, 2005), hearing impaired children
(Schröder, 2004), children with cochlear implants (Makowem, 2005), children with attention
deficit hyperactivity disorder (Baker, 2005), and a comparison of first and second born twins
(Davidson, 2008).
Research relating to technical studies has shown that the GMDS-ER is a reliable and
valid assessment measure (Beail, 1985; Griffiths, 1984; Luiz, 1988c; Mothuloe, 1990;
Stewart, 1997; Worsfold, 1993). The recent revision and restandardisation of the GMDS-ER
has necessitated investigations into its psychometric properties. This need for technical
studies has resulted in numerous research findings based on studies conducted on the
Subscales of the GMDS-ER (Barnard, 2000; 2004; Knoesen, 2005; Kotras, 2003; Moosajee,
2007; Povey, 2008). Other studies have focused on comparing a sample of normal South
African children with a sample of British children (Van Heerden, 2007; Van Rooyen, 2005).
The present study is a technical study as it assessed a normal sample of South African preschool boys and girls on the GMDS-ER. This study aims to further contribute to the credible
use of the GMDS-ER, by forming part of a greater project that intends to generate norms for
the South African population.
1.4
Problem formulation and aims
To date, no research has focused on comparing the developmental profiles of South
African pre-school boys and girls utilizing the GMDS-ER. Therefore, it is to this much-
8
needed area of research that the present study devoted itself. The research question that was
formulated to guide the study focused on whether the boys and girls within this sample would
perform differently on this assessment measure. Against this backdrop, this study aimed to
explore and compare the developmental profiles of a sample of normal South African preschool boys and girls between the ages of 5 and 6 years utilizing the GMDS-ER. In order to
achieve this, the following specific aims were explored:
1. To explore and describe the developmental profiles of pre-school boys and girls (in
the 5- and 6-year-old age group), with respect to their overall performance on the
GMDS-ER as well as their performance on the six Subscales.
2. To compare the General Quotient (GQ) and the developmental profiles across the six
Subscales of pre-school boys and girls (in the 5- and 6-year-old age group) on the
GMDS-ER.
1.5
Chapters of the study
Chapter two focuses on gender. An overview is provided of literature and studies
conducted on gender differences and similarities in children. The reader is then briefly
introduced to a proposed taxonomy of underlying cognitive processes envisaged to
contextualise findings from gender-related studies.
Chapter three focuses on child development. A definition of child development is
provided, followed by a discussion of the importance early childhood has on subsequent
development. The concept of intelligence will be explored in this chapter, with particular
attention being placed on the psychometric view of intelligence as the Griffiths Scales fall
within this category. The reader is then introduced to the theoretical tenets underpinning Ruth
Griffiths’ view of child development. Demetriou’s (2000; 2004) developmental model of
cognitive development is discussed in detail as this developmental theory serves as the
theoretical basis for this study.
Chapter four focuses on child developmental assessment and the GMDS-ER, with
emphasis placed on the need for a holistic and multi-cultural perspective in the developmental
assessment of South African children. An overview is provided of developmental assessment
measures utilized with infants and young children in South Africa, followed by a description
of selected international developmental measures that have been adapted for use in South
Africa. The reader’s focus is guided to the introduction and description of the GMDS-ER, as
it is the developmental assessment utilized in the present study.
9
Chapter five presents the problem formulation of the present study and the primary
and specific aims that guided the research process. The methodology employed in conducting
the study is delineated, including the research design, the participants, the sampling procedure
and relevant inclusion criteria, as well as the assessment measures utilized and the data
collection procedure. Lastly, a description of the statistical analysis is provided, followed by a
discussion on the ethical considerations relevant to the present study.
Chapter six presents the results and a discussion of the findings according to the
specific aims of the study.
Chapter seven provides the conclusions of the study as well as a critical evaluation of
the study, addressing its limitations, and recommendations for future research.
10
CHAPTER TWO
GENDER
Gender is not simply something that is imposed on children; at all points of development, children are
actively constructing for themselves what it means to be male or female
(Golombok, & Fivush, 1994, p.111)
2.1
Introduction
The physical differences between boys and girls, men and women are obvious and
universal. Literature on gender development indicates that children begin to consistently label
themselves as male or female around the age of two years, and that very soon after this, they
begin to associate particular behaviours and traits with one gender or the other (Golombok &
Fivush, 1994). It is understandable that the existence of gender stereotypes has prompted
several researchers in the past to question and investigate whether gender differences exist
specifically within cognitive and intellectual ability. “Research is the only way in which
psychologists can distinguish between those stereotypes that have a basis in fact (i.e. that are
statistically associated with one group more than another) and those that do not” (Halpern,
1997, p.1091). As a result of the myths surrounding gender differences, the value of a study
such as this, which aims to explore the developmental similarities and differences between a
sample of South African pre-school boys and girls, is realised.
In this chapter, the terminology issues in gender-related research will be clarified,
followed by an overview of literature and studies conducted on gender differences and
similarities in children. Thereafter, South African gender-related findings obtained on the
Griffiths Scales are discussed. A description is then provided of a proposed taxonomy of
underlying cognitive processes envisaged to contextualise findings on gender differences and
similarities.
2.2
Clarification of the terms ‘sex’ and ‘gender’
Until the 1970s, the term ‘sex’ was the commonly used term to refer to boys and girls
and men and women, and ‘sex roles’ was the most commonly used term to refer to
adopting cultural definitions of masculinity and femininity. More recently the term
‘gender’ has been used to refer to the same things (Blakemore et al., 2009, p.2).
One common perspective among many psychologists would reserve the term ‘sex’ for
references to biological aspects (hormones, chromosomes, genitals) of being male or female
and the term ‘gender’ for references to social characteristics defined by cultural norms and
beliefs (Blakemore et al., 2009; Ding & Littleton, 2005; Unger, 1979; Winstead, Derlega &
11
Unger, 1999). However, Maccoby (1988) has argued that by assuming biological causes for
some characteristics and social causes for certain others is problematic: “uncovering the
biological and social connections to behaviour is a major research objective, not something to
be assumed at the outset through the choice of terminology” (p.755). In agreement,
Blakemore et al. (2009) emphasize that “it is not always easy to know what is biological and
what is learned, and many behaviours may be influenced by several different factors” (p.3). It
seems likely that biological and social factors may interact with each other, and therefore in
the light of this view many researchers choose to use sex and gender interchangeably (Ding &
Littleton, 2005). According to Blakemore et al. (2009), “there is no convention for the use of
these terms that is accepted by all scholars of sex and gender, even within a single discipline
like psychology” (p.3). For the purpose of ensuring consistency throughout this work, the
researcher has opted to use the term ‘gender’. However, it should be pointed out that in this
context it is intended to be inclusive of both biological and psychological aspects.
Historically, research conducted on gender differences and similarities in intelligence
has been the topic of much controversy, which is reflected in the contradictory evidence
documented in this literature review.
Regardless of the position taken on the many questions that pertain to gender-related
similarities and differences, most psychologists would agree that gender is a
fundamental component of identity; it is the primary way of classifying humans into
groups, a fact that can be seen in all of the artefacts of popular culture (Halpern, 1997,
p.1091).
The majority of the research conducted on gender occurred around the 1960s and
1970s, when “psychological research had become increasingly methodologically
sophisticated, theoretical models were more prevalent, and the second wave of the feminist
movement arose on the scene” (Blakemore et al., 2009, p.33). During that time, the
psychometric conceptions of intelligence held a substantial influence on psychometric
measurement for the next three generations, and focused narrowly on verbal, visual-spatial
and quantitative abilities (Luiz et al., 2006a). As a result, a large body of research on gender
was conducted within these particular domains.
2.3
Historical influences on the research of children’s gender development
According to Blakemore et al. (2009), three major works were published in the 1960s
and 1970s that had a significant impact on the understanding of children’s gender
development. They were Eleanor Maccoby’s book entitled The Development of Sex
12
Differences published in 1966, Money and Ehrhardt’s book entitled, Man and Woman, Boy
and Girl, published in 1972; and Maccoby and Jacklin’s book entitled The Psychology of Sex
Differences published in 1974 (Blakemore et al., 2009). Eleanor Maccoby has been
considered to be one of the most influential developmental psychologists of the 20th century,
and her publication in 1966 was regarded as a “major turning point in the study of children’s
gender development” (Blakemore et al., 2009, p.33). This book focused on understanding the
possible reasons for gender differences and not just merely documenting the differences
themselves. Research in gender development in the early part of the 20th century focused on
the examination of gender differences with little systematic investigation into the roots of
these differences and had no clear theoretical foundation on which to base the findings
(Blakemore et al., 2009). Mischel’s (1966) social learning theory and Kohlberg’s (1966)
cognitive developmental theory was introduced in this text and to date remains among the
major theoretical models that guide research into children’s gender development (Blakemore
et al., 2009).
John Money and Anke Ehrhardt’s publication in 1972 focused on the topic of
formation of gender identity and gender role, and they argued that “it was outmoded to ask
questions about biological versus environmental influences on gender identity and gender
role”, as they asserted that, “development unfolds with a series of interacting influences”
(Blakemore et al., 2009, p.35). Money has been criticised for focusing so narrowly on
biological factors in his views about gender, as well as for not being biological enough
(Diamond & Sigmundson, 1997; Rogers & Walsh, 1982). Blakemore et al. (2009) disagree
and believe that Money and Ehrhardt emphasized both factors.
In Maccoby and Jacklin’s (1974) book, results of more than 1,600 studies that
compared males and females on some behaviour or psychological characteristic were
reviewed. Compared to previous works on the topic of gender development, Maccoby and
Jacklin were as interested in similarities as they were in differences, which set their book
apart from previous reviews on the topic (Blakemore et al., 2009). They pointed out a serious
flaw in research on gender in that when differences were not found, information about the
lack of difference was usually not published.
Therefore if a handful of studies on some topic found a difference between males and
females, and published such a difference, the finding would be repeated in textbooks
and other sources for years, yet there might be many more studies that did not find
such a difference that did not enter published scholarship (Blakemore et al., 2009,
p.35).
13
This book was organised into three sections, namely a) intellect and achievement, b)
social behaviour, and c) origins of sex differences (Maccoby & Jacklin, 1974). Within
intellect and achievement, Maccoby and Jacklin discussed research on perception, learning,
memory, achievement and ability testing, and achievement motivation. They found that the
basic processes of perception, learning and memory were very similar in males and females.
Specifically, they concluded that girls had better verbal skills and boys had better spatial and
mathematical skills, but found that consistent differences only emerged during adolescence
(Maccoby & Jacklin, 1974). They also concluded that there may be greater male variability in
spatial or mathematical skills, but not verbal skills and that despite females obtaining higher
grades at school, their achievement was less than males after leaving school (Blakemore et al.,
2009). Maccoby and Jacklin found that it was much more difficult to examine social
behaviour in children than in the cognitive domain, nonetheless a large number of social
behaviours were examined. They found that boys were more aggressive with their rough-andtumble play and fighting than girls, especially in terms of direct, physical aggression. This
book has shaped research on gender development for the next generation as researchers are
still actively citing it 34 years since it was first published (Blakemore et al., 2009).
Research findings on children’s gender development have been naturally placed
within two categories, namely those findings that show gender differences and those findings
that show similarities. Over the years, these two categories have been given different names,
such as the alpha bias or the gender differences hypothesis and beta bias or the gender
similarities hypothesis (Blakemore et al., 2009; Hyde, 2005). Due to the vastness of
information within this area, research findings documented in this chapter are presented
within these two categories. Before this is done, it would be of assistance to the reader to first
be provided with an overview of the statistical methods utilized in research on gender
differences to enable them to make sense of the findings reviewed in this chapter. To achieve
this purpose, the statistical methods of meta-analysis, narrative review and effect size will be
briefly described in the following section.
2.3.1
Meta-analysis
The question of how to integrate scientific knowledge had become an important one
due to the fact that empirical research on gender differences in cognition had accumulated
(Caplan, Crawford, Hyde & Richardson, 1997). For most of the 20th century, findings on
gender differences were summarised using narrative reviews, in which they read and
organised the research and tried to make sense of the pattern of findings (Blakemore et al.,
14
2009). The reviews included in Maccoby and Jacklin’s (1974) research is illustrative of this
approach. “Although narrative reviews are still being done, another important technique was
developed in the 1970s called meta-analysis” (Blakemore et al., 2009, p.74). Meta-analytic
reviews of gender research emerged in the 1980s and have continued in contemporary work
(Hyde, 1986; 1994; Johnson & Eagly, 2000; Kimball, 2000). Caplan et al. (1997) have
defined meta-analysis as a “systematic, quantitative technique for aggregating results across
different studies, thus reducing some of the subjectivity involved in narrative review” (Caplan
et al., 1997, p.31). Blakemore et al. (2009) explain the meta-analysis method in the following
edited description.
After locating all the studies that include data relevant to that topic, the researcher
calculates an effect-size for each study, usually d, and then calculates an average of all
effect sizes. The researcher then calculates whether all the effect sizes are
homogenous….According to Kimball (2001), most of the meta-analyses on gender
differences have data with effect sizes that are not homogenous….The researcher then
tries to determine what factors might have led to the different effect sizes and divides
the full set of studies into subsets that have similar effect sizes and then attempts to see
what differentiates the groups of studies that produce large versus small effects (p.74).
Specifically, the concept of effect size measures the magnitude of gender differences,
and the most commonly used index is d, which is the difference between the means of the two
groups expressed in terms of standard units by dividing the pooled within-group standard
deviation (Hyde, 2005). In analyses of gender differences, d represents the ratio of the
difference between the means obtained by the male and female participants to the withingender variability (Caplan et al., 1997; Hyde, 2005). Whether the effect size is positive or
negative indicates the direction of the difference: a positive value of d indicates higher scores
for males, and a negative value of d indicates higher scores for females. Once the value of d is
computed for each study, a weighted mean effect size is computed across all the studies
(Caplan et al., 1997). According to Cohen (1969), an effect size of 0.20 is small, an effect size
of 0.50 is medium, and an effect size of 0.80 is large.
Throughout this chapter, the researcher will describe effect sizes, narrative reviews
and meta-analyses as findings of research on gender differences are discussed.
2.4
Gender differences
When intelligence or IQ tests were originally constructed, they were intentionally
designed to avoid producing any overall differences in male and female performance (Hyde &
McKinley, 1997; Snow & Weinstock, 1990). Despite the difficulty in looking for differences
in intellectual ability in tests designed not to have them, careful analyses have concluded that
15
there is no difference in overall performance of intelligence tests between males and females
(Flynn, 1998; Halpern & La May, 2000). However, a pattern of differences has been found,
indicating that boys are better at some tasks and skills, such as spatial tasks and mathematical
problem solving, whereas girls are better at other tasks and skills, such as verbal fluency,
writing ability and perceptual speed (Arcenaux, Cheramie & Smith, 1996; Blakemore et al.,
2009; Born, Bleichrodt & Van Der Vlier, 1987; Halpern, 2000). For example, Camarata and
Woodcock (2006) examined the performance of more than 4,000 participants ranging in age
from 2 to 90 years who took part in the standardisation studies of the Woodcock-Johnson
(W-J) series of cognitive and achievement batteries during the 1970s and 1980s. The W-J
measures general intelligence, as well as verbal ability, visual-spatial thinking, auditoryprocessing, fluid reasoning, long-term retrieval, processing speed, and short-term memory, as
well as subsets of each of those broader domains (Blakemore et al., 2009). As expected, no
difference in general intelligence was found. However, Blakemore et al. (2009) emphasized a
very significant finding that showed that females had faster processing speeds across almost
all of the timed tests and at most ages, although the difference was particularly noticeable
during adolescence. “This report of females having faster processing speed has not been
widely reported before now, and thus additional research will be needed before it will be
possible to judge whether this finding is replicable” (Blakemore et al., 2009, p.80).
Substantial research has been undertaken to examine differences such as these in
intellectual abilities. According to Hyde (2005), the differences hypothesis dominated the
popular media with “the belief that males and females, boys and girls, are psychologically
different” (p.581). Another common perspective, termed ‘alpha bias’, also emphasizes
differences and contends that males and females are very different (Blakemore et al., 2009;
Hare-Mustin & Marecek, 1988). Understandably, the examination of gender differences in
achievement and cognitive ability has resulted in an ample amount of literature on the topic
(Deaux, 1984; Fennema & Sherman, 1977; Geary, 1989; 1994; 1996; Halpern, 1986; 1989;
1997; Linn & Peterson, 1985; Maccoby & Jacklin, 1974; Naglieri & Rojahn, 2001; Voyer,
Voyer & Bryden, 1995). However, it is important to note that historically many psychologists
were opposed to gender comparisons of any nature, fearing that when differences were found,
the data would be interpreted and misused in ways that supported a misogynist agenda
(Halpern, 1997). “In the past, people who maximised gender differences often argued that
males had an inborn superiority” (Blakemore et al., 2009, p.69). On the other side of the coin,
others have argued that the biological, cognitive and social variables that vary as a function of
one’s gender are a critically important area of psychological inquiry, and, for this reason,
16
comparisons between females and males should become a routine part of scientific reports
(Eagly, 1990; 1994). Thus, extensive studies were carried out to investigate the authenticity of
the differences hypothesis, which provided significant contributions to the field of
psychology.
Maccoby and Jacklin (1974) found that gender differences were well-established in
the areas of verbal, visual-spatial, quantitative ability, and aggression. There are fewer studies
investigating gender differences in the behavioural areas, as it is a difficult construct to
measure. One study investigated possible differences in emotional and behavioural problems
between the genders and reported some differences manifested in boys versus girls as rated by
their teachers (Butler, Marsh, Sheppard & Sheppard, 1985; Hollis, 1995; Horacek, Ramey,
Campbell, Hoffman & Fletcher, 1987; Pianta & McCoy, 1997; Ramey & Campbell, 1991;
Reynolds, 1991; 1994). In this chapter, relevant literature and studies that have recorded
gender differences between boys and girls will be described below within these domains. In
addition, a brief outline of gender differences within aggression will be provided. However,
before proceeding to the following section, two common assumptions about gender
differences need to be brought to the reader’s attention when reviewing the literature. The first
is the assumption that a gender difference in some skill, ability or behaviour means that it is
true for all males and females, and the second assumption is that the finding of a gender
difference implies that it is biologically based, and therefore results in an unchangeable ability
or behaviour (Blakemore et al., 2009; Eagly, 1995; Halpern et al., 2007). Blakemore et al.
(2009) cautions, “both of these assumptions are very common and very wrong” (p.70).
2.4.1
Gender differences within language development and verbal skills
When investigating whether there are gender differences in the verbal domain, the
most obvious place to start looking is in early language development. The examination should
be guided by questions such as, ‘Do girls or boys learn to talk earlier?’, ‘Is the language use
of young boys and girls different?’ and ‘Does one gender have more language-related
problems such as stuttering or dyslexia?’ (Blakemore et al., 2009, p.80). Several studies have
found gender differences favouring females from infancy through to the pre-school years.
McCarthy (1954) compiled a comprehensive report on children’s early language
development, in which girls were reported to be slightly ahead of boys on several measures of
language development including age at first word, first combinations, average sentence length
at various ages, and grammatical correctness.
17
Maccoby and Jacklin (1974) reported that girls learned to talk slightly earlier than
boys, yet the differences were so slight that they were not statistically significant. More recent
studies have found that girls are slightly ahead of boys on some measures, particularly
vocabulary growth (Berglund, Eriksson & Westerlund, 2005; Fenson et al., 1994; Galsworthy,
Dionne, Dale & Plomin, 2000; Morriset, Barnard & Booth, 1995; Rome-Flanders & Cronk,
1995). One study reported that, on average, girls knew 13 more words than boys at 16 months
of age, 51 more words at 20 months, and 115 more words at 24 months (Huttenlocher, Haight,
Bryk, Seltzer & Lyons, 1991). Bornstein, Hahn and Haynes (2004) examined children
between 1 and 7 years of age on several different language development measures, such as
maternal and teacher reports, standardised measures of language skill, and analysis of
transcripts of spontaneous speech. They found that girls were consistently ahead of boys on
almost all of these measures between the ages of 2 and 6, but not before or after. “This
suggests that girls’ language development is advanced in early childhood, but that boys
eventually catch up” (Blakemore et al., 2009, p.81).
Gender differences within verbal ability between older boys and girls also show a
female advantage. Some studies have indicated that girls are superior with executive aspects
of language such as reading, writing, spelling, and rote memory (Buffery & Gray, 1972; Hutt,
1972). Hurlock (1981) also found that boys, as a group, lag behind girls, as a group, in
learning to talk. She stated that at “every age, boys’ sentences are shorter and less
grammatically correct, their vocabularies are smaller, and their pronunciations are less
accurate than girls” (p.171). According to Neisser et al. (1996) some verbal tasks show
substantial mean differences favouring females, which include synonym generation and
verbal fluency. However, there are findings in verbal ability that show a male advantage, for
instance McCarthy and Kirk (1963) found a consistent trend across all age levels, that boys
were better at visual coding, such as pointing at named objects when the stimulus was visual.
Buffery and Gray (1972) have attempted to provide an explanation for the female advantage
in verbal ability and suggested an innate neural mechanism for speech perception that is more
developed in girls. They found that this is related to the lateralisation of linguistic functions to
the left hemisphere.
Girls have fewer speech disorders, such as stuttering and dyslexia, than boys (Halpern,
2000; Hyde & McKinley, 1997). According to Blakemore et al. (2009), stuttering is three to
four times more likely to be found in boys, and dyslexia, which is a disturbance in the
processing of the sounds of language leading to difficulties with reading, is found two to ten
18
times more frequently in boys. “The more serious the dyslexia is, the more likely it is to be
found in boys” (Blakemore et al., 2009, p.81).
Most of the research conducted in this area has focused on linguistic parameters or
cognitive content, whereas much less has been done to investigate the functional aspects of
language use, particularly as related to gender differences. Work done by Cook, Fritz,
McCornack and Visperas (1985) aimed to investigate the functions of interpersonal speech in
a sample of young pre-school children (N = 32), and to ascertain how early these differences
are apparent if it is found that functional differences do exist. The findings of this study
indicated that males talked more to their male peers than did females. The results also showed
that males made significantly greater use of statements that expressed their personal desires
and statements that asserted leadership, assuming a teacher role, greater competency, and
imitation of an activity. According to the researchers, these findings were consistent with
other literature on gender differences in social interaction and with the literature on adult
males’ conversational style (Cook et al., 1985).
2.4.2
Gender differences within quantitative ability
There are many different kinds of quantitative or mathematical abilities and skills.
There are more routine abilities, such as counting, and the simple operations of arithmetic
such as addition or subtraction; and different areas of mathematics such as algebra and
geometry. There is a difference between computation and problem solving, where in the
former the correct answer is calculated without making errors and in the latter, one determines
the correct procedure to use, and then the procedure is used to find a solution to a problem
that is often stated in words (Blakemore et al., 2009). Maccoby and Jacklin (1974) concluded
that gender differences are well-established in mathematical ability. According to Hoyenga
and Hoyenga (1979) “males show a mathematical superiority” (p.235).
The age at which quantitative differences between the genders begins to emerge is
unclear. For instance, Maccoby and Jacklin (1974) asserted that gender differences in
mathematics performance were small or non-existent in childhood and that the male
advantage appeared beginning around the time of puberty. However, in a study conducted by
Robinson, Abbott, Berninger and Busse (1996) it was concluded that the male advantage in
mathematical giftedness could be seen as early as pre-school. Other studies (Hyde, Fennema
& Lamon, 1990; Neisser et al., 1996) have focused on the early years of school and have
shown that females have a clear advantage on quantitative tasks, but that this reverses
sometime before puberty where males then maintain their superior performance into old age.
19
Several studies have arrived at the same conclusion and have found a female advantage in the
early primary school years, when mathematics consists of computational knowledge and
speed; then little or no gender difference occurs throughout the rest of the primary school
years. In addition, they have found a male advantage when the mathematical concepts require
more reasoning and are more spatial in nature, in the context of solving problems in geometry
and calculus (Geary, 1996; Halpern et al., 2007; Hyde et al., 1990). Males also score
consistently higher on tests of proportional and mechanical reasoning (Meehan, 1984;
Stanley, Benbow, Brody, Dauber & Lupkowski, 1992).
Research has also examined whether boys and girls solve mathematical problems
differently, and if different strategies are found whether they could account for differences in
standardized test scores (Blakemore et al., 2009). On standardized tests, girls are more likely
to do well on problems that are familiar and well-defined and more likely to use strategies that
have been taught to them by their teachers (Gallagher & De Lisi, 1994; Gallagher et al., 2000;
Stumpf, 1995). Boys are found to perform better on problems that require a less well-defined
solution strategy, and more on figuring out the problem at the time, or on using novel
strategies (Blakemore et al., 2009). Halpern et al. (2007) cautioned that when interpreting
gender differences it is important to examine the distribution of the sample, and emphasized
the fact that differences depend on the portion of the distribution that is examined. As males
are more variable in quantitative and visual-spatial abilities, they explained that there are
more males at both high- and low-ability ends. For instance, researchers have identified
mathematically talented pre-schoolers, scoring one or two standard deviations above the
norm, and have concluded that males are over represented in this group even at this young age
(Robinson et al., 1996).
2.4.3
Gender differences within visual-spatial ability
Spatial skill is defined as “the ability to encode, generate, retrieve, or mentally
manipulate visual images in some way” (Blakemore et al., 2009, p.83). The kinds of items
that are generally included are mazes, paper-folding tasks, embedded figures, determination
of vertical and horizontal, and imagining the rotation of objects in two or three dimensions
(Newcombe, Mathason & Terlecki, 2002). A large body of research conducted over the last
25 years has revealed substantial gender differences for some, but not all, of the measures that
reflect visual-spatial information processing (Halpern et al., 2007). Researchers have found
that some differences in visual-spatial ability emerge during the infant years. According to
Reinisch and Sanders (1992), females have a perceptual advantage seen in early infancy, with
20
fluency differences in the toddler years. The male advantage in transforming information in
visual-spatial short term memory is seen as early as it can be tested at around age three and in
mathematical giftedness as early as pre-school (Robinson et al., 1996). Levine, Huttenlocher,
Taylor and Langrock (1999) reviewed the literature on gender differences in pre-schoolers’
spatial skills and found that, on average, pre-school boys are more accurate than girls at
spatial tasks that measure accuracy of spatial transformations and score higher on the Mazes
subtest of the Wecshler Pre-school and Primary Scale of Intelligence. They concluded that
gender differences in favour of boys are present on spatial tasks by age 4 years 5 months.
Similarly, Halpern (1993) also found reliable gender differences in visual-spatial tasks by age
4 years 5 months, prior to pre-school. It is interesting to note that some studies, in which
female superiority during the pre-school years has been documented, have shown that in
subsequent years the gender difference disappears and that the genders are equal until
adolescence (Berry, 1966; Coates, 1974). Males then begin doing better than females (Wolf,
1971), and this gender difference may last well into old age (Cohen, 1977). Townes, Trupin
and Fay (1980) found that boys are more advanced in spatial and motor skills than girls.
Dorfman (1977) found that at all ages between 6- and 19-years, males do better at moving a
spot of light over which they have control to intersect a moving target on a screen. Keogh
(1971) also found that when 9- and 10-year-old boys and girls were asked to reproduce a
visual pattern by walking it out on the floor, boys did better in all conditions. Among tenyear-olds, boys are better than girls at discriminating between various two-dimensional shapes
(Etaugh & Turton, 1977).
It is logical that an individual’s visual-spatial competency in later years is dependent
on the earlier development of these abilities. Cohen (1977) has argued that spatial ability
increases with age up to late adolescence, and that at any given age a person’s ability is highly
correlated with his or her relative ability at other ages. It has been documented that in tests of
visual-spatial ability, post-pubescent males scored higher than females, in fact only about 25
percent of the females scored above the median of the males (Bieri et al., 1958; Hakstian &
Cattell, 1975; Maccoby & Jacklin, 1974; McGee, 1976; Sherman, 1967; Vaught, 1965).
Several researchers have wondered whether there is a relationship between math
performance and spatial skills, that is whether spatial skills are part of the reason for the
gender difference in mathematics (Blakemore et al., 2009; Halpern, 2000; Linn & Petersen,
1986; Shea, Lubinski & Benbow, 2001). Several studies have found that spatial skills are
related to math performance, even after the impact of general intelligence is statistically
controlled (Casey, Nuttall & Pezaris, 1997; Casy, Nuttall, Pezaris & Benbow, 1995;
21
Friedman, 1995; Geary, Saults, Liu & Hoard, 2000). Spatial ability has found to be highly
correlated with performance IQ, which refers to the ability to apply information supplied in a
question in both younger and older children; and spatial ability is correlated with verbal IQ,
but only for older children (Crandall & Sinkeldam, 1964).
South African studies on gender differences within cognitive ability are limited,
however some have also supported the above findings. Kruger (1983) found girls to be more
advanced in both their school readiness and cognitive, motoric, and language ability than boys
(Edwards, 1975; Landman, 1978). An overview of the literature on gender development
points to another area in which extensive studies have also been done to investigate whether
gender differences exist and that is in children’s display of aggression. As the area of
behavioural gender differences is not within the focus of this study, the purpose of its brief
exploration in the following section is to provide the reader with an understanding of the
nature of the studies conducted on gender differences.
2.4.4
Gender differences in aggression
Aggression is typically defined as behaviour that is intended to hurt or harm another,
or an action that is perceived by the victim as hurtful (Coie & Dodge, 1998). Maccoby and
Jacklin (1974) concluded that aggression was the most consistently found social behaviour
that differed between males and females. In addition, they concluded that the difference was
found as soon as children were capable of behaving aggressively, and that although
aggression itself declined with age, the gender difference continued into adulthood
(Blakemore et al., 2009). In their review, they identified different types of aggression, namely
physical, verbal, or fantasy (pretending to harm another or thinking about it) aggression.
There is also a form of aggression termed social aggression, in which people harm others by
manipulating their social relationship, which damage another’s self-esteem, social standing or
social relationships (Crick & Rose, 2000; Underwood, Galen & Paquette, 2001).
Blurton-Jones (1972) investigated a sample of 25 atypical children to determine which
gender displayed more aggression. They found a higher level of aggression in boys than in
girls. It has also been documented that behavioural gender differences are found across a
variety of cultures. For example, the cross-cultural work reported by Whiting and Pope (1988)
involved time-sampled behaviour observations in seven cultures. Two age cohorts were
observed in each culture: children from 3 to 6, and from 6 to 10. In all the cultures studied,
direct physical assault of one child upon another was rare, but what they did find was that
boys engaged in more rough-and-tumble play, exchanged more insults, and a boy was more
22
likely than a girl to counterattack if aggressed against in either verbal or physical form
(Maccoby & Jacklin, 1974; Whiting & Pope, 1988). A more recent meta-analysis of gender
differences in aggression was careful to control several characteristics of the studies used in
the meta-analysis, such as observational versus self-report (Knight, Fabes & Higgins, 1996).
They found that there was a very stable gender difference in aggression (d = 0.5 – 0.6), with
the largest difference in physical aggression observed directly (d = 0.8 – 0.9).
A vast amount of research has found contradictory evidence for the above notion that
developmental differences exist between the genders. Proponents of this view advance the
gender similarities hypothesis (Epstein, 1988; Hyde, 1985; 2005; Hyde & Plant, 1995;
Kimball, 1995). Golombok and Fivush (1994) have highlighted irregularities in research
findings that have reported gender differences.
Although there is widespread belief that males are superior in mathematical abilities and
females are superior in verbal abilities, in fact the research has shown very small
differences in these areas. Careful statistical analyses across hundreds of studies have
demonstrated that gender differences in ability in math and language are so small as to be
virtually non-existent for all practical purposes (p.177).
2.5
Gender similarities
According to Hyde (2005), the gender similarities hypothesis states that “males and
females are similar on most, but not all, psychological variables. Men and women, as well as
boys and girls, are more alike than they are different” (p.581). This perspective has also been
referred to as the ‘beta bias’, as it attempts to minimize gender differences (Blakemore et al.,
2009). People who minimize differences argue that the differences are small, inconsistent, and
artifactual (Hyde, 2005). In Maccoby and Jacklin’s 1974 review of gender research, they
found that not only were consistent differences rather thin on the ground, but the few
differences that were identifiable were usually of a small to moderate magnitude (Ding &
Littleton, 2005). Maccoby and Jacklin dismissed as unfounded many popular beliefs in
psychological gender differences, including beliefs that girls are more ‘social’ than boys; that
girls are more suggestible; that girls have lower self-esteem; that girls are better at rote
learning and simple tasks; whereas boys are better at higher level cognitive processing and
that girls lack achievement motivation (Hyde, 2005).
Hyde (2005) conducted a review of 46 meta-analyses which addressed the classic
gender differences questions – that is, areas in which gender differences were reputed to be
reliable, such as mathematics performance, verbal ability, visual-spatial ability and aggressive
behaviour. She found that 30% of the effect sizes were in the close-to-zero range, and an
23
additional 48% were in the small range. Therefore, 78% of gender differences are small or
close-to-zero. This result is similar to that of Hyde and Plant (1995), who found that 60% of
effect sizes for gender differences were in the small or close-to-zero range. According to
Hyde (2005), the “results from the review of 46 meta-analyses support the gender similarities
hypothesis” (p.581). In this regard, Ding and Littleton (2005) have stressed that it is important
to note that a larger number of myths exist regarding the gender differences between boys and
girls than the actual differences that have been consistently found in scientific research. Hyde
(2005) concluded that due to the fact that Maccoby and Jacklin (1974) only found wellestablished differences within the four areas of verbal ability, visual-spatial ability,
quantitative ability and aggression; that overall then “they found much evidence for gender
similarities” (p.581). Hyde (2005) and colleagues have criticised secondary reports of
Maccoby and Jacklin’s findings in textbooks and other sources, for having focused
exclusively on their conclusions about gender differences (Glietman, 1981; Lefrançois, 1990).
The literature and research findings demonstrating gender similarities are presented in
the following section.
2.5.1
Gender similarities within language development and verbal ability
Hyde reported the first meta-analysis of verbal gender differences in 1981, and re-
analysed the findings of studies reviewed by Maccoby and Jacklin. Twenty-seven studies of
verbal ability included in the original Maccoby and Jacklin review was analysed. Hyde (1981)
reported an effect size of 0.24 and concluded that the gender of the child alone accounted for
approximately one percent of the variance in verbal performance. The findings from this
meta-analysis indicate that although statistically significant, the results are small in absolute
magnitude (Bjorklund, 1995). Since the publication of Hyde’s report, several other metaanalytic studies of gender differences in verbal ability have been published, and they
generally conclude that whilst the difference in verbal abilities favouring females continue to
be found, the effect size is small in an absolute sense, and perhaps even getting smaller over
the decades (Bjorklund, 1995; Feingold, 1988; Hyde & Linn, 1988; Marsh, 1989; Plomin &
Foch, 1981).
Hyde and Linn (1988) conducted a meta-analysis on 165 studies that reported data on
gender differences in verbal ability, with the aim to reassess the belief that gender differences
exist. Averaged across all of these samples, the mean effect size was –0.11. This indicated a
slight female superiority in performance, but the researchers argued that the difference was so
small that it indicated that there are not any gender differences in verbal ability. More detailed
24
analysis of various types of verbal ability (e.g., vocabulary, reading comprehension, and
analogies) similarly yielded no evidence of a substantial gender difference (Hyde & Linn,
1988). Hedges and Nowell’s (1995) meta-analysis provided similar results and also found that
the differences were insignificant. Despite the criticism Maccoby and Jacklin (1974) have
received regarding their statistical methods, they too have found similarities between the
genders in verbal ability and stated that “for large unselected populations the situation seems
to be one of very little gender difference in verbal skills from about three to eleven, with a
new phase of differentiation occurring at adolescence” (p.85). Based on the recent metaanalyses it can be concluded that the effect size determines whether the differences obtained
are large enough to be considered significant. It appears that there are differences favouring
females in verbal abilities, but they are so small on average that knowing the gender of a child
would not help one predict how verbal he or she would be. As Bjorklund (1995) has stated,
“even if these differences are based in biology, the two genders are biologically more alike
with respect to verbal abilities than they are different” (p.348).
2.5.2
Gender similarities within quantitative ability
According to Hyde et al. (1990), reviewers have consistently concluded that males
perform better than females in quantitative and mathematical ability. The earliest measures of
some aspect of quantitative ability begin at about age three with measures of number
conservation, soon followed by enumeration (Maccoby & Jacklin, 1974). Several studies have
been conducted on pre-school children to determine if the gender similarities hypothesis is
accurate. “There appear to be no gender differences in performance on quantitative and
mathematical tasks during the pre-school years, or in mastery of numerical operations and
concepts during the early school years, except in disadvantaged populations” (Hyde et al.,
1990, p.85). Similarly, Farnham-Diggory (1970) found no gender differences in a sample of
282 children between the ages of 4- and 9-years-old with regards to mathematical synthesis
tasks. Studies conducted on children in their middle childhood years have also concluded that
gender differences do not exist. For instance, in a large study on a sample of 5,020 children
between the ages of 7- and 13-years-old, Parsley et al. (1963) found no significant gender
difference on tests of arithmetic fundamentals and reasoning tests. Siegel (1968) found no
significant gender differences in a sample of 192 children aged 7- to 11-years-old on digitprocessing tasks.
Hyde et al. (1990) conducted a meta-analysis of gender differences with regard to
performance in mathematics. This was based on 100 studies that provided effect sizes for 254
25
separate samples and represented the testing of over three million people. According to
Caplan et al. (1997) the findings were surprising given the long-held belief in a male
superiority in mathematics. This meta-analysis provided little support for the global
conclusions that “boys excel in mathematical ability” (Maccoby & Jacklin, 1974, p.352) or
“the finding that males outperform females in tests of quantitative or mathematical ability is
robust” (Halpern, 1986, p.57). The overall gender difference is small at most (d = 0.15 for all
samples or –0.05 for general samples) (Hyde et al., 1990). As a result, Hyde et al. (1990)
concluded that there are no gender differences in understanding of mathematical concepts and
in problem solving in the early childhood years.
2.5.3
Gender similarities within visual-spatial ability
Maccoby and Jacklin (1974) have located several studies in which visual-spatial
ability has been studied in children. They reviewed studies conducted on the spatial subtests
of the Differential Aptitudes Test and the Primary Mental Abilities Test, including mazes,
formboards and block counting. On the whole, Maccoby and Jacklin (1974) found no gender
differences in these measures in the early childhood and pre-school years. Shipman (1971)
studied a large sample of 1,411 children between the ages of 3- and 4-years-old and found
that there were no significant gender differences with regards to identifying and matching
geometric shapes. Similarly, Kraynak and Raskin (1971) investigated a sample of 64 3- and 4year-old children and found no significant gender differences with regards to matching two
and three-dimensional geometric stimuli. Strayer and Ames (1972) found no significant
differences when they investigated the performance of a sample of 40 4- and 5-year-old
children with regards to the number of errors they made when completing a formboard and
when coping geometric shapes. Brainerd and Vanden Huevel (1974) found no significant
differences when they studied a sample of 120 children between the ages of 5- and 6-yearsold in which they had to choose two-dimensional drawings to represent three-dimensional
objects. Mumbauer and Miller (1970) conducted research on a sample of 64 children between
the ages of 4- and 5-years-old on the Children’s Embedded Figures Test (CEFT) and found no
significant gender differences. Schubert and Croploy (1972) conducted research on a sample
of 211 children between the ages of 6 and 15 on the Block Design subtest of the WISC and
found no significant difference. Recently, Hyde (2005) collected the major meta-analyses that
have been conducted on psychological gender differences and included studies conducted on
the visual-spatial abilities with children on the areas of spatial relations, spatial perception,
26
mental rotation, spatial visualizations, and the progressive matrices. The effect sizes from
these studies ranged between the close-to-zero to small range.
South African studies have also found contradictory evidence for the notion that there
are differences between the genders. Kroukamp (1991) found that gender did not significantly
influence the prediction of scholastic performance. Furthermore, Stevenson, Parker,
Wilkinson, Hegion and Fish (1976) found little evidence to support the differences between
boys’ and girls’ basic cognitive processes such as learning and memory. In recent years,
research has turned to another area of development to examine whether gender differences
exist in motor development and skill. A brief overview is provided in the following section on
the influence of gender on motor skills.
2.5.4
The influence of gender on motor development and motor skills
Motor skills form an important part of a young child’s developmental progression.
In the first year of life, babies learn to roll over, sit up, crawl and walk. In the second
year these skills become much more fine tuned, and by the age of two children can
walk efficiently and do such fine-motor tasks as open drawers and build towers three
or four blocks high (Blakemore et al., 2009, p.75).
There are no gender differences in children in these early developmental
accomplishments (Blakemore et al., 2009). There are no gender differences in the motor
decisions young children make, in their ability to undertake risky motor activities, or in the
degree of risks they take in these physical arenas as infants and toddlers (Mondschein, Adolph
& Tamis-LeMonda, 2000). After the age of two years, gender differences begin to appear in
the development of physical skills. Eye-motor co-ordination is accomplished at a younger age
in girls, as it is not reliant on muscular strength (Karapetsas & Vlachos, 1997; Pollatou,
Karadimou & Gerodimos, 2005; Thomas & French, 1985). Studies on neuromotor
development, involving tasks such as repetitive finger movements, side-to-side jumping,
walking on toes or heels, or maintaining balance, was completed on 600 Swiss children
between 5 and 18 years of age (Largo et al., 2001a; 2001b). Very small gender differences
were found, with girls developing fine-motor skills and upper body tasks sooner and boys did
better on tasks requiring rapid movement. However, none reached statistical significance. On
tasks related to muscular strength, pre-school boys perform significantly better than girls,
such as ball throwing speed and throwing distance (Blakemore et al., 2009).
In conclusion, differences were found in some motor and physical skills. “When skills
reflect underlying neurological maturity or measure fine-motor skills, girls do slightly better.
27
When skills depend on substantial muscle strength, boys perform slightly better” (Blakemore
et al., 2009, p.77). Thomas and French (1985) attributed these differences to experiences and
gender role socialisation than to differences in the physical capacities of boys and girls. An
overview of the abovementioned literature and research studies demonstrates the
inconsistencies that exist regarding the possibility of gender differences. The emergence of
the gender differences hypothesis and the gender similarities hypothesis indicates the two
opposing sides on this controversial psychological topic. South African research studies
investigating the influence of gender on performance is limited to findings obtained on the
original Griffiths Scales of Mental Development (GMDS). The influence of gender on
performance on the recently released GMDS-ER has not been explored as yet.
2.6
Influence of gender on the performance of South African children on the
Griffiths Scales
The influence of gender on the performance of South African boys and girls on the
Griffiths Scales has not received considerable interest, which is reflected in the limited
findings documented in this section. A review of the existing Griffiths research indicates that
there are more studies in which gender differences have been found, as opposed to those that
have not. In a longitudinal study of language and intelligence, Moore (1967) compared the
Griffiths General Quotient (GQ) and Speech and Hearing Quotient of boys and girls at the
ages of 6 and 18 months. He found no significant differences at the age of 6 months, but at 18
months the speech quotient was significantly higher for girls. Mothuloe (1990) investigated
the use of the original Griffiths Scales as a measure of development for black Setswanaspeaking children, in which he adapted a number of the items on the Scales, as they appeared
culturally biased. His sample consisted of 45 children in the age range of 5 years 9 months to
7 years 3 months. Mothuloe (1990) found that girls obtained significantly higher scores than
boys in respect of the Locomotor Scale. Bhamjee (1991) using the original Griffiths Scales
conducted a study of 360 South African Indian children in the age range of 3- to 8-years-old.
She investigated the extent to which the variables of age, gender and socio-economic status
influenced the performance of her sample on the Scales. Bhamjee (1991) found significant
gender differences within the GQ and Personal-Social Subscale, with girls obtaining a higher
quotient and subquotient respectively.
Knoesen (2003) using the Revised Griffiths Scales explored the relationship between
the Scales and Grade One scholastic development. Her sample consisted of 93 children within
the age range of 5-years to 6-years-11-months. The results indicated that boys and girls
28
performed differently on each of the subscales. Unfortunately, Knoesen (2003) cannot
comment on the significance of this observed difference, as it was not statistically tested.
However, the results do prove useful for the purposes of descriptive observations and
necessitate the need for further investigation. Knoesen found the girls in the sample obtained
slightly higher subquotients than the boys for each Subscale, with the exception of the
Locomotor Scale. The girls obtained an above average GQ, whilst the boys’ GQ fell just short
of the above average cut off point of 110. The boys in the study obtained above average
performances on Subscales A (Locomotor), B (Personal-Social) and F (Practical Reasoning),
while the girls obtained above average performances on Scales A, B, C (Language), D (Eye
and Hand Co-ordination), and F. Both genders performed within the average range on the
Performance Subscale (Subscale E).
Van Rooyen (2005) explored and compared the performance of a sample of normal
South African children between the ages of 4- to 7-years-old with the performance of a
sample of normal British children on the GMDS-ER. The sample consisted of 129 South
African children and 161 British children. Significant differences were found favouring girls
in the South African sample on the Personal-Social, Eye and Hand Co-ordination,
Performance and Practical Reasoning Subscales. It is interesting to note that significant
differences were found on all the subscales within the British sample where the girls
performed significantly better than the boys.
However, no significant gender differences were found in the performance of boys
and girls on the original Griffiths Scales (Allan, 1988; Tukulu, 1996; Ward, 1997). Allan
(1988) compared the performance of a sample of 60 normal pre-school South African and
British children aged 5 years on the Griffiths Scales and found no significant difference
between boys and girls in their performance across the Subscales. Tukulu (1996) investigated
the relationship between the Denver II Scales and the Griffiths Scales using a correlational
method. Her sample consisted of 60 Black, Xhosa-speaking children between the ages of 3- to
6-years. Tukulu (1996) found that girls performed better than boys on both the Denver II and
the Griffiths Scales, although the differences were not statistically significant. Ward (1997)
conducted a similar study to Tukulu, in which she also investigated the use of the Denver II
Scales and the Griffiths Scales using a correlational method but with a pre-school Coloured
sample of 50 children, ranging in age from 3- to 6-years-old. Ward (1997) found differences
within the performance of her sample on particular Subscales, with few differences reaching
the required level of statistical significance. Ward (1997) found that the boys in her sample
performed better than the girls on the GQ, as well as on the Locomotor, Personal-Social and
29
Practical Reasoning Subscales. The results also indicated that the girls in Ward’s study
performed better on the Language, Eye-Hand Co-ordination and Performance Subscales.
An overview of the abovementioned literature and research studies reflects the
inconsistencies that exist regarding the possibility of gender differences. Although the
literature review indicates that numerous studies on gender differences have been embarked
upon, a literature survey as well as a conclusive NEXUS search revealed that to date there are
no recorded studies in South Africa comparing the development of boys and girls in their
early childhood years on the recently released GMDS-ER. In recent years, the tendency to
conceptualise the results of research findings within the context of verbal, quantitative, and
visual-spatial abilities has been heavily criticised (Halpern, 1997; Naglieri & Rojahn, 2001).
This has led to a taxonomy of underlying cognitive processes proposed to contextualise
findings of gender differences and similarities.
2.7
Towards a contemporary cognitive view of understanding gender performance
According to Naglieri and Rojahn (2001), understanding gender differences in
performance is partially based on the interpretations researchers give to the assessment
measures they utilize. They believe that some researchers make such inferences complicated
because they do not provide clear definitions of their constructs, the tasks are of a complex
nature, and a variety of tests may be used to measure the same construct. For example,
quantitative ability is typically measured on the basis of mathematical achievement. As a
result, some items are included such as basic maths operations, long division, word problems,
oral arithmetic problems, algebra, and the like whereas some topics (e.g., trigonometry) will
be excluded in assessment measures aimed at young children (Naglieri & Rojahn, 2001).
Similarly, studies that compare girls and boys in verbal ability could include a variety of tasks
such as vocabulary, verbal fluency, and verbal analogies that, although all verbal, may have
different cognitive demands and lead to inconsistency when measuring the verbal ability
construct (Halpern, 1997; Naglieri & Rojahn, 2001).
There has been a paradigm shift in views on intelligence that has now incorporated
underlying constructs across several domains that have not been recognised in standard
intelligence measures and as such cannot be documented. This led Halpern (1997) to propose
a taxonomy with the aim of unifying cognitive constructs for interpretive purposes. Halpern
(1997) rejected the verbal, quantitative and visual-spatial taxonomy domains. This
conceptualisation may have been used so often because it has been a superstructure for group
and individual tests of ability since the early part of the 19th century (Kaufman &
30
Lichtenberger, 1999). Although the schema has been popular in psychology and education for
about 100 years, its weakness is apparent both in the study of gender-related differences and
in intelligence testing (Naglieri, 1999). To replace this organizational system, Halpern (1997)
suggested a taxonomy based on “underlying cognitive processes, which offers a more finegrained analysis of how information is retrieved from memory and what participants are
doing when they are working on a cognitive task” (p.1092). The idea that working memory
can be separated into different functions is also consistent with recent work in cognitive
psychology (Shah & Miyake, 1996), and the separation of cognitive tasks into component
processing subsystems such as phonological and meaning subsystems is in accord with recent
findings with brain-imaging techniques (Halpern, 1997; Posner & Raichle, 1994). From this
perspective, Halpern (2001) summarised some of her major findings as follows:
Girls outperform boys on tests of verbal fluency, foreign language, fine-motor skills,
speech articulation, reading and writing, and math calculation, and they typically earn
higher grades in school in all or most subjects. Boys have been found to do better on
tasks such as mental rotation, mechanical reasoning, math and science knowledge, and
verbal analogies (p.430).
According to Naglieri and Rojahn (2001), these abovementioned findings were
organised into eight areas that appear to reflect the underlying cognitive processes described
by Halpern (1997) as areas in which girls and boys differ. Furthermore, Halpern (1993)
illustrated the value of a new taxonomy as follows:
In general, those tasks in which females tend to excel and exhibit large differences
involve generating synonyms, producing language fluently, and computing and
solving anagrams. The underlying cognitive processes for these tasks seem to involve
rapid access to and retrieval of information in memory. By contrast, the tasks in which
the literature shows that males excel are verbal analogies- the mapping of meaning in
relationships, mathematical problem solving, mental rotation and spatial perception
and using dynamic visual displays. Here the underlying cognitive processes involve
manipulating and maintaining a mental representation (pp.96-103).
Halpern’s (1993; 1997) efforts to provide alternative descriptions of the underlying
cognitive processes which she used to organise a variety of tasks and her suggested
taxonomy, is an important recognition of the need for a carefully articulated perspective, or
theory, from which differences between girls and boys can be understood (Naglieri & Rojahn,
2001). McHough, Koeske and Frieze (1986) argued that gender differences could not be
understood adequately unless girls and boys are compared according to a theoretical model of
cognitive function. Geary (1989) further emphasized that conceptual models of cognitive
31
differences between the genders should provide an integration of the neurological and sociocultural components that influence the development of cognitive processes.
2.8
Chapter overview
At the outset it was decided to use the term ‘gender’ throughout this work to maintain
consistency as complexity can result when sex and gender are used interchangeably. It was
noted that for the purposes of this study, the term gender should encompass both the
biological and psychological aspects of child development, and not merely the social aspects
as some have suggested. It was explained that the psychometric conceptions of intelligence
held a substantial influence on psychometric measurement during the 1960s and onwards for
the next three generations, and that psychometric measurement focused narrowly on verbal,
visual-spatial and quantitative abilities (Luiz et al., 2006a). As a result, a large body of
research on gender differences and similarities focused on these particular domains. The
reader was then provided with an overview of the literature and relevant findings within the
two differing perspectives, namely the gender similarities and gender differences hypothesis
according to the verbal, visual-spatial and quantitative domains. To provide the reader with a
comprehensive understanding of the nature of studies conducted on gender, a brief description
was allocated to the area of differences in children’s display of aggression. South African
research studies investigating the influence of gender on performance on the Griffiths Mental
Development Scales (GMDS) was discussed. Furthermore, it was highlighted that studies in
this regard in the local context is severely limited which is also reflected in the fact that no
studies have embarked upon exploring gender performance on the recently released extended
revised GMDS-ER. In conclusion, an overview was provided of a relatively new taxonomy of
underlying cognitive processes in which findings of gender similarities and differences can be
contextualised. The following chapter will explore the field of child development, with
special emphasis placed on the developmental model of information processing theory, which
will serve as a theoretical basis to guide and understand the results of the study.
32
CHAPTER THREE
CHILD DEVELOPMENT
3.1
Introduction
In this chapter, the focus will shift to the area of child development where a definition
of child development is provided, followed by a discussion of the importance early childhood
has on subsequent development. The concept of intelligence has played an instrumental role
in the understanding of how children’s cognitive abilities develop and for this reason will be
explored in this section, with particular attention placed on the psychometric view of
intelligence as the Griffiths Scales fall within this category. Thereafter, the theoretical tenets
underpinning Ruth Griffiths’ view of child development will be described, followed by a brief
overview of specific developmental theories that have had a valuable and lasting influence in
child development. Compared to these specific theories, which view development from a
more psychosocial perspective, Piaget’s theory of cognitive development will be described in
more detail as it paves the way for the introduction of the developmental theory used in this
study. Demetriou et al.’s (2002) developmental model of cognitive development, which
originated from the information-processing perspective, will be unpacked as this
developmental theory serves as the theoretical basis for this study as the results are guided
and understood in accordance with the theory. It is important to acknowledge the debate
surrounding the nature of development as it has continued for many years and focuses on
whether development progresses in a continuous versus discontinuous manner.
3.2
Child development
The growth and development that pre-school children must cover between the ages of
two and six in order to develop the thought processes necessary for them to begin school is
vast. During this crucial period young children can make things appear by turning their heads
or disappear by closing their eyes, to concept-forming, linguistically competent realists
(Fraiberg, 1959; Craig, 1996). Development is a broad term that refers to the “orderly and
relatively enduring changes over time in physical and neurological structures, in thought
processes, in emotions, in forms of social interaction, and in many other behaviours”
(Newcombe, 1996, p.4). The goal of studying development is three-fold, namely to
understand changes that appear to be universal regardless of culture, to explain individual
differences, and to understand how children’s behaviour is influenced by the environmental
context or situation (Newcombe, 1996). Another important reason to study development is the
33
early identification of possible developmental delays (Kotras, 2001; Newcombe, 1996;
Schröder, 2004).
It is imperative that child development is viewed holistically. This is reflected in the
interdisciplinary nature of information that exists about child development. Psychologists,
sociologists, anthropologists and biologists have joined forces with professionals from fields
such as education, medicine and social services in the search for solutions to problems faced
by children on a daily basis (Stewart, 2005). Consequently, the field of child development has
practical relevance for several disciplines resulting in a growing body of knowledge reflecting
developmental changes that are systemic in nature, and as such need to be studied holistically.
Griffiths emphasized the need for a broad-based conception of development, and
defined it as “the processes and rates at which growth and maturation of a child’s attributes
and abilities takes place” (Luiz et al., 2006a, p.1). Griffiths believed that the assessment of
mental development should involve a comprehensive investigation of a child’s abilities
including motor, social and cognitive abilities by direct observation, testing and reports from
caregivers. In line with this holistic approach, Kail and Cavanaugh (2000) posit four forces
fundamental to successful development, namely: 1) biological (genetic and health factors), 2)
psychological (perceptual, cognitive, emotional and personality factors), 3) socio-cultural
(interpersonal, societal, social and ethnic factors), and 4) life-cycle factors (similar events
affect individuals differently). Many psychologists investigated to what extent a child’s
development will negatively be affected if these fundamental forces are absent.
3.3
The impact of early development on subsequent development
Long before scientific studies of children were carried out, it was an accepted fact that
the early years are critical in the child’s development. This was expressed in the old Chinese
proverb, “As the twig is bent, so the tree’s inclined”. In a more poetic way, Milton expressed
the same fact when he wrote, “the childhood shows the man, as morning shows the day”
(Hurlock, 1978, p.25). The growth and development that occurs during these early years of
childhood has a significant impact on later development (Luiz, 1997). In studies conducted in
several areas of development, the persistence of early patterns of behaviour has been
demonstrated. For instance, it has been found that in attitudes and values, individuals change
little as life progresses even when marked cultural changes are taking place (Bronson, 1966;
Brooks & Elliott, 1971). Likewise, studies of personality have revealed that early patterns
persist relatively unchanged as time goes on (Hurlock, 1978). The first five years of the
child’s school experience, for example, has been called the ‘critical period’ in the
34
development of the achievement drive. The reason for this, Sontag and Kagan (1963) have
pointed out, is that high levels of achievement behaviour at that age are highly correlated with
achievement behaviour in adulthood. Results of such studies have justified this conclusion by
Bijou (1978):
Most child psychologists have said that the pre-school years, from about ages two to five,
are among the most important, if not the most important, of all the stages of
development, and a functional analysis of that stage strongly points to the same
conclusion. It is unquestionably the period during which the foundations are laid for the
complex behavioural structures that are built in a child’s lifetime (p.26).
Hurlock (1978) believes that as evidence accumulates to show that early foundations tend
to be persistent and to influence the child’s attitudes and behaviour throughout life, it
becomes increasingly apparent why early development is important. Hurlock (1978, p.27)
provides the following explanation of four important factors, in substantiation of this claim,
namely:
1. Since learning and experience play increasingly dominant roles in development, as
children grow older, they can be directed into channels that will lead to good
adjustment. The family handles this task, though the larger social group can provide a
culture in which children can fulfil their potentials. Guidance is most needed in the
early stages of learning to place the child on the right track, which will result in them
being less likely to get on the wrong track later;
2. Due to the fact that early foundations quickly develop into habitual patterns, they will
have a lifelong influence on the children’s personal and social adjustments;
3. Contrary to popular belief, children do not outgrow undesirable traits as they grow
older. Instead, patterns of attitudes and behaviour, established early in life, tend to
persist regardless of whether they are good or bad, beneficial or harmful to the child’s
adjustments; and
4. As it is sometimes desirable to make changes in what has been learned, the sooner the
changes are made, the easier it is for children and the more co-operative they are in
making changes.
Against this backdrop, most professionals are of the opinion that the earlier
developmental problems are identified and the earlier the intervention can be implemented,
the greater the child’s chances are in overcoming their developmental difficulties. Sadly, if
35
developmental problems are not detected in early childhood, the future development of the
child can be significantly stunted thus resulting in a lifetime of lowered, untapped potential
(Schröder, 2004). McGraw (1935) noted that a measure of a child’s abilities should
encompass the child’s physical, mental, motor, emotional and personality development. The
GMDS-ER has proven to be effective in holistically assessing a child’s abilities across the
several developmental domains listed, and serves as a valuable tool in identifying
developmental lags. According to Stewart (2005), it is imperative that “any description of
child development must include in the discussion a review of the concept of intelligence,
because a major aspect of child development is the development of intelligence” (p.97).
Therefore, in the following section the concept of intelligence will be reviewed, with
emphasis being placed on the psychometric approach to intelligence.
3.4
Concept of intelligence
There are multiple views on the concept of intelligence and about what behaviours
constitute intelligence. Initially, intelligence was defined as a general competence - an ability
that could be displayed across a wide variety of tasks. However, before long this view was
challenged by those who believed that different intellectual skills do not necessarily occur
together (Newcombe, 1996). Although many experts agree that intelligence is
multidimensional and includes several abilities, they do not always agree on the nature of
these abilities. Some divide abilities according to the content of the task - for example, verbal
comprehension, number comprehension, spatial relations, social skills, and musical ability
(Anastasi, 1987). Others emphasize cognitive processes such as memory, inference, and
problem solving (Newcombe, 1996). Although considerable clarity has been achieved in
some areas, no such conceptualisation has yet answered all the important questions and none
commands universal assent (Neisser et al., 1996). Indeed, when two-dozen prominent
theorists were asked to define intelligence, they gave two-dozen somewhat different
definitions (Sternberg & Detterman, 1986). Neisser et al. (1996) noted that there are many
individual differences to be taken into consideration that could further complicate the
attainment of a concept of intelligence that has universal assent.
36
Neisser et al. (1996) noted that:
Individuals differ from one another in their ability to understand complex ideas, to
adapt effectively to the environment, to learn from experience, to engage in various
forms of reasoning, to overcome obstacles by taking thought. Although these
individual differences can be substantial, they are never entirely consistent: a given
person’s intellectual performance will vary on different occasions, in different
domains, as judged by different criteria (p.77).
“Defining intelligence in children is more complicated and challenging because the
traits that may characterise intelligence in a two-year-old have changed considerably when the
intelligence of a seven year old is examined” (Stewart, 2005, p.99). Behaviours that reflect
intelligence change with age until a person reaches maturity (Beck, 1994). According to
Neisser et al. (1996), “concepts of intelligence are attempts to clarify and organize this
complex set of phenomena” (p.77). Although no conceptualisation has been accepted
universally as yet, Stewart (2005) believes that “theories guide our understanding” in this
regard (p.100).
Theories guide research into areas which might not otherwise attract interest or that
might otherwise seem too complicated to handle. Like a prospector’s map of a secret
treasure, they lead us to expect substantial yields in areas that would otherwise seem
to have little promise (Liebert et al., 1978, p.4).
Theories are vital tools in all scientific investigations; they provide an organizing
framework for observations of children, and theories with a strong empirical base provide a
sound starting point for practical action (Beck, 1994; Stewart, 2005). Theories systematise
observations into an organised pattern, and also develop a rational explanation of how or why
the observed phenomenon occurs (Craig, 1996). The advent of developmental psychology has
resulted in various theories, which provide valuable insight into the development of a child.
However, as Stewart (2005) has pointed out, “the study of child development does not
provide definitive answers as investigators often interpret behaviours in different ways”
(p.100). Each developmental theory has positive and negative aspects, but none is likely to be
the theory of development. This occurs because of the complexity of developmental
processes, different theories address discrete aspects of the process (Craig, 1996). In
accordance with the holistic view of development, a child develops across several domains
namely, physical, cognitive, emotional and social and therefore theories need to be able to
explain such domain-specific development. “In addition, arguments about how to
conceptualise human intelligence, as comprised of either a single or multiple factors, have
been heard in the field of mental testing for the best part of a hundred years and continue
37
unabated” (Stewart, 2005, p.100; Wood, 1998). Assessment has been the focus of this study
and it is imperative that practice is grounded within theory. As the development of
intelligence constitutes a major portion of the theory of child development it is necessary to
keep abreast of current thinking in this particular area. Furthermore, “while intelligence is
only one aspect of development, it is frequently emphasized and it is the main theoretical
construct upon which developmental assessment is based” (Stewart, 2005, p.98). In this
regard, the following section will briefly look at the psychometric approach to intelligence.
3.4.1
The psychometric approach to intelligence
Ever since Alfred Binet’s great success in devising tests to distinguish mentally
retarded children from those with behaviour problems, psychometric instruments have gained
significant importance in the field of psychology. Tests are used for many purposes, such as
selection, diagnosis, and evaluation (Neisser et al., 1996). Despite its apparent usefulness,
there has also been a debate regarding what constructs intelligence tests measure and how the
results should be interpreted (Stewart, 2005). This stems from the multiple views of
intelligence discussed in the previous section. As a result, “some believe that intelligence tests
measure a single, underlying general intelligence quotient (IQ), g, while others believe there
are up to 120 different abilities” (Stewart, 2005, p.101). According to Neisser et al. (1996,
p.78), “one common view today envisages something like a hierarchy of factors with g at the
apex, but there is no full agreement on what g actually measures: it has been described as a
mere statistical regularity (Thomson, 1939), a kind of mental energy (Spearman, 1927), a
generalized abstract reasoning ability (Gustafsson, 1984), or an index measure of neural
processing speed (Reed & Jensen, 1992)”. It is important to note that there have been many
disputes over the utility of IQ and g, where some theorists are critical of the entire
psychometric approach, while others regard it as firmly established (Neisser et al., 1996).
Griffiths (1954; 1970; 1984) developed the General Quotient (GQ) of the Griffiths
Scales in accordance with the principle of a general factor, and developed six distinct and
important avenues of development (Stewart, 2005). The psychometric conceptions of
intelligence emerged at the time that Griffiths was producing her original work. Griffiths was
mindful of the importance of interactions between the various learning avenues and developed
a broad-based approach to developmental assessment of children (Luiz et al., 2006a).
Griffiths operationalised her learning avenues of development by developing corresponding
subscales. Some learning avenues are more cognitive in content, namely Language,
Performance and Practical Reasoning Subscales (Stewart, 2005). Griffiths also ascribed equal
38
value to the other avenues of learning, such as those related to motor development, namely
the Locomotor and Eye and Hand Co-ordination Subscales, whilst the Personal-Social
Subscale addresses the adaptive aspects of development (Stewart, 2005). Griffiths’s broadbased approach conceptualises the holistic view of the child, and as Stewart (2005) succinctly
states “its value is reflected in the enduring status of the Griffiths Scales” (p.101).
3.5
Griffiths’ theoretical view of child development
Griffiths (1954; 1970; 1984) developed the Extended Scales based on the same
theoretical foundation as the Baby Scales. Griffiths’ (1954) view of child development is
reflected in her philosophy based on the “the basic avenues of learning” (p.28). Griffiths’
(1954) thinking is in line with modern systemic approaches, as illustrated by Figure 1.
Figure 1:
Griffiths’ basic avenues of learning
(Source: Griffiths, 1954, p.29)
39
The following quotation provides a brief overview of Griffiths’ (1954) description of
her basic avenues of learning.
The large circle represents the social background in which the child is situated. The
social factor encircles the child from the beginning, modifying and influencing all his
experiences. The next circle represents the physiological functions and organic
movements, awareness of which appears basic to experience. Superimposed on this
physiological substrate, certain weak physical attempts to move the body in various
ways… lead on to locomotor development. Arm and hand movements, at first vague
and poorly directed…develop later into more complicated manipulative acts. For
successful manipulative development, both hand and eye must co-operate. The two
develop together in manipulative performances of growing complexity. Almost from
birth, the normal baby makes vague sounds…listens intently to sounds and to the
voices of those around him. Hearing and voice together result in vocalisation and
babble, and the development of this is finally speech. All this development takes place
in time and space. Performance and Speech are the two main aspects of intellectual
development, and together form the basis ultimately of formal education both practical
and verbal. A more advanced stage is reached when the older child learns to read and
write, for then all four main avenues of learning, eye and hand together with voice and
hearing, all co-operate in the acquisition of this complex ability of understanding and
reproducing written language….All these abilities form, as they develop, a complex
and unified whole (pp.30-31).
Griffiths (1954) developed the Baby Scales at a time when the psychometric view of
intelligence played a dominant role in test construction and focused solely on the verbal,
visual-spatial and quantitative domains as indicators of intellect. Her holistic view of a
developing child was in stark contrast to her peers (Luiz et al., 2004a). In constructing the
Baby Scales, Griffiths acknowledged this psychometric view and stated that in construction of
the Griffiths Scales, she had to “cast a wide net to include a large number of different specific
abilities, so that g or general intelligence could be measured in as many as possible of its
manifestations” (Griffiths, 1954, p.31).
The object of Griffiths’s work was to develop a measuring instrument that would be
“reasonably exact, well-balanced and comprehensive so that those activities that later go to
make an efficient person, or as many as possible of those skills that are measured in assessing
intelligence in older subjects would be represented” (Griffiths, 1954, p.32). The Extended
Scales, which measured development in children from two to eight years of age, included a
new subscale, the Practical Reasoning Subscale, which records the child’s numerical
reasoning ability. According to Stewart (2005), Griffiths’s thinking was considerably
advanced for that time period as it is in line with current contemporary developmental
theories.
40
Stewart (2005) described Griffiths’ contribution to child development in the following
paragraph.
Griffiths’ theoretical approach may appear somewhat dated, but it remains fundamentally
sound. Most of its features are consistent with current theory of child development, as
Griffiths acknowledged the child within his social systems; she recognised the
physiological aspect of child development; and she attributed equal importance to the
psychological aspects of the child. She identified six domains of development, which she
stated provided a thorough view of development. She maintained that the domains
measured separate abilities, but emphasized that there is also considerable overlap
between them. All these aspects are consistent with current thinking on child
development (p.97).
3.6
Brief review of developmental theories
“A theory of child development can be likened to a lens through which we view
children and their growth. The theory filters out certain facts and gives a particular pattern to
those it lets in” (Thomas, 2005, p.4). This quote aptly describes the importance of
developmental theories, and illustrates the valuable insight they provide into child
development. Theorists agree that children are actively engaged in their own development.
Children try to make sense of the world around them, and in doing so, construct ideas and
hypotheses about how the world works. Children’s understanding of the world depends on
their ability to understand information, to make logical inferences, and to draw conclusions,
and these skills develop throughout childhood (Golombok & Fivush, 1994). A brief overview
will be provided on selected theories, followed by a detailed examination of a cognitive
developmental model of information processing, which will be used to frame the results of
this study.
Sigmund Freud was the first psychologist to focus on developmental issues and
particularly on very early development as an important psychological period (Golombok &
Fivush, 1994). His prominent theory was also the driving force of the psychoanalytic
tradition. Freud’s psychoanalytic theory describes the development of an individual as a
succession of stages determined by maturation and that progression from one stage to the next
is seen as the result of changes in the source of sexual energy (Meyer, Moore & Viljoen,
2002). Freud produced a model of child development that featured a series of growth stages.
He labelled these growth steps psychosexual phases because he believed the development of
the personality-the psyche-was critically influenced by the manner in which the child learned
to expend sexual energy (libido) from one period of life to the next (Thomas, 2005). The
psychosexual stages that form the cornerstone of his development theory are: 1) oral (within
41
the first year), 2) anal (within the second year), 3) phallic (within the third and fifth year), 4)
latent (within the fifth and sixth year), and 5) genital (seventh year onwards). The name of
each stage represents the most important physiological source of sexual energy at that stage.
Freud believed that personalities are divided into three parts, namely the id, ego and superego.
In addition, he delineated that there are three levels of consciousness, which are the
conscious, preconscious and the subconscious (Louw & Edwards, 1997). The participants of
this study fall within the latent stage of Freud’s theory. For the purposes of this study, it is
interesting to note that five and six year-olds are mainly concerned with learning their gender
role, and this period has often been called the gang age because children seldom voluntarily
form groups that include the opposite sex (Thomas, 2005). During this stage, Freud believes
that children play mainly with friends of their own sex because they want to consolidate their
acquisition of appropriate sex-role behaviours (Meyer et al., 2002).
Erik Erikson was a German-born psychoanalyst whose self-imposed mission was to
extend and refine Freud’s notions of personality development, with particular attention to
child development. Erikson’s theory of child development was guided by his adherence to the
epigenetic principle, which refers to the belief that “everything that grows is governed by a
present construction plan” (Thomas, 2005, p.88). Erikson acknowledged cultural variations
that could exist in the developmental process, which he believed may influence the types of
interactions children would have as they would be varied from one culture to another.
However, he held that “personality growth follows a sequence of inner laws that set the
potentialities for the kinds of significant interactions children will achieve with the people and
institutions they meet in their particular culture” (Thomas, 2005, p.88). Erikson’s ego
psychological developmental theory is based on stages. Erikson believed that the interaction
of individuals with their social environment produces a series of eight major psychosocial
crises the individual must work through in order to achieve eventual ego identity and
psychological health. At each stage, synthesis of a preferred choice and the developmental
crisis should be achieved in order to advance to the next stage. The eight stages are: 1) basic
trust versus basic mistrust (within the 1st year), 2) autonomy versus shame and doubt (2nd to
3rd year), 3) initiative versus guilt (3rd to 6th year), 4) industry versus inferiority (6th to 12th
year), 5) identity versus identity diffusion (12th to 18th year), 6) intimacy versus isolation
(18th to 25th year), 7) generativity versus self-absorption or stagnation (25th to 65th year),
and 8) integrity versus despair (60 years and onwards) (Davidson, 2008; Thomas, 2005).
According to Erikson the participants in this study fall within the initiative versus guilt
and industry versus inferiority stages. Children in the initiative versus guilt stage gain more
42
skill in using language, in moving about, and in handling things. The psychosocial modalities
of intrusion and inclusion emerge during this stage, and children are able to act on their
initiative and may experience guilt about their behaviour in which they feel conflicted
between their abilities to intrude into other people’s lives and their new-found realisation of
moral rules, which are encouraged by their identification with the parent of the same-sex
(Meyer et al., 2002). This stage is important in the development of the conscience and the
danger of this stage is that the conscience will develop too strictly or in a moralistic way.
Therefore, the ideal resolution of the crisis lies in finding a balance between the childlike
enthusiasm for doing and making things and the tendency to be too strict in self-judgement.
The ego strength that emerges in this stage is that of purpose (Meyer et al., 2002; Thomas,
2005). Children in the industry versus inferiority stage develop a sense of industry, learn to
handle the tools of their culture and become “keen collaborators in any productive process”
(Meyer et al., 2002, p.200). Children want to earn recognition by producing something and to
gain the satisfaction of completing work by perseverance. Children will develop a sound
sense of industry if they are provided with learning tasks and subsequent guidance by society
that they can accomplish and recognize as being worthy of their efforts. However, if the child
is not provided with such learning opportunities and thus not adequately prepared for school
life, a feeling of inadequacy and inferiority can develop (Thomas, 2005).
Alfred Adler (1930) viewed the first five years of life as being important rather than
demarcating developmental stages. Adler’s individual psychology developmental theory held
that within the first five years of life a prototype is formed. Adler emphasized certain
problems confronting the individual at specific age levels, which can be grouped into three
categories, namely occupational, social and sexual. Furthermore, he believed that there are
three childhood situations, namely inferiority, pampering and neglect. Adler proposed that
two types of factors have a significant effect on development, which is constitutional and
social environmental factors, where he considered influences being physical and family
respectively (Davidson, 2008). Compared to the abovementioned theories, which view
development from a more psychosocial perspective, the Piagetian approach to development is
based in cognitive theory. “Piaget’s theory of cognitive development has provided an
invaluable contribution which has had a lasting influence on the field of developmental
assessment” (Luiz, 1994, p.4). The theorist who most advanced our understanding of
cognitive development and provided an enduring influence on our thinking of child
development is Piaget (Stewart, 2005). Modern cognitive theory has built on aspects of
43
Piaget’s developmental theory and his profound observations, and it is for this reason that his
theory is examined in more detail below.
3.7
Piaget’s theory of cognitive development
Many regard Piaget to be the cognitive developmental psychologist of the twentieth
century (Moseley et al., 2005). Drawing upon biology, sociology and philosophy, his
psychological theorising and methodologies revolutionised a field that was dominated by the
contrasting perspectives of environmentalism and biological determinism (Moseley et al.,
2005). Piaget’s ‘clinical method’ of observing children in their natural environments, as well
as interviews with children engaged in various intellectual tasks, originated in the 1920s
(Moseley et al., 2005). Piaget held a similar philosophy to Griffiths in that he too valued
seeing and understanding the world from the child’s perspective. The central tenet of his
theory of cognitive development was that the child passed through a set of ordered,
qualitatively different stages. In essence, Piaget’s theory is described as a stage theory
(Moseley et al., 2005). Accordingly, he viewed development as unfolding through a series of
stages, characterising an invariant developmental sequence. The child must progress through
each of the stages in exactly the same order and no stage can be missed out. The stages are
associated with characteristic age periods although considerable individual differences can be
observed (Craig, 1996; Moseley et al., 2005). There are four stages, namely: 1) sensorimotor
stage (0-2 years), 2) pre-operational stage (2 to 7 years), 3) concrete operational stage (7 to 11
years), and 4) formal operational thought (11 years onwards) (Craig, 1996).
According to Piaget, the participants in this study would fall within the pre-operational
stage. During this stage, the child begins to communicate by using symbols and language.
Piaget considered the ability to grasp the logic of relations and classes as underpinning
intelligence and argued that children at this stage tend to focus upon one aspect of an object or
a situation at a time. Through a number of experiments, Piaget concluded that pre-operational
children experience difficulty in solving problems involving class-inclusion, conservation and
transitive reasoning. At this age children continue to display egocentrism, thus experiencing
difficulty in recognising that their own thoughts and perceptions may differ from those of
others (Craig, 1996; Moseley et al., 2005). Piaget believed that the impetus towards further
cognitive development and growth occurs when cognitive structures are incapable of
reconciling conflict between existing understandings and current experience. Development is
thus facilitated through the processes of assimilation, disequilibration and accommodation
(Craig, 1996). Assimilation is the interpretation of events using existing cognitive structures,
44
whereas accommodation describes the process whereby existing representations are modified
to encompass new experiences that cannot be assimilated. Cognitive restructuring involving
the development of more sophisticated schemata is the natural outcome. “This process has
been likened to the process of a filing system in which assimilation involves filing material
into existing categories, and adaptation involving modification of the existing system because
new material does not fit these” (Moseley et al., 2005, pp.191-192).
Piaget’s theory had a substantial influence on various schools of thought studying
intellectual development in childhood. According to Weinert and Weinert (2005), “Piaget’s
work ultimately caused a revolution in developmental theory with such concepts as activity,
adaptation, self-regulation, construction, and cognitive structures occurring in a universal
sequence of qualitatively different developmental stages” (p.192). However, there have been
many theoretical and methodological criticisms of Piaget’s theory. These criticisms have been
documented by Moseley et al. (2005) and will be described briefly. They found that
investigations that have attempted to replicate Piaget’s findings have yielded different results.
Such studies have demonstrated that children are capable of performing many cognitive tasks
and operations at an earlier age than Piaget outlined. Subsequently, it is now widely accepted
that Piaget underestimated the importance of social meaning and context of his experiments,
and the importance of children’s linguistic facility in understanding and responding to his
questions. Therefore, as a result many children failed to demonstrate their true capability in
the experiments. Studies have also indicated that individual’s operate at different levels in
different domains, which challenges Piaget’s notion that developmental stages had
overarching structures that operated across multiple domains (Bidell & Fischer, 1992). Lastly,
Piaget’s stepwise view of development is outdated with the latest findings in cognitive
development. There appears to be a considerable amount of overlap between stages, and
therefore it is more appropriate to regard development as a continuous process (Moseley et
al., 2005). In light of these criticisms, Piaget’s ideas were subsequently harnessed along
cognitive psychology’s information-processing paradigm resulting in the neo-Piagetian
theories of writers such as Pascual-Leone (1970), Fischer (1980), Case (1985) and Demetriou
(1998). This has resulted in a substantial body of more recent and contemporary literature on
cognitive development from the information-processing perspective. The informationprocessing theorists have constructed their theory on the foundation of Piaget’s cognitive
theory, using empirical methods to contribute to the existing knowledge base of cognitive
development. They have developed a groundbreaking theory that subscribes to the notion of
development neither being continuous nor discontinuous but instead occurring in a wave-like
45
fashion reflecting a more modern systemic approach to child development. This
developmental theory serves as the theoretical basis for this study as the results presented in
chapter six are guided and understood in accordance with the theory.
3.8
Demetriou’s developmental model of information processing
Demetriou and his colleagues set out to validate through empirical research an
integrated developmental model of the mind, first outlined in 1985 by Demetriou and
Efklides, and further developed by Demetriou (1993) and Demetriou, Efklides and Platisdou
(1993). In addition to a series of cross-sectional studies (Demetriou & Kazi, 2001), they
carried out a longitudinal study in which specially devised assessments were regularly
administered over a three-year period (Demetriou, Christou, Spanoudis & Platisdou, 2002).
Demetriou’s overall aim is to build and validate an overarching theoretical model, thereby
“laying the ground for integrating the study of intelligence and cognitive functioning with the
study of personality and self” (Demetriou & Kazi, 2001, p.218). Since the end of the
nineteenth century, three fields of psychology have attempted to understand the human mind:
cognitive, differential and developmental psychology. Demetriou (2000; 2004) believes that
the three fields must be integrated if a general theory of intelligence and mind is to become
possible. Demetriou et al. (2002) view the developing intellect as a multi-level and multisystem structure. This structure includes four basic constellations of processes and abilities:
processing efficiency, working memory, thinking and problem solving, and self-awareness
and self-regulation. They believe that these are likely to be the components of g, the general
factor of intelligence. According to this theory, the architecture of the human mind includes
two basic hierarchical levels of knowing (Demetriou & Raftapoulos, 1999; 2004). The first
level involves systems oriented to the environment, and the second level involves systemoriented constructs. At the intersection of these two levels, there is a functional system that
defines the activation and the interaction between the two knowing levels. It also needs to be
noted that the processes and structures in each of the levels are themselves hierarchically
organised (Demetriou & Raftapoulos, 1999; 2004).
3.8.1
Demetriou’s architecture of the developing mind
Demetriou et al.’s (2002) general model of the mind is based on the three concentric
circles shown in Figure 2, which represents seven specialised capacity systems or spheres
(SCSs), processing capacities and the hypercognitive system.
46
Figure 2:
Demetriou’s general model of the architecture of the developing mind
Note: This figure is based on Demetriou et al., 2002, p.5
(Source: Moseley et al., 2005, p.226)
The first knowing level involves systems addressed to the environment. The input
coming to this level is information coming from the environment and its output are actions,
overt or covert, directed to the environment (Demetriou & Raftapoulos, 1999; 2004). Through
empirical studies, these environment-oriented systems have been delineated into seven
systems of thought that specialise in the representation and processing of different domains of
relations in the environment (Demetriou et al., 2002). These systems are called specialised
capacity systems (SCSs) because each of them includes a characteristic set of operations and
processes which are appropriate for thinking and problem solving within its domain of
application (Kargopoulos & Demetriou, 1998). In addition, each of the seven systems is
biased to a different symbol system, the one most appropriate for that specialised capacity
47
system’s representational and computational needs, such as language for the propositional
system, mental images for the spatial system, and mathematical symbols for the quantitative
system (Demetriou, Efklides & Platsidou, 1993).
Development of thinking and problem solving within each SCS is influenced through
the combined influence of constitutional (maturational), socio-cultural and experiential factors
and inconsistent performance at the transition zones between levels in Figure 2 is very
common. Equally, Demetriou et al. (2002) found that development is very often uneven
across developmental domains (Demetriou, 2004; Demetriou & Raftapoulos, 2004; Moseley
et al., 2005). The four developmental stages identified in Figure 2 are essentially those of
Piaget: 1) sensorimotor, 2) pre-operational, 3) concrete operational, and 4) formal operational
(Moseley et al., 2005). The seven SCSs will be examined in more detail later in this section
and its applicability to the Griffiths Scales.
The second level of knowing which involves system-oriented constructs refers to the
hypercognitive system. Hypercognition refers to the supervision and co-ordination of
cognition (Demetriou et al., 2002). The input to the hypercognitive system is information
coming from the first level (SCSs). This information is organised into the maps or models of
mental functions, which are used to guide the control of the functioning of the SCSs and the
processing potentials available (Demetriou et al., 2002; Demetriou & Raftapoulos, 2004). The
hypercognitive system is conceived as being an interface between mind and reality, between
aspects of cognition, and between processing capacities and the SCSs (Demetriou et al., 2002;
Moseley et al., 2005). The hypercognitive system is hierarchically organised and is described
as having an active self-knowing component (working hypercognition) and a self-descriptive
component (long-term hypercognition) (Demetriou et al., 2002). Working hypercognition’s
efficiency is dependent on the individual’s processing capacities. The function of working
hypercognition is concerned with organising, monitoring and evaluating the responses and
performances of the self and of others, while long-term hypercognition incorporates a model
of the mind, a general model of intelligence and self-concept (Demetriou et al., 2002).
Working hypercognition “is responsible for the management of the processing system” and
“carries over to it, so to speak, both the person’s personhood and the person’s more general
views about the mind” (Demetriou & Raftapoulos, 1999, pp.328-329).
The functions of the working and long-term hypercognitive systems are summarised
in Figure 3. At the intersection of the environment-oriented level (SCSs) and the self-oriented
level (hypercognitive system), is the processing system or capacities. The processing
capacities, which consists of three dimensions, namely: speed of processing, attentional
48
control of processing and working memory are present in all thinking and have a major
influence on general problem solving (or psychometric g) (Demetriou et al., 2002). Speed of
processing refers to the maximum speed at which a given mental act may be efficiently
executed, thereby conserving mental resources. More specifically, it indicates the time needed
by the system to record and give meaning to information (Demetriou et al., 2002). Control of
processing refers to the processes that enable the thinker to stay focused on the information of
interest while filtering out interfering and goal-irrelevant information (Macleod, 1991; Posner
& Raicle, 1997; Sternberg, 1975). Working memory refers to the processes enabling a person
to hold information in an active state while integrating it with other information until the
current problem is solved (Demetriou et al., 2002). The optimal level of development within
the processing system is when an individual achieves processing efficiency (Demetriou &
Raftapoulos, 1999; 2004; Demetriou et al., 2002).
Processing efficiency can be described as the capacity of the thinker to focus on goalrelevant information, and to make use of available mental resources as efficiently as possible
(Demetriou et al., 2002). The processing system is a dynamic field that is always occupied by
elements coming from the other hierarchical levels, in proportions that vary from moment to
moment. Specifically, the input to this system is environment relevant information, skills, and
processes, which pertain to a SCS, and monitoring, regulation, and evaluation processes,
which pertain to the hypercognitive system (Demetriou & Raftapoulos, 1999; 2004). The
hypercognitive system is responsible for effecting the orchestration and the processing of the
SCSs and for the evaluation of the outcome of processing in relation to the goal of processing.
Working hypercognition specifically is the management system, which is responsible for the
management of the processing system (Demetriou et al., 1993). As shown in Figure 2, the
SCSs, the hypercognitive system, and the processing system are at one and the same distinct
and dynamically intertwined (Demetriou & Raftapoulos, 1999; 2004). That is, the SCSs are
formulated in response to the structure of the environment and become operative via the
processing system and known via the hypercognitive system (Demetriou, 2004; Demetriou et
al., 2002; Demetriou & Raftapoulos, 2004). The processing system is void if not fed by the
SCSs and undirected if not controlled by the hypercognitive system. Therefore, whilst they
are recognised as different operational and functional systems, there are still important generic
influences at work, involving processing efficiency, working memory, self-awareness and
self-regulation (Demetriou et al., 2002). The processing capacities and hypercognitive system
direct and manage each domain of thought (SCS) resulting in its efficient application and
49
functioning. Furthermore, the domains would not be specialised if the functions were not
directed to the correct environmental stimulus or input.
Figure 3:
Demetriou’s model of working memory
(Source: Demetriou et al., 2002, p.8)
3.8.2
Demetriou’s model of working memory
Demetriou et al.’s (2002) model of working memory incorporates and extends that of
Baddeley and Hitch (1974). Baddeley’s (1990; 1993) model, which has received extensive
empirical and theoretical scrutiny in the past ten years, is widely regarded as a good
approximation of the architecture of working memory (Caplan & Waters, 1999; Engle, 2002;
Kemps, De Rammelaere & Desmet, 2000; Morra, 2000; Ribaupierre & Bailleux, 2000;
Scheider, in press; Swanson & Sachse-Lee, 2001). As shown in Figure 3, Demetriou
incorporated the SCSs, processing capacities and long-term hypercognitive system to his
model of working memory to demonstrate the interrelatedness of the various components
(Demetriou, 2000; 2004; Demetriou et al., 2002).
In Demetriou’s model of working memory, the working hypercognitive system is
responsible for managing the operations of the specialised storage system, the SCSs and the
hypercognitive system. The specialised storage system receives information from the
50
environment. The visual, phonological and other specialised storage units draw on different
environmental sources. For example, the phonological storage unit only stores incoming
verbal information, whereas the visual storage unit only stores visual-spatial information. The
information is then sent to the appropriate SCS to be processed. For example, the working
hypercognitive system sends the information from the phonological storage unit to the verbalpropositional SCS. The output from the SCS is then stored in the working hypercognitive
system and co-ordinated with the existing knowledge filed in the long-term hypercognitive
system. The functioning of these interrelated components is dependent on the individual’s
processing capacities (Demetriou et al., 2002; Demetriou & Raftapoulos, 2004). The
processing capacities determine how effectively the information is channelled through the
various components and retained in working memory. The role of processing capacities is
reflected in Figure 4. Well-developed processing capacities ensure that less time is needed to
record and process the information thereby increasing the individual’s working and long-term
memory capacity (Demetriou & Raftapoulos, 2004).
Figure 4:
Demetriou’s model of working memory (Adapted)
(Source: Demetriou et al., 2002, p.8 [Adapted])
According to Demetriou et al. (2002) the role of working memory in the functioning
of thinking and problem solving remains strong. They believe that it is one of the main factors
underlying individual differences in thinking and problem solving. In other words, that
51
working memory is a mechanism for the implementation of the processing potential of a
given age into actual thinking and problem solving skills and abilities. Thus, differences
between individuals in the condition or use of this mechanism results in differences in how
fully they can transform their processing potentials into actual thinking and problem solving
skills and abilities (Demetriou et al., 2002). It is, however, recognised that individual
differences depend on social and cultural opportunities, such as education, the complexity of
the social environment in which the child develops and so forth (Demetriou et al., 2002).
3.8.3
Specialised capacity systems (SCSs)
As previously mentioned, Demetriou et al. (2002) categorized the environment-
oriented level into seven domains of thought. These systems of thought were induced on the
basis of evidence generated by a large number of studies, such as factorial studies looking for
underlying factors standing for different abilities and found the SCSs always coming out as
independent factors (Demetriou et al., 2002). These domains specialise in the representation
and processing of their corresponding relations in the environment. They are specialised
because each domain requires a particular method of processing information, and uses
different symbol systems. Due to the differing processes that occur within each SCS and
accompanying symbol system, the development of each system may proceed through partially
different types of developmental sequences and at different rates of progression (Demetriou &
Efklides, 1987; Demetriou & Raftapoulos, 1999; 2004; Demetriou, Raftapoulos &
Kargopoulos, 1999; Demetriou & Valanides, 1998; Demetriou et al., 2002). The seven SCSs
developed by Demetriou et al. (2002) are the systems of categorical thought, quantitative
thought, causal thought, spatial thought, verbal-propositional thought, social-interpersonal
thought and the drawing-pictographic system. Within each SCS consists a hierarchy of three
elements, namely 1) core elements, 2) operations, rules, skill processes and problem solving,
and 3) knowledge and beliefs (Demetriou & Raftapoulos, 2004). The domain and
composition of each of these seven systems is presented below.
3.8.3.1 The system of categorical thought
The primary function of categorical reasoning is to enable the child to identify
information that is important for the task at hand and reduce unnecessary complexity so as to
facilitate future information selection needs. Therefore, this domain specialises in the
handling of similarities and differences between objects (Demetriou & Raftapoulos, 2004).
Five- and six-year-old children pre-select a criterion for categorization and apply this criterion
52
to specify the identity of objects and their similarity relations (e.g., colour, shape etc.)
Children then use this criterion to classify things on the basis of having or not having this
attribute (Demetriou & Raftapoulos, 2004). Browsing, scanning, and comparison, which
enable the child to identify the properties related to a categorization task, are examples of the
operations involved in this system (Demetriou et al., 2002; Demetriou & Raftapoulos, 2004).
Classification and rule-induction strategies, which primarily involve organisation and
reduction of information into more general mental schemes, are examples of processes aimed
at the simplification of complexity for the sake of mental economy (Demetriou et al., 2002).
One of the items in the GMDS-ER within the Performance Subscale assesses a child’s ability
to assemble brick-boxes by colour at the age of four-years-old. The test administrator places
the lids in front of the incorrect box and asks the child to put the bricks back in their boxes
with the lids on. The four-year-old child selects the classification strategy of colour to
categorize the different objects, and assembles the brick-boxes with the corresponding colour
bricks and lids to complete the task. The child was not instructed to match the same colour
box with its lid; the child did this instinctively. This criterion is an example of one of the core
elements involved in this domain, that of categorical perception according to colour
(Demetriou & Raftapoulos, 2004). The formboard items within the Performance Subscale
require the child to use the core element of categorical perception according to shape, and
then match the similar insets with the corresponding place on the board. Without this
classification strategy this can prove to be quite a complex mental activity for a child. Fiveand six-year-olds are able to understand class inclusion relations based on natural kinds as
well (Demetriou & Raftapoulos, 2004). For instance, pre-school children understand that dogs
are members of the same species and cats are members of another species.
In other words, the core element within the system of categorical thought is that of
categorical perception and action (Demetriou & Raftapoulos, 2004). The second level consists
of the operations that enable the child to spot and process similarities and differences between
objects. The third level, the knowledge and beliefs within that SCS refer to a person’s
conceptions and misconceptions about the world, such as concepts people have about physical
phenomena or different types of people for instance (Demetriou & Raftapoulos, 2004).
3.8.3.2 The system of quantitative thought
According to Demetriou et al. (2002) all elements of reality can potentially undergo
quantitative transformations. They believe that things aggregate or separate so that they
increase, decrease, split or multiply in space or time for many different reasons. Demetriou
53
(2004) identified subitization as the core process involved in this system. Subitization is
defined as “the ability to specify the numerosity of small sets (smaller than three or four
elements) by simply looking at them” (Demetriou & Raftapoulos, 2004, p.30). One of the
items within the Practical Reasoning Subscale on the GMDS-ER assesses a four-year-old’s
ability to count four bricks correctly. However, it has been qualitatively observed that several
children that have been assessed on the GMDS-ER knew that there were four bricks without
needing to count. The second level of this domain involves operations such as counting,
pointing, bringing in and removing and sharing, and their internalised mental counterparts,
that is the four arithmetic operations (Demetriou et al., 2002; Demetriou & Raftapoulos,
2004). Demetriou (2004) has found that five- and six-year-old children develop the ‘increasedecrease scheme’, which is co-ordinated with the basic principles of counting and that this
generates a first understanding of number conservation. The Practical Reasoning Subscale of
the GMDS-ER is only introduced to children over the age of two years, and assesses the most
primitive indications of arithmetic comprehension and the realisation of the most practical
problems. Pre-schoolers are required to count 15 bricks, to compare two lines for length and
point to the longest one, to remove the middle brick from a row of five bricks and to know the
number of fingers on each hand as well as altogether. The third level of organisation within
this SCS involves all kinds of factual knowledge about the quantitative aspects of the world.
Examples include knowledge about reading the time, money values and rules underlying
everyday transactions, and numerical knowledge such as multiplication tables (Demetriou &
Raftapoulos, 2004). On the original Griffiths Scales, children were asked to name the
monetary values of coins and to tell the time using a clock-face on a board. However, these
items were removed during the ten-year revision process as a facet analysis of these items
found them to be of lesser value than other more relevant items on the Scales.
3.8.3.3 The system of causal thought
According to Demetriou (2000; 2004), objects and people are very often dynamically
related, sometimes functioning as the cause of changes and other times as the recipients of
causal effects. Causal reasoning enables the grasp of dynamic interactions between objects or
persons. Perception of fundamental causal relationships, such as when there is direct transfer
of energy from one object to another (e.g., we push something to move it) are examples of the
core processes involved in this system (Demetriou & Raftapoulos, 2004). At the second level
of organisation, causal reasoning involves operations enabling the thinker to manipulate and
represent causal relations (Demetriou, 2004). The most prominent operation utilized for this
54
purpose is trial-and-error manipulations aiming to uncover the causal role of objects.
Demetriou (2004) found that five- and six-year-olds develop causal schemes to enable them
to accurately describe causal sequences. An example of this is when a child discovers that a
toy no longer works. The child may search for the cause of this event by testing (usually
persistently and inflexibly) some idea directly suggested by the apparent aspects of the event
(Demetriou & Raftapoulos, 2004). The picture arrangement items within the Practical
Reasoning Subscale of the GMDS-ER measure causal reasoning. Picture cards are placed in
front of the child on the table, from left to right, in the incorrect order. The child is told that
the cards are in the wrong place and instructed to re-arrange the cards so that they tell a story.
The first picture arrangement series shows a boy kicking a ball to a girl, with arrows drawn on
the card to show the direction the ball is travelling in. This is a practice example and if the
child answers incorrectly, the test administrator explains the correct method until the child
conveys that he or she understands. Children whose causal reasoning is well-developed
proceed to more difficult picture arrangements, which are for older children. Causal reasoning
is not only related to cognitive ability purely but also to the psychological and social world of
the child. For instance, the immaterial effects exerted on human behaviour by desires,
ambitions, and feelings are examples of masked causal relations (Demetriou et al., 2002).
Young toddlers’ test boundaries set by their parents and soon learn that if they do not listen to
their parents, they will be punished. Another scenario could be that the child may get his or
her own way if their parents fail to establish solid boundaries for acceptable and unacceptable
behaviour. Psychologically, young children start grappling with cause-and-effect relations
before they reach pre-school (Demetriou et al., 1993). Their homes are their first classroom
and their parents assume the teaching role. Knowledge related to the ‘why’ and ‘how’ of
things pertains to the third level of the organisation of the system (Demetriou et al., 1993).
3.8.3.4 The system of spatial thought
This system is directed to the representation and processing of two aspects of reality,
orientation and movement in space and situations or scenes, which can be visualised mentally
as integral wholes and processed as such (Demetriou & Raftapoulos, 2004). Therefore,
anything that can be perceived and then somehow preserved as a mental image can become
the object of the activity of this system (Demetriou & Raftapoulos, 2004). Therefore, in this
domain, spatial relations within (the composition and structure of objects) and between
objects (relative distances, directions, and orientations) acquire prominence because they are
crucial in the representations of objects themselves, their location in space, and of the space
55
that surrounds them (Demetriou & Raftapoulos, 2004). Formation of mental images and
processes, such as perception of size, depth, and orientation of objects, constitutes the
foundations or core processes of this domain (Demetriou & Raftapoulos, 2004). To be able to
represent them, operate on them, and move between them, the thinker needs operations, such
as mental rotation, addition, and removal, which honour these relations, thereby enabling the
thinker to visualise the objects and space from the perspective needed so as to be able to
recognise and locate them and efficiently move between or to them (Demetriou et al., 2002;
Demetriou & Raftapoulos, 2004). Mental images, mental maps and scripts about objects,
locations, scenes or layouts stored in memory belong to the third level of the organisation of
this system (Kosslyn, 1983). Demetriou et al. (2002) found that five- and six-year-olds are
able to analyse pictures in their component parts, as well as able to construct spatial
dimensions and spatial operations, such as mental rotation. For example, upon assessing a sixyear-old boy on the GMDS-ER recently, the concept of mental rotation was very well
demonstrated. He had built a model of a bridge, and as the table that the boy and Tester were
sitting at was large the Tester moved closer and sat to his right. Out of his own, he started
building the model again and this time constructed it from his angle facing the Tester. He was
able to mentally rotate the model to visualise how the Tester would see it.
Spatial reasoning plays a vital role in the successful completion of several items that
span across the Subscales of the GMDS-ER. The Locomotor Subscale focuses on the
assessment of gross-motor skills, perceptual-motor abilities, visual acuity, figure-ground
perception and depth perception, balance, and flexibility etc. The Eye and Hand Coordination Subscale assesses visual-perceptual skills, perceptual-motor and sensorimotor
ability. The Performance Subscale requires a synthesis and analysis of skills, as it looks at
spatial logic and reasoning, visual-spatial and visual-motor skills, and spatial organisation. If
a child has spatial reasoning and perceptual problems, his or her performance on several
subscales of the GMDS-ER will be affected.
3.8.3.5 The system of verbal-propositional thought
Verbal reasoning facilitates interaction between persons, and it is used as a guide to
action. Core processes in this system underlie the ability, which is present from infancy, to
use the grammatical and syntactical structures of language in order to infer the relations
between the events or situations mentioned in a sequence of sentences (Braine, 1990;
Demetriou, 1998). At the second level of organisation, operations and processes in this
domain are primarily directed to the truth and validity relations between verbal statements so
56
that person may judge the accuracy of the information received and decipher deception etc.
(Demetriou et al., 1993; Demetriou & Raftapoulos, 2004). Two types of skills are used to
attain these aims. First, there are grammatical and syntactical skills enabling the individual to
interpret and interrelate the components in verbal statements so that information may be
abstracted in goal-relevant, meaningful, and coherent ways. Second, there are skills enabling
one to differentiate the contextual from the formal elements in a series of statements and
operate on the latter (Demetriou & Raftapoulos, 2004). For example, focusing on such verbs
as ‘is’ or ‘belongs to’, or connectives such as ‘and’, ‘if’, and ‘or’ directs thinking to the
relationships between the statements, rather than simply the statements themselves. These
processes, the second in particular, enable one to grasp the basic logical relations (‘and’) and
disjunction (‘either…or’), implication (‘if…then’), etc. (Efklides, Demetriou & Metallidou,
1994). Explicit knowledge about grammar and syntax and explicit knowledge about logical
reasoning belong to the third level of the organisation of this system (Demetriou &
Raftapoulos, 2004). Demetriou (2004) found that five- and six-year-olds are able to
distinguish propositions from each other and organise them in order to suggest a given
conclusion. In addition, they are also able to grasp and understand permission rules. For
example, if you do X then you can do Y. The Language Subscale of the GMDS-ER assesses
young children’s language ability. More specifically, the emphasis of this subscale is on
expressive language. However, it does measure a child’s receptive language abilities, verbal
and semantic reasoning, verbal comprehension, as well as general and applied linguistic
knowledge.
3.8.3.6 The system of social-interpersonal thought
This system deals with the understanding of social relationships and interactions
(Demetriou & Raftapoulos, 2004). This system involves operations and processes that enable
understanding and manipulation of the forces underlying verbal and non-verbal social
interactions, such as motives and intentions (Demetriou & Kazi, 2001; Demetriou, Kazi &
Georgiou, 1999). Demetriou et al. (2002) found that social thought is related to crystallised
intelligence underlying knowledge about the world. One of the areas that the Personal-Social
Subscale of the GMDS-ER assesses is that of the child’s ability to interact with other children
as well as his or her level of independence (Luiz et al., 2004a). Griffiths (1954) believed that
social interaction such as co-operative play with peers is important. Furthermore, whilst
emotional factors are known to affect performance on all of the subscales of the GMDS-ER, it
is believed that they impact this subscale in particular (Baker, 2005).
57
3.8.3.7
The drawing-pictographic system
This system involves multiple skills and operations that integrate many of the systems
above into an idiosyncratic whole that is particular to humans (Demetriou et al., 2002). This
system makes use of imaginal and kinetic processes and abilities for the sake of the pictorial
representation of the relations associated with any of the other systems (Demetriou et al.,
2002). Through this system, children can represent their environment or their thoughts
themselves by the production of drawings or any other kinds of signs (Demetriou & Kazi,
2001; Demetriou et al., 2002). Within the Eye and Hand Co-ordination Subscale of the
GMDS-ER are drawing items. Children are specifically asked to draw a person and a house,
whilst the other items require them to copy shapes and objects. Children’s drawings reveal
substantial information about their intellectual and emotional maturity. Psychological
projective measures utilize children’s drawings as they provide the psychologist with an
indication of the child’s self-concept, their view of their family and/or friends. Therefore, the
fact that a developmental theory of the mind is recognising the importance of the pictographic
system in child development is valuable.
The nature of development as postulated by Demetriou et al. (2002) is discussed in the
following section.
3.9
The nature of development
Thinking and problem solving processes are organised in domain specific systems,
which are differentiated on the types of relations they represent, and on the process and the
symbol systems to which they are biased (Demetriou et al., 2002). In other words, the
processing system and hypercognitive system processes exist within the SCSs but take on
specific functions to enable that domain to efficiently operate on that symbol system
(Demetriou et al., 2002). To reiterate, it was mentioned earlier that the development of
thinking and problem solving within each SCS is influenced through the combined influence
of constitutional (maturational), socio-cultural and experiential factors. Due to the differing
processes that occur within each SCS and accompanying symbol system, the development of
each system may proceed through partially different types of developmental sequences and at
different rates of progression (Demetriou et al., 2002). Demetriou et al. (2002) view the nature
of development as “a series of overlapping waves or cycles of change” (p.131). In this series,
the processes and functions of the various levels and systems of the mind may be at different
points in their own cycle of development. However, when one of them reaches a certain point
in its own cycle of development (e.g., processing efficiency), it opens the possibility for
58
another process or function to advance to a different point in its cycle (e.g., working memory
or problem solving) (Demetriou et al., 2002). There is a reciprocal growth relationship in that
the later processes may bounce back and alter the movement of the first process in its cycle
(Demetriou et al., 2002). It is important to add that the wavelength or rate of change is not
uniform across successive phases of development. It is logistic as anticipated by dynamic
systems theory (Fischer & Bidell, 1998; van Geert, 1994). According to the basic assumption
of dynamic systems theory, any kind of change (e.g., learning) is logistic when it occurs under
limited resources (Demetrou & Raftapoulos, 2004). The phases of logistic development of
the various abilities do not coincide. For example, processing efficiency approaches its peak
before the various domains of thinking and problem solving. These differences in the
development of the various processes reflect their functional relations as revealed by both the
structural equations and dynamic systems model (Demetriou et al., 2002). A review of child
development theory is not complete without recognising the continuity-discontinuity debate
that has existed amongst psychological theories for decades.
3.10
Continuity-discontinuity debate
A controversy has existed for several years among developmental theorists around the
issue of whether development occurs gradually in small increments or dramatically in large
periodic steps followed by periods of levelling out. An example of a theory that proposed that
development occurs in increments is Skinner’s behaviourism theory, in which he pictured
development as occurring in “imperceptibly small increments” (Thomas, 2005, p.39). In
contrast, Piaget proposed steps and sub-steps of cognitive development, whereas Freud
developed major psychosexual stages of growth. Havighurst proposed that children at
differing points in their life are confronted with specific developmental tasks and that these
form a succession of stages in development. Thomas (2005) found that the essence of many
theories is found in the sorts of stages postulated and in the way a child’s movement from one
level to the next is viewed.
Everyone agrees that development from one day to the next is gradual, and in this
sense growth is continuous and occurs in small increments. The real question is then
whether the child’s structure and behaviour periodically display symptoms that
warrant the label of a new stage of development? (Thomas, 2005, p.39).
Thomas (2005) has emphasized that parents, teachers, paediatricians and children
themselves are all interested in the matter of whether children are growing up ‘normally’,
resulting in the understandable tendency to question what a theory expects of developmental
59
stages. More specifically, how are levels or stages related to a child’s chronological age? Are
the stages universal and invariant for children in all cultures? (Thomas, 2005). These
questions are especially pertinent in the South African context, in which it is imperative to
have a view of child development that does justice to the different cultures. In answering the
first question about how stages are related to age, theorists such as Piaget, Freud and
Kohlberg have developed stages that are somewhat loosely tied to specific ages. The second
question about the universal and invariant attributes of a developmental theory is important to
consider as theories are used as a yardstick to determine a child’s normalcy in relation to his
or her peers (Thomas, 2005). It is interesting to note that many theorists view their stages as
universal and common among children in all cultures and their sequence invariant. Thomas
(2005) defines invariant as meaning that “not only are the stages found in all cultures for
which we have reports, but the nature of development is such that no other sequence in the
pattern of growth stages is possible” (p.40). Piaget, Erikson and Kohlberg assume invariance,
which has been questioned by critics such as Phillips and Kelley (1975). In addition, decisive
questions have centered on whether children progress through developmental stages at the
same pace, as well as whether they can display typical characteristics of more than one stage
at the same time. Terms such as retarded, normal, advanced, and gifted have traditionally
been used to describe children who are developing at particular rates compared to their peers,
regardless of whether development is viewed as continuous or stepwise (Thomas, 2005).
Piaget demonstrated in his theory about children’s ideas of causality that children are able to
operate on two stage levels simultaneously (Piaget, 1930). In conclusion, many of the older
developmental theories subscribe to a discontinuous view of development characterised by
stages, whereas contemporary developmental theories are advancing that child development
does not progress in such a fixed and predictable manner.
3.11
Chapter overview
This chapter focused on child development. Awareness was raised on the goal of
studying child development and it was identified that an important reason to study
development is the early identification of possible developmental delays. The section
highlighted that Griffiths (1954) argued for a broad-based conception of development, which
was in contrast to the psychometric view of intelligence at the time that Griffiths’ was
producing the Griffiths Scales. Emphasis was placed on the impact early development can
have on a child’s subsequent development and that the earlier developmental problems are
identified and intervention implemented, the greater the child’s chances of overcoming
60
developmental difficulties. The value of the Griffiths Scales was highlighted as it has proven
to be effective in holistically assessing a child’s abilities across the several developmental
domains listed, as well as serving as a valuable tool in identifying developmental lags. As
intelligence is the main theoretical construct upon which developmental assessment is based,
the concept and psychometric view of intelligence was discussed. It was noted that whilst
Griffiths’ theoretical approach may appear somewhat dated, it still remains fundamentally
sound and that most of its features are consistent with current theory of child development
(Stewart, 2005). More specifically, Griffiths acknowledged the child within his social
systems; she recognised the physiological aspect of child development; and she attributed
equal importance to the psychological aspects of the child (Stewart, 2005). Once a brief
overview of selected developmental theories was provided, more attention was paid to the
Piagetian approach to development. Thereafter, Demetriou’s (2000; 2004) developmental
model of information processing was presented in some detail and selected as the theory to
guide and understand the results of this study. The reader was then provided with a brief
overview on the continuity versus discontinuity debate of development to inform his or her
own thinking on the issue.
Childhood development has a profound impact on the course of an individual’s life.
As the significance of understanding the process of early childhood development more fully
increases, so does the need to establish with more confidence the value and role of
developmental assessment in the early identification of problems. The following chapter
explores child developmental assessment, focusing on a thorough description of the GMDSER as this study has utilized this assessment measure to explore and compare the
development of a sample of South African pre-school boys and girls.
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CHAPTER FOUR
CHILD DEVELOPMENTAL ASSESSMENT AND THE GRIFFITHS MENTAL
DEVELOPMENT SCALES-EXTENDED REVISED
4.1
Introduction
Children are the touchstone of a healthy and sustainable society. How a culture or
society treats its youngest members has a significant impact on how they will grow, prosper
and be viewed by others. Unfortunately, not all children are born healthy; not all children
have access to good nutrition, adequate health care, and acceptable housing; not all children
are raised by parents who can comfort, nurture, and challenge them appropriately; and not all
children are born free of disabilities or other biological vulnerabilities. It is the mission of
early childhood intervention to help young children and their families thrive (Shonkoff &
Meisels, 2000). It is against this backdrop that this chapter provides an overview of child
developmental assessment, with an emphasis being placed on the need for a holistic
perspective when considering the developmental assessment of South African children. Child
developmental assessment within a multi-cultural context will be discussed including the
Griffiths Mental Development Scales-Extended Revised’s (GMDS-ER) applicability to
diverse population groups. An overview will be provided of the developmental assessment
measures utilized with infants and young children in South Africa, followed by a description
of selected international developmental measures that have been adapted for use in South
Africa. As the GMDS-ER is the assessment measure employed within the current study, it
will be discussed in detail and the focus will shift to the history of the Scales, including a
description of the Subscales, the scoring and administration procedure and its reliability and
validity as a diagnostic measure. A brief discussion on the need for South African research on
the GMDS-ER will be provided, concluded by clinical and technical research studies
conducted on the GMDS-ER to date.
4.2
Child developmental assessment
Since the early 1970s, the need for the early identification of children with difficulties
has been recognised (Foxcroft & Roodt, 2001; 2006). Considering the South African history
and current context, further awareness needs to be created around the benefit of early
identification of developmental problems. In South Africa’s diverse background, there are
many children who do not have access to adequate resources and learning opportunities and
thus fall within the disadvantaged bracket. Without some form of assessment, these children
62
may go unnoticed and their developmental difficulties only be detected later when they fail to
master the developmental milestones. It may prove more challenging to intervene in the older
child’s life and sadly the window of opportunity may be missed. Thus, “the rationale for
assessing a child’s development at an early age is simple: the sooner a child’s difficulties can
be identified, the sooner an intervention can be implemented and, hence, the sooner a child
can be assisted” (Luiz & Jansen, 2001, p.155).
The benefits of identifying problems early is that intervention can be implemented
which will assist the child to catch up developmentally and cope successfully as opposed to
those who are identified much later (Foxcroft & Roodt, 2001; 2006). Knoesen (2003) asserts
that the early identification of the child’s areas of developmental weaknesses will enable the
practitioner to provide remedial intervention to maximally develop those areas of
developmental delay. Van Rooyen (2005) further highlighted the need for developmental
assessment within the South African context, and explained that due to the substantial number
of at risk children in South Africa, there is a great need for intervention programmes that
focus on the improvement of the development of vulnerable children. Luiz and Jansen (2001)
provide the example of how detecting a cognitive developmental delay early in a child,
having an accompanying lack of social and emotional stimulation, can lead to a certain
amount of remediation. They assert that if this cognitive delay is detected at an early enough
age and the child provided with intensive stimulation, the cognitive deficit may disappear to a
certain extent after a period of time. Therefore, it can be said that early childhood intervention
can also serve as a measure of hope. It can assist in remedying deficits that exist due to
unequal opportunities in education for instance.
Therefore, the goal of early childhood assessment within the South African context
should be to “acquire information and understanding that will facilitate the child’s
development and functional abilities within the family and community” (Shonkoff & Meisels,
2000, p.232). Greenspan and Meisels (1996) define developmental assessment as: “a process
designed to deepen understanding of a child’s competencies and resources and of the
caregiving and learning environments most likely to help a child make fullest use of his or her
developmental potential” (p.11). The holistic view of child development was emphasized in
the previous chapter, and by implication a holistic perspective to the developmental
assessment of South African children is vital in view of the poor social conditions the
majority of South African children have experienced (Luiz, 1994).
Brooks-Gunn (1990) stressed that the measurement of the well-being of a child should
include the assessment of the physical, cognitive, social, and emotional developmental arenas.
63
Therefore, a comprehensive developmental assessment should include these four aspects of
functioning, which are not mutually exclusive, meaning that a problem in one area may have
an effect on another area (Luiz & Jansen, 2001). If one accepts the definition of child wellbeing offered by Brooks-Gunn as the goal we wish South African children to attain, by
implication a comprehensive measure of development is required (Davidson, 2008). Luiz
(1994) asserts that the Griffiths Scales play a “pivotal role in this process” (p.9).
Developmental measures can be categorized as either screening or diagnostic
measures (Foxcroft & Roodt, 2001; 2006). Developmental screening involves a brief, formal
evaluation of developmental skills, which attempts to identify children who may be
potentially at risk for developmental difficulties (Squires, Nickel & Eisert, 1996). Nonspecialists, such as parents, educators and clinic nurses, can administer screening measures as
long as they have been trained to use them (Luiz & Jansen, 2001). In comparison to screening
measures, diagnostic measures can be described as “in-depth, comprehensive, individual
holistic measures used by trained professionals and the aim of diagnostic measures is to
identify the existence, nature, and severity of the problem” (Luiz & Jansen, 2001, p.155).
Both screening and diagnostic measures assess a child holistically, in which they examine
areas such as fine and gross motor co-ordination, memory of visual sequences, verbal
expression, language comprehension, social-emotional status and so forth. Screening
measures usually provide an overall view of the child’s development, rather than information
relating to specific areas. Diagnostic measures are more comprehensive in that they provide
numerical scores and/or age equivalents for both overall performance as well as for each
specific area assessed (Luiz & Jansen, 2001).
4.3
Child developmental assessment within a multi-cultural context
The family may be the most important context for the child, but the culture and
community provide the contexts for the family. Families are cultural mediators, and if we are
to understand the child, we need to understand the sources of influence. Furthermore, if we
are to offer services to the child and family, we need to be sensitive to these factors (Meller,
Ohr & Marcus, 2001; Mosley-Howard, 1995; Okagaki & Diamond, 2000; Roopnarine &
Carter, 1992). Culture is a complex construct that is often intertwined with the concepts of
ethnicity and race. Betancourt and Lop´ez (1993) regard culture as a distinct system of
meaning or a cognitive schema that is shared by a group of people or an identifiable segment
of the population. Culture has been defined as “historically transmitted patterns of meaning”
(Mosley-Howard, 2005, p.337). In contrast, ethnicity is typically used to describe a group
64
defined by a common nationality, culture or language. Therefore, ethnicity refers to a broad
grouping to which members have a subjective sense of belonging (Garcia Coll & Magnuson,
2000). In more recent conceptual models of development, socio-cultural influences on infant
and child development have increasingly been proposed (Garcia Coll & Magnuson, 2000).
“This shift has been driven by a compelling combination of scholarly and clinical
contributions that have indicated that universal assumptions about development do not
equally explain all processes and pathways of development for all populations” (Garcia Coll
& Magnuson, 2000, p.94). It has consistently been found that an individual’s cultural group
has an influence on test performance (Allan, 1992; Heimes, 1983; Mothuloe, 1990; Tukulu,
1996). Foxcroft and Roodt (2001) assert that “although there may be cultural differences in
test scores, there is no decisive evidence that culture influences competence rather than
performance” (p.328). In other words, although “socio-cultural factors may affect
manifestations of underlying cognitive and emotional processes, it is unlikely that cultural
differences exist in the basic component cognitive processes” (Miller, 2001, p.328).
Mwamwenda (1995) stated that empirical studies have shown that the pattern and sequence of
acquisition of Piagetian stages of cognitive development is universal, however the rate of
acquisition may vary among different cultures. Therefore, it is imperative that cultural
differences are taken into account when test performance is interpreted (Foxcroft & Roodt,
2001; 2006).
According to Jansen (1991) there is no such thing as a ‘culture-free’ test as
psychological tests are samples of behaviour, which are affected by the cultural milieu in
which the individual is reared. Thus, a more realistic approach to developing a culture-free
test is to develop a test with content that is based on experiences which are common across
cultures and thus proves to be ‘culture-fair’ (Baker, 2005). The concept of play, whilst
perhaps in different forms across cultures, is a universal behaviour, and the Griffiths Scales
were developed by observing children in their natural environments, and whilst engaged in
natural activities (Allan, Luiz & Foxcroft, 1992). Furthermore, several studies conducted
within different parts of the world have demonstrated the Griffiths Scales applicability to
diverse population groups as they tap into experiences that are common to different cultures
(Luiz, Collier, Stewart, Barnard & Kotras, 2000). In addition, research conducted on the
Griffiths Scales have demonstrated that they can be applied in the evaluation and treatment of
children from a variety of cultures and from first as well as third world countries (Allan,
1988; Bhamjee, 1991; Mothuloe, 1990). Luiz (1994) confirmed that the Griffiths Scales could
be considered to be ‘culture-fair’ as they utilize experiences that are common to different
65
cultures, an attribute which is obviously very significant within the South African context.
Another positive reason for using the Griffiths Scales in a multi-cultural context is that the
tester demonstrates a number of the items, making the test process more understandable to
children with limited experience with psychometric assessment. Furthermore, the language
component of the Griffiths Scales is smaller than that of some other psychometric measures,
thus enabling the tester to assess aspects of a child’s development without having to rely on
proficient verbal skills (Baker, 2005). The Griffiths Scales of Mental Development is one of
the few measures that can be used across various South African populations with confidence
(Bhamjee, 1991; Baker, 2005; Knoesen, 2003; Kotras, 2001; Schröder, 2004; Van Heerden,
2007). The Association for Research in Infant and Child Development (ARICD) based in the
United Kingdom, London, is highly supportive of projects in third world countries such as
Asia and South Africa, which aim to increase Griffiths research in these continents. Such
research aims to facilitate the development of a set of norms specifically applicable to
developing populations such as those found in these abovementioned countries (L. Stroud,
personal communication, December 3, 2007). In conclusion, Luiz (2000) highlighted the
following as needing to be addressed and focused on when considering developmental
assessment within a multi-cultural South African context:
1. The absolute need for holistic developments;
2. Screening measures that are culture-reduced, valid and reliable from our diverse
South African population;
3. The value and necessity for para-professionals and parents to increase their
knowledge about normal developmental milestones and to form part of the
screening process; and
4. The importance of establishing a community network system to facilitate
communication, referrals and the sharing of knowledge amongst the various
professionals, lay-professionals, parents and caregivers who are involved in the
lives of South African infants and children.
4.4
Psychological assessment measures utilized with infants and young children in
South Africa
In review of the state of the developmental measures in South Africa, Foxcroft and
Roodt (2001; 2006) have found that during the last decade, there has been a concerted effort
made by researchers to attend to the need for more reliable and valid developmental measures
66
for use with South African children. Researchers have focused on the construction of new
culture-reduced tests and adapting, revising and norming assessment measures that have been
extensively used in other countries and thus proved to be reliable and valid (Foxcroft &
Roodt, 2001; 2006). A brief description of developmental measures used in South Africa will
be presented, followed by a description of selected international developmental measures that
have been adapted for use in South Africa.
4.5
4.5.1
Developmental assessment measures utilized in South Africa
The Junior South African Individual Scales (JSAIS)
The Junior South African Individual Scales (JSAIS) were developed in 1979 and
initially designed for use with White South African children between the ages of 3 and 7 years
11 months (Madge, 1981). There are two main aims of this assessment battery, namely 1) to
establish a child’s general intellectual level, and 2) to evaluate a child’s functional strengths
and weaknesses (Madge, 1981). Van Rooyen (2005) described the JSAIS, as a comprehensive
measure that provides a profile of abilities, yet does not assess gross motor and personalsocial development. It is interesting that the JSAIS was adapted and standardised for Asian
children, and norms established for Coloured Children between the age group of 6 years to 8
years and 11 months (Robinson, 1989; Swart, 1987). Furthermore, the measure was further
standardised for English and Afrikaans-speaking children who have received formal
schooling in these languages (Van Rooyen, 2005). However, this assessment measure has not
been normed for black children, and Van den Berg (1987) has stated that this can only be
achieved once parallel forms of the test have been developed for the South African black
language groups. In view of the need for a holistic view of development to be adopted within
the South African context and advanced to our developmental measures, it can be said that the
major limitation of the JSAIS is its inability to be used in our diverse population. Further
criticisms include its limited focus on the different domains of development as envisaged by
Griffiths’ learning avenues, and its ignorance of contextual factors in the assessment of
children.
4.5.2
Grover-Counter Scale of Cognitive Development
The Grover-Counter Scale was based on Piagetian theory and developed in
accordance with Piaget’s stages of cognitive development. It measures five domains, with
each domain measuring a stage in a person’s development, called Sections. Section A consists
67
of simple recognition of shapes and colours, Section B evaluates the ability to reconstruct
patterns from memory, Section C evaluates the ability to copy a model made by the tester,
Section D evaluates the ability to reconstruct a model from memory, and Section E evaluates
the ability to produce and complete patterns from a design card within a time limit (Luiz &
Jansen, 2001). Each section provides an indication of the child’s stage of current
development, based on factors that look at procedural elements of how the child goes about
performing the tasks (Luiz & Jansen, 2001). Therefore, it is rather apparent that there are
several similarities between the items found on the Griffiths Scales and the Grover-Counter
Scale. Dickman (1994) has found that there is a growing body of research developing on the
Scale that has proved its clinical use in South Africa.
4.5.3
Educationally-focused developmental screening measures
Due to South Africa’s socio-political history and rich diversity of people, it is
important that attempts are made to instil equality in every sphere. Formal schooling equips
children with the vital tools of learning to further their thinking and hands them the key with
which they can open new doors to success for not only themselves but for their community.
Therefore, the attempt to instil equality should start with ensuring that all children have access
to proper education. In this regard, “educationally focused screening measures assess the
extent to which young children are developing the necessary underpinning skills that are the
essential building blocks for being able to successfully progress in the early school years”
(Luiz & Jansen, 2001, p.158). Such assessments are vitally important in detecting any early
developmental difficulties in children so that they can be rectified and thus allow the children
to develop to their full potential. The following assessment measures have been developed in
South Africa and assess “whether a pre-school child or Grade One child is at risk for
developing scholastic difficulties” (Luiz & Jansen, 2001, p.158).
4.5.3.1
School-readiness Evaluation by Trained Testers (SETT)
The SETT was developed in 1984, and measures whether a child is ready for school or
not. It is administered by setting up a learning station, similar to a classroom. The SETT
evaluates a child’s development in the following areas, namely: language, general or
intellectual development, physical and motor development, and emotional and social
development (Luiz & Jansen, 2001). According to Knoesen (2003), the SETT was developed
for use with urban White, Coloured and Asian children. No black children were included in
the normative sample. An investigation into the predictive validity of the SETT for White,
68
Coloured and Asian children was conducted by Bender (1990) and in analysis of the results,
found that the SETT is able to predict the primary school progress of these population groups.
4.5.3.2
School-entry Group Screening Measure (SGSM)
The SGSM is a non-verbal cognitive group-screening measure developed in South
Africa for five- to nine-year-old children (Foxcroft, Shillington & Turk, 1990). It measures
the cognitive abilities of simultaneous visual-motor functioning, visual sequential processing,
cognitive flexibility, attention, and incidental memory (Luiz & Jansen, 2001). These abilities
are comprised within four separate subtests, namely Visual-motor, Reasoning, Incidental
Memory and Visual-spatial. According to Luiz and Jansen (2001) the SGSM has been found
to predict accurately if a child is at risk for later scholastic difficulties. In addition, test
instructions are available in several South African languages, namely English, Afrikaans,
Xhosa, Zulu, and Southern Sotho (Luiz & Jansen, 2001). Knoesen (2003) noted that an
advantage of the SGSM is its time efficiency, as well as that psychologists, psychometrists
and teachers trained on the SGSM can administer the test. Furthermore, Knoesen (2003)
highlighted the fact that as the SGSM is a screening measure, it is best to categorize
performance in terms of qualitative, descriptive categories as opposed to quantitative norms,
such as stanines or scaled scores. Cut-points have also been developed for each cultural
group.
4.5.3.3
Aptitude Test for School Beginners (ASB)
The ASB was published in 1974 and was the first standardised test for Black,
Coloured and White South African children. It is also the only test that has been standardised
for black school beginners (Knoesen, 2003; Ras, 1987). The aim of the ASB is to obtain a
comprehensive picture of particular aptitudes of the school beginner and evaluates the
cognitive aspects of school readiness. The ASB consists of eight subtests: Perception, Spatial,
Comprehension, Numerical, Gestalt, Co-ordination, Memory, and Verbal Comprehension.
The instructions are available in the seven most commonly spoken African languages (Luiz &
Jansen, 2001). The ASB is not without its criticisms, some of which are that it excludes gross
motor and personal-social development, the cumbersome administration of the test and
lengthiness of completion time, difficult scoring procedures for some of the subtests, the
paper-and-pencil requirement when many children have limited experience with such
mediums at school-entry level, and lastly that children battle to understand and follow the
instructions independently (Knoesen, 2003). However, Hoar (1983) and Mothuloe (1990)
69
have found significant positive correlations with the ASB scores and Grade One school
results, indicating that it could be a useful screening measure for Black school beginners
(Knoesen, 2003).
4.6
International developmental assessment measures adapted for use in South
Africa
As mentioned earlier, South African researchers identified the need to adapt, refine
and norm appropriate tests that have been constructed and proven valid and reliable in other
countries for use in the South Africa context. However, this would need to be undertaken in a
cost-efficient way due to the financial challenges that face a third world country such as South
Africa. Therefore, through adapting assessment measures such as the Bayley Scales of Infant
Development II, the McCarthy Scales of Children’s Abilities, the Wechsler Scales and the
GMDS-ER, diagnostic developmental measures have become more accessible to the South
African context. These measures will be described briefly below, however it must be
emphasized that these measures are not the only measures in use.
4.6.1
The Wecshler Scales
The Wechlser Intelligence Scale for Children was developed in 1949 and was replaced
by a standardised version known as the Wechsler Intelligence Scale for Children-Revised
(WICS-R) in 1974 (Wechsler, 1974). The WISC-R assesses the cognitive and intellectual
abilities in children aged 6 to 16 years old. According to Anastasi (1982), whilst the WISC-R
is said to be technically superior in terms of its construction processes, reliability and validity
studies have been insufficient and inconclusive. The WISC-R was updated to the Wechsler
Intelligence Scale for Children-III (WISC-III) in 1991, and extends across the same age range
as the WISC-R (Strauss et al., 2006). The WISC-III enabled the comparison of verbal and
non-verbal ability, and the revision process intended to improve the “contemporaneous nature
of the norms as well as updating the content coverage” (Baker, 2005, p.66). However,
Edelman (1996) found that whilst the WISC-III may have acceptable internal consistency
reliability co-efficients, there is a significant practice effect on the Performance scale if a
retest is completed within a 12-63 day interval. Thus, the WISC-III was not a suitable test for
testing developmental changes if a retest is to be done within two months after the initial
testing (Van Rooyen, 2005). The WISC-III was updated to the Wechsler Intelligence Scale
for Children-Fourth Edition (WISC-IV) in 2003. The WISC-IV embodies a fundamental shift
from previous editions, as the test’s theoretical underpinnings now reflect more updated factor
70
analytic theories of intelligence collectively termed Carroll-Horn-Cattel (CHC) theory, which
has been termed one of the most important theories in contemporary intelligence research
(Strauss et al., 2006).
The CHC theory is a model that stresses broad classes of abilities at the higher level
(fluid ability, crystallized intelligence, short-term memory, long-term storage and
retrieval, processing speed), and a number of primary factors at the lower level
(quantitative reasoning, spelling ability, free recall, simple reaction time) (p.98).
Their thinking reflects modern day contemporary theories of the structure of cognitive
functioning that emphasize multiple, somewhat independent factors of intelligence, and thus
believe that it is best evaluated with multifaceted instruments and techniques (Strauss et al.,
2006). Whilst the WISC-IV has dominated the international field and is used by so many
psychologists, the adoption of this model represents a major historical paradigm shift for the
assessment of intelligence in children. However, the WISC-IV has been criticised by
Wechsler traditionalists and by the CHC proponents for not providing coverage of all CHC
domains and for an a posteriori adherence to the model (Flanagan & Kaufman, 2004). The
Wechsler Pre-school and Primary Scale of Intelligence-Revised (WPPSI-R) was constructed
as an extension of the WISC in 1989, and was designed for children in the three to seven year
age group. The twelve subtests are grouped into a verbal and performance scale, and whilst it
is has been regarded as easy to administer it has also been heavily criticised for its inability to
estimate the IQ of severely retarded children, as well as ethnic minority children from low
socio-economic backgrounds (Groth-Marant, 1984). Further criticisms focused on the
WPPSI-Rs limited range of measured abilities, low reliability of some subtests, limited floors
and ceilings, long administration time, complex scoring criteria for some subtests and for
overemphasizing speed which put some children at a disadvantage (Strauss et al., 2006).
The Wechsler Pre-school and Primary Scale of Intelligence-III (WPPSI-III) was
released in 2002, and it improved on the abovementioned limitations, as well as being more
consistent with current factor-analytic theories of intelligence and cognitive functioning such
as CHC theory. The age range was extended down from 2 years 11 months to 2 years 6
months and there are now two distinct age groups, namely 1) 2 years 6 months to 3 years 11
months, 2) 4 years 0 months to 7 years 3 months. The two age groups differ in their score
structure, administration time, item difficulty, and reliance on verbal expression (Strauss et
al., 2006).
While none of the Wechsler Scales for children have been fully adapted for the South
African context, they are widely used. Some preliminary studies have been conducted with
71
respect to translating some of the subtests and to establish preliminary local norms. For
example, Horsmann (2007) investigated the effects of the quality of education on the WISCIV Coding B-Incidental Learning subtest for a sample of Xhosa and English-speaking Grade
7 learners aged between 12 and 13 years in the Eastern Cape. As one of the outcomes of this
study, normative guidelines were developed that can be used in clinical practice. Furthermore,
Van Tonder (2007) provided preliminary normative information in terms of means and
standard deviations for all the subtests, the four indices, and Full Scale IQ of the WISC-IV for
English and Xhosa-speaking children in Grade 7 aged between 12 and 13 years in the Eastern
Cape.
4.6.2
McCarthy Scales of Children’s Abilities (McCarthy Scales)
The McCarthy Scales were published in 1972, and are utilized with children between
the ages of 3 years 6 months and 8 years 6 months. The tasks are designed to be suitable for
both boys and girls, as well as for children from different cultural and socio-economic groups
(Luiz & Jansen, 2001). There are eighteen separate tests, grouped into five scales, namely: 1)
verbal, 2) perceptual performance, 3) quantitative, 4) motor, and 5) memory (Luiz & Jansen,
2001). An overall measure of the child’s intellectual functioning is obtained when the Verbal,
Quantitative, and Perceptual Performance Scales are combined (Luiz & Jansen, 2001). The
general cognitive score is expressed as a General Cognitive Index (GCI) and indicates the
child’s functioning at the time of testing, with no implications of immutability or etiology.
Furthermore, Bhamjee states that the GCI is reported to come the closest to the traditional
global measure of intellectual development, IQ (Bhamjee, 1991). Luiz and Jansen (2001)
have highlighted the fact that the McCarthy Scales have normative information available for
various groups of South African children.
4.6.3
Bayley Scales of Infant Development-Second Edition (BSID-II)
The BSID-II is used to identify children between the ages of 1- to 42-months (3 years
5 months) with developmental delays or those suspected of being ‘at risk’ (Luiz & Jansen,
2001). The original Bayley Scales were published in 1969, a second edition was published in
1993, and a new edition is forthcoming, the BSID-III (Strauss et al., 2006). Items from the
Bayley Scales have as origins some of the earliest tests of infant development (Bayley, 1936).
The BSID-II is designed to assess cognitive, physical, language, and psychosocial
development of infants, toddlers and pre-schoolers (Bayley, 1993). Norms published in 1969
on the original Bayley Scales are available for interpreting the performance of black South
72
African children (Richter & Griesel, 1988). However, no other South African norms are
available for the revised scales. In accordance, Barnard (2000) has recommended that further
studies should be undertaken to investigate the BSID-II’s suitability with special populations.
4.6.4
Griffiths Scales of Mental Development (GMSD)
The original Griffiths Scales of Mental Development covered the first two years of life
and was first published in 1954. It assessed areas of development, such as Locomotor,
Personal-Social, Hearing and Speech, Eye and Hand Co-ordination, and Performance. The
Griffiths Extended Scales of Mental Development were initially developed in the 1960s as an
extension to the original Scales and tested children aged two to eight years. A sixth subscale,
Practical Reasoning, was introduced with the Extended Scales (Griffiths, 1970; 1984).
Recently, the Extended Griffiths Scales have been revised to further update the items. As the
focus of the present study is on the Griffiths Mental Development Scales-Extended Revised
(GMDS-ER), it will be discussed in greater depth in the following section.
4.7
Griffiths Mental Development Scales-Extended Revised (GMDS-ER)
Dr. Ruth Griffiths is regarded as one of the most influential developmental
psychologists for her remarkable contributions to the area of developmental assessment. Dr.
Griffiths emphasized that in order to work with children one needs to understand them and
that one of the keys needed to unlock that process is that of observation.
One cannot stress too often the significance of careful and detailed observation of
children if we are to understand them, perceive their thoughts or interpret their
behaviour. There is in fact scarcely any limit in this field of work, to what can be
learned by the observation of children, at play, at home, on the street, in trains or
buses, and in their own homes and gardens (Griffiths, 1954, p.7).
Using observation of children in their natural settings, the Griffiths Scales were
developed as an instrument to assess early childhood development (Griffiths, 1984). Griffiths
understood that the best indication of a child’s development is to include as many facets as
possible that will predict their development in later years. As illustrated in the previous
chapter, Griffiths’ basic avenues of learning formed the foundation of the original Griffiths
Scales and it is of no doubt that in the revision and extension process, these avenues guided its
further development. It has been said that Griffiths’ thinking around child development was
somewhat before her time. This can be safely assumed as her basic avenues of learning,
73
which were published in 1954, are in line with modern systems theory, which was developed
over a decade later.
4.7.1
The development of the GMDS-ER: A historical journey
The inventor of the Griffiths Scales, Dr. Ruth Griffiths, is bestowed the title of the
“architect of the most carefully constructed infant scales for her development of the Griffiths
Scales” (Luiz, 1994, p.5) Griffiths recognized that no sector of the community is more
deserving of the time and expertise of professionals than infants, children and adolescents
(Luiz et al., 2006a). Griffiths had been devoted to her sister who died of polio at the age of
five years in 1914 soon after the family’s emigration to Australia. According to Burne (cofounder and trustee of the ARICD), Griffiths was determined to use her talents and skills to
celebrate the memory of her sister, and her own life (Luiz et al., 2006a). Therefore, in 1954
Griffiths published the Griffiths Scales of Mental Development for British infants in the birth
to two years age group, and introduced a new diagnostic technique for studying the
development of babies. She also wrote a book in 1954 entitled The Abilities of Babies in
which her philosophy of learning avenues within child development became known. The
Griffiths Scales assessed development in five areas, namely Locomotor, Personal-Social,
Hearing and Speech, Eye and Hand Co-ordination and Performance (Luiz et al., 2006a). The
construction of the Griffiths Scales arose out of an identified need for the early identification
and diagnosis of mental conditions in children (Griffiths, 1954; 1984). The Scales were
compiled after an extensive study of development and were then standardised on 571 British
babies (Stewart, 2005). The implications of having a measure that assisted with the clinical
diagnosis of normal and handicapped children received wide acclaim from practitioners out of
numerous disciplines (Griffiths, 1970; 1984). Griffiths gained inspiration from the extensive
writings of Professor Arnold Gesell on babies and young children, as well as from the work of
Professor L.M. Terman and Professor Maud Merrill for their revisions of the Binet-Simon
tests (Griffiths, 1970). Dr. Ruth Griffiths, Dr. Rose Unmack and Dr. Brian Henry Burne
founded the Association for Research in Infant and Child Development (ARICD) in 1957. It
supported and advised Ruth Griffiths until she died in December 1973 (Luiz et al., 2006b).
Griffiths received many requests for the extension of the infant scales for use in clinical
practice with older children. Therefore, the Extended Griffiths Scales were developed in the
1960s and described in her book entitled The Abilities of Young Children (Griffiths, 1970).
The Scales were expanded to cover from birth to eight years (Griffiths, 1970) and a sixth
subscale, Practical Reasoning, was added to the Extended Griffiths Scales for children aged
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two years and older. The Practical Reasoning subscale was aimed at providing a more
comprehensive coverage of the young child’s emerging problem-solving and logical
reasoning skills (Luiz et al., 2006a). According to Griffiths (1970; 1984; Luiz et al., 2006a),
the Scales were developed according to five stringent criteria:
1. The development of the Scales was based on detailed systematic observation of
children in their natural environments and their behaviour was recorded. These
observations formed the basis of the material for the test items.
2. Previous and existing test methods and tests were taken into account and items from
significant tests were included in the Griffiths Scales.
3. The Scales had to fulfil stringent statistical requirements of reliability and validity.
4. The Scales took into account the requirements of both special needs and normally
developing children.
5. The Scales were based on a study of:
(i)
trends that appeared significant for mental growth; and
(ii)
the interrelations between the basic avenues of learning (such as
physiological/locomotor, eye/hand, voice/hearing) which develop with
rhythm in time and space and are influenced also by environmental and
social factors.
Griffiths not only extended the Infant Scales in the 1960s to expand its coverage to
eight-year-olds, but also revised and restandardized the original Infant Scales (Van Heerden,
2007). The items on the Extended Scales are diverse and tap into the main aspects of a child’s
development. In addition, they are norm-referenced and the items of each subscale are placed
in order of gradually increasing difficulty (Luiz et al., 2006a; Van Heerden, 2007). In line
with the first criteria mentioned above, the items are based on natural activities such as
walking, talking and playing and as Kagan (1981) has stated, play is a universal activity that
emerges at the same age in all children and is found within all cultures. Furthermore, each of
the six subscales of the Scales was devised to be a separate and complete scale in itself
(Griffiths, 1970). This means that any one process of development can be measured
independently and as completely as possible. Although the majority of initial research took
place in Great Britain, research was further conducted in Canada, Columbia, France,
Germany, and China and more recently in Australia, Greece, Lebanon, the United States of
America and South Africa. Such research on the Scales has shown that they have practical
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and diverse applications in the evaluation and treatment of infants and young children from a
variety of cultural backgrounds (Brandt, 1983; 1984; Cobos et al., 1971; Collins et al., 1987;
Laroche et al., 1974; 1976; Luiz et al., 1999; 2001; 2003; Ramsay & Fitzharding, 1977;
Sletten, 1970; 1977). Furthermore, Luiz (1994) confirms that the Griffiths Scales could be
considered to be ‘culture-fair’. In other words, the Scales utilize experiences that are common
to different cultures, an attribute which is obviously very significant within the South African
context.
The Scales are widely used by professionals as a developmental assessment tool in
countries including the United Kingdom, Eire, Portugal, Australia, Hong Kong, South Africa
and the United States of America and have been used in a wide array of research. In an
international survey conducted with over 100 tutors and registered users of the Scales, it was
found that the Extended Griffiths Scales are most frequently used with problems such as
general developmental delay, environmental deprivation, and specific child developmental
problems, such as delayed speech, clumsiness, poor eye-hand co-ordination and Down’s
syndrome (Luiz et al., 1995; 2006a). According to Luiz et al. (2006a) such findings indicate
that the test is sensitive enough to provide practitioners with valuable diagnostic information
on a range of developmental disorders.
Dr. Ruth Hanson first introduced South Africa to the Griffiths Scales in 1977 and Dr.
Brian Burne fostered further interest in this developmental measure in 1989 when he visited
South Africa (Davidson, 2008). Therefore, to make it user friendly within the South African
context, translations and adaptations had to be made to suit our diverse population. The test
was originally developed in English and translated into Afrikaans by Allan in 1988. The
translation of test instructions and verbal items into Xhosa has subsequently been undertaken
by means of the back-translation technique (Allan et al., 1992; Luiz, 1994; Tukulu, 1996).
While, there is an extensive amount of support for the Griffiths Scales, several comprehensive
reviews in the 1980s and 1990s identified areas in which they could be improved (Allan,
1988; 1992; Bhamjee, 1991; Hanson, 1982; 1983; Hanson & Aldridge Smith, 1982; 1987;
Hanson et al., 1985; Luiz et al., 1995). These studies found that various items of the Scales
were outdated and several items were culturally biased and ambiguous (Kotras, 2003).
Therefore, the original Griffiths Scales were no longer providing the examiner with reliable
and valid results on current evaluations of the child. This provided the rationale for the
revision of the Scales. The revision began with the Scales from Birth to Two Years and, in
March 1994, the ARICD introduced a draft version of the Revised Baby Scales from Birth to
Two Years, which was published in 1996 (Huntley, 1996). Also, at the ARICD conference
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(1994), the need to revise and standardise the Extended Scales from Two to Eight Years was
emphasized and a working team was recruited. The late Professor D.M Luiz of the University
of Port Elizabeth was appointed by the ARICD to lead this team aiming to revise and re-norm
the extended scales in the British Isles and Eire (Davidson, 2008; Van Heerden, 2007).
According to Luiz et al. (2006b) the aims of the revision process was seven-fold:
1. To update the norms;
2. To improve scoring standards, making them explicit and less open to subjective
interpretation;
3. To include additional new items to assess previously untapped areas of development,
to improve the content coverage, and to also strengthen the reliability of the subscales
and scale as a whole;
4. To remove items that are not adding any value to the subscales and the scale as a
whole;
5. To improve administration instructions (including the provision of practice examples
for selected items);
6. To improve the visual and aesthetic properties of the test material;
7. To replace outdated training aids.
The revision and standardisation process of the Extended Griffiths Scales proceeded
over a ten-year period and the GMDS-ER was launched and published in 2004 and again in
2006 (Luiz et al., 2004a; 2004b; 2006a). It is vitally important that the norms of the GMDSER are revised and regularly updated. If this is not done, as with the real phenomenon of IQscore inflation over time, the average GQ will gradually drift upward and give a progressively
deceptive picture of a child’s performance (Luiz et al., 2006b).
4.7.2 Description of the GMDS-ER Subscales
The GMDS-ER consists of the five subscales used in the Birth to Two Years Scales,
namely Locomotor, Personal-Social, Hearing and Language, Eye and Hand Co-ordination and
Performance. When the Scales were expanded to cover the ages from birth to eight years six
months, a sixth subscale was added to the Extended Griffiths Scales for children aged two
years and older. While in the Birth to Two years Scale, Subscale C is known as the Hearing
and Language Subscale, it is known as the Language Subscale in the GMDS-ER as no hearing
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items are included (Luiz et al., 2006a). Each of the individual subscales which together form
the GMDS-ER is briefly described below.
4.7.2.1 Subscale A: Locomotor
This subscale allows the examiner to assess the child’s gross motor skills including his
or her ability to balance and to co-ordinate and control movements (Luiz et al., 2006a). This
subscale enables the examiner to observe physical weakness or disabilities or more definite
gross motor defects in young children. The items administered include age-appropriate
activities such as walking up and down stairs, kicking a ball, jumping, and skipping, kneeling
on the floor, and so on (Stewart, 2005). According to Sweeney (1994), this subscale was
placed first to provide a basis for objective assessment, to set the child at ease and to gain an
initial impression of the child’s overall maturity. Furthermore, “performance is also
influenced by the child’s ability to focus and concentrate on the task at hand, and the
emotional determination to succeed” (Stewart, 2005, p.9).
4.7.2.2 Subscale B: Personal-Social
This subscale assesses the child’s proficiency in the activities of daily living, his level
of independence and his ability to interact with other children (Luiz et al., 2006a). A degree of
self-help, appropriate to the child’s age, is required in terms of personal cleanliness, efficiency
at the table, and so forth. There is an expectation for some degree of social interaction from
the child, as well as in their co-operation in play with their peers (Stewart, 2005). For
instance, the examiner obtains information about the child’s name, age, home address, family
name and so on, by interacting with the child and in as natural a manner as possible. This
means that the items on this particular subscale can be scored without the child even detecting
that it forms part of the assessment (Stewart, 2005). According to Kotras (2001), whilst
emotional factors will affect performance across all the subscales, it exerts a particular
influence on the Personal-Social subscale. It is interesting to note that Griffiths (1984) has
found that children who are neglected or overly protected usually perform poorly on this
subscale in comparison to the other subscales. The reason for this is that apparently over
protected children are usually slower in learning self-help and personal care (Griffiths, 1984).
4.7.2.3 Subscale C: Language
This subscale allows the examiner to assess the child’s receptive and expressive
language. The items administered include age-appropriate items such as naming colours and
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objects, describing a picture, repeating a sentence, analysis of spontaneous sentence
structures, and answering comprehension questions such as ‘What should you do if are tired?’
and questions about the differences and similarities between objects (Luiz et al., 2006a).
According to Griffiths (1984, p.45), “this is the most intellectual of the scales”. However, it
should be noted that poor performance on this particular subscale does not reflect impaired
intellectual functioning, Kotras (1998) stated that poor performance could be the result of
complete or partial hearing loss, a result of mixed language families or even a lack of verbal
stimulation. In agreement with Kotras, Stewart (2005) noted that poor performance could be a
“manifestation of some degree of deafness or hearing impairment” (p.10).
4.7.2.4 Subscale D: Eye and Hand Co-ordination
This subscale assesses the child’s fine-motor skills, manual dexterity and visual
monitoring skills (Luiz et al., 2006a). The items administered include age-appropriate items
such as cutting with scissors, copying shapes and writing letters and numbers. Co-ordination,
careful work and persistence at a task are also measured (Davidson, 2008). The child’s
drawings of geometric shapes provide information on his or her conception of space and
form, in addition information about the child’s personality can be gauged from the drawings
as reflected by the use of projective techniques for such purposes like the Draw-A-Person
(Harris, 1963; Kotras, 1998; Stewart, 2005).
4.7.2.5 Subscale E: Performance Subscale
This subscale allows the examiner to assess the child’s visuo-spatial skills including
speed of working and precision (Luiz et al., 2006a). The items administered include ageappropriate activities such as building bridges, gates and stairs, completion of formboards and
pattern making. As its name implies, this particular subscale is largely one of performance
and requires that practical tasks are performed as well as that the child manipulate material
(Stewart, 2005). This subscale does complement Subscale D to a certain extent in that the
components of Subscale D, namely manual dexterity and eye-hand co-ordination are assumed
in the Performance Subscale. Thus, the child is expected to apply these skills in original
situations (Stewart, 2005).
4.7.2.6 Subscale F: Practical Reasoning
This subscale assesses the child’s ability to solve practical problems, his or her
understanding of basic mathematical concepts and questions about moral and sequential
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issues (Luiz et al., 2006a). The items administered include age-appropriate activities such as
counting and comparison of size, length and height and repetition of digits, recognition of
coins, picture arrangement cards and so on. It also examines the child’s visual sequential
skills, understanding of right or wrong as well as the child’s knowledge of the days of the
week. This subscale commences when the testee is three years of age, and attention and
concentration span have a major impact on this subscale in terms of the child’s performance
(Stewart, 2005). As Davidson (2008) noted that although the Scales were not originally
constructed to predict scholastic success, the results of this subscale do provide an indication
of the child’s ability to benefit from formal schooling. Therefore, it has often been included in
school readiness assessments to aid in a more comprehensive assessment of a child’s abilities.
According to Foxcroft and Roodt (2001; 2006), an age equivalent is obtained for each
subscale and by combining the subscales a comprehensive score called the General Quotient
(GQ) is obtained. In addition to producing a GQ, a mental age (in months) is generated per
subscale as well as an overall mental age (MA) that can be correlated with the child’s
chronological age to determine whether the child’s performance was above or below his
actual age. Sattler (1974) defined MA as the “degree of general mental ability possessed by
the average child of a chronological age corresponding to that expressed by the MA score”
(p.19). Jensen (1979) described MA as indicating a level of cognitive functioning,
achievement, cerebral development and readiness to learn. In addition, the Scales do not only
assess the general or overall development of the child but also specific areas of development
integrated by the basic avenues of learning (Kotras, 2001), which are known as
developmental quotients. An added value of the GMDS-ER is that using histograms based on
the developmental quotient of each scale enables a comparison to be made of the child’s
performance on the different scales. This developmental profile will then provide an
indication of the child’s range of abilities and relative disabilities and enable comparison of
these at different times (Foxcroft & Roodt, 2001; 2006).
4.7.3
Scoring and administration of the GMDS-ER
The GMDS-ER consists of a total of 228 items. The examiner administers the test
items in each subscale until the child obtains a basal and a ceiling score within the subscale. A
basal is calculated as the first of the six consecutive passed items, and a ceiling is calculated
as the first of six consecutive failed items. The child incurs no penalty for items failed below
the basal, and obtains no credit for items passed beyond the ceiling. For the ages 0 to 24
months, there are two items per month in each of the five relevant subscales, and each item
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completed correctly is credited with half a month. For years three to eight, there are six items
for each year in every subscale, plus two extra items for the eighth year. The subscale items
are graded in order of difficulty per age group (Luiz et al., 2006b; Stewart, 2005). The
examiner administers the test items, starting approximately four months below the child’s
chronological age (Bhamjee, 1991). For each subscale separately, the items passed, up to the
ceiling, are added and multiplied by two. The figures in each column are then summed to
produce the total raw score for each subscale. As there is no Practical Reasoning Subscale in
the first and second years, the examiner calculates the average mental age across the other
five subscales for each of the two years. Children who did not need to be administered items
from the Birth to Two Years Scales due to their basal being higher are credited with a score of
12 months for the first and second years respectively. The total raw score represents the sum
of the scores in all the sections under that subscale and reflects the child’s mental age (MA)
for that subscale. This study will report on each of the subscale total scores and on the
General Quotient (GQ). The GQ is obtained by taking the average of the scores for the six
subscales. The scores can also be converted to percentiles, standard scores and age
equivalents by using the appropriate table in Appendix B in the Analysis Manual (Luiz et al.,
2006b).
Any psychological measure must fulfil two standard requirements, namely reliability
and validity (Foxcroft & Roodt, 2001; 2006). Therefore, the GMDS-ER will be examined
with regards to its reliability and validity in the following two sections.
4.7.4
Reliability
Reliability can be defined as the accuracy, consistency and stability of test scores
across situations (Anastasi, 1961). It refers to the consistency of test scores over time, or the
extent to which one is confident that a measure will produce the same result if measured again
(Murphy & Davidshoffer, 1991; Nuttall et al., 1992; Smit, 1996). There are two kinds of
reliability, namely internal and external. Internal reliability measures whether the test is
consistent within itself, and it is generally agreed by test constructors that internal consistency
should be high for a test to be of any practical use (Coolican, 2004). External reliability refers
to the stability of a measure across time. According to Kline (1993) internal consistency
coefficients are the most suitable test of reliability in instances where an individual’s score on
some attribute may change significantly in a short period of time. An appropriate example of
such an attribute is that of child development. In 1984, Griffiths used the test-retest method in
determining the reliability of the Griffiths Scales. Data generated from a sample of N = 270
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children from various regions within the United Kingdom was collected by Griffiths. The age
range of the children was between one to seven years old, and the interval between the
assessments ranged between 3 and 63 months. Griffiths found a test-retest reliability of 0.77
(Baker, 2005; Stewart, 2005). Honzik, McFarlane and Allan (1966) found reliability
coefficients between 0.71 and 0.76 for test-retest periods of 6 to 12 months for a sample of 3to 5-year old children. According to Barnard (2000), these studies indicated that the Griffiths
Scales are a stable measure of development.
Aldrige Smith, Bidder, Gardner and Gray (1980) measured the inter-rater reliability of
the Griffiths Scales. A video recording of eight normal children between the ages of six
months to seven years three months was rated and scored by a panel. An acceptable overall
reliability level of between 0.60 and 1.00 in 78% of the cases was found. Greater agreement
was obtained between all raters on the Eye-Hand Co-ordination Subscale (84%), the
Performance Subscale (91%), and Practical Reasoning Subscale (95%), than on the
Locomotor, Personal-Social and Hearing and Speech Subscales. It was hypothesized that the
latter three subscales may be more sensitive to interpretation and that the lower inter-rater
reliability obtained for these three subscales could be a result of the small sample size, few
scorers and that scoring was based on the mother’s report. Suggestions that arose in order to
improve their inter-rater reliability proposed more detailed instructions in the test manual for
Subscales A, B, and C (Stewart, 2005). However, Hanson (1982) was unable to replicate the
findings of Aldridge Smith et al. (1980), in her attempt to study the item reliability in terms of
inter-observer agreement and understandably she questioned the conclusions of their study
(Baker, 2005). In addition, scorers were asked to identify those items with ambiguous manual
instructions. This led to the finding of Hanson, Aldridge Smith and Humes (1984) that “when
the manual’s administration instructions and scoring criteria were ambiguous in respect of a
certain item, such an item was found to be unreliable” (Stewart, 2005, p.13). In review of test
construction issues, Clark and Watson (1995) recommended that the Scales strive for a
coefficient alpha of approximately 0.80, and maintained that this benchmark needs to be
established. They cautioned that an over concern with internal consistency can be counterproductive as it almost inevitably produces a scale which is narrow in construct (Stewart,
2005).
On the Extended Revised version of the Griffiths Scales, Cronbach’s alpha
coefficients were calculated for each subscale independently as well as for the GQ as an
indication of the reliability of the subscales as a measure of mental development (Van
Heerden, 2007). Luiz et al. (2006b) found that the overall reliability of the GMDS-ER is
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0.993, which is highly satisfactory. On the whole, the reliability of the individual subscales
ranges between 0.90 and 0.99 and thus is indicative of a high level of internal consistency
(Luiz et al., 2006b). As previously mentioned, Griffiths (1970) stated that “each subscale was
devised to be a separate and complete scale in itself, each measuring only one avenue of
development or process of development, but measuring this one aspect as completely as
possible” (p.34). In light of this, it is reasonable to expect that low intercorrelations between
some, seemingly unrelated, subscales will exist as the GMDS-ER is comprised of six separate
subscales which are all “vastly different in content” (Griffiths, 1970, p.34) rather than one
global scale. Several recent studies have been conducted on exploring the reliability of the
GMDS-ER and this will be described later in the technical studies section. The validity of the
GMDS-ER will now be examined in the following section.
4.7.5 Validity
Validity can be defined as the “the degree to which evidence and theory support the
interpretations of test scores entailed by proposed users of tests” (AERA, 1999, p.9). There
are three types of validity or validation procedures, namely content-description, criterionprediction and construct-identification procedures (Foxcroft & Roodt, 2001; 2006). Construct
validity refers to the extent to which it measures the theoretical construct or trait it is supposed
to measure (Aiken, 1997; Foxcroft & Roodt, 2001; 2006). Foxcroft and Roodt (2001; 2006)
document three ways in which construct validity can be ascertained, namely: 1) a high
correlation between a new measure and similar earlier measures of the same name; 2) by
using factor analysis for analysing the interrelationships of variables; and 3) by examining
whether it correlates highly with other variables with which it should theoretically correlate
with (convergent validity) and examines whether it correlates minimally with variables from
which it should differ (discriminant validity). Part of construct validity is concurrent validity,
which is defined by Coolican (2004) as the validation of a new test by comparing it with a
currently existing measure of the construct. In other words, it can be described as the
correlation of a previously unvalidated test with an already validated one (Jensen, 1980). To
establish the concurrent validity of the Extended Griffiths Scales, they were compared to the
Terman-Merrill Scale, which is a version of the Stanford-Binet. The GQ on the Griffiths
Scales ranged from 99.45 to 101.92 for the different age groups, while the Terman-Merrill
Intelligence Quotient (IQ) ranged from 102.77 to 106.87. The correlations between the GQ
and IQ obtained were satisfactory as they varied from r = 0.79 to r = 0.81 for the different
year groups (Stewart, 2005). Luiz and Heimes (1994) studied the construct validity of the
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Griffiths Extended Scales on a South African sample. They compared the Griffiths Scales
with the Junior South African Intelligence Scale (JSAIS) and found that the GQ and General
Intelligence Quotient (GIQ) of the JSAIS showed highly positive correlations, suggesting that
the Griffiths Scales and the JSAIS measure a similar construct.
Mothuloe (1990) administered the Griffiths Scales and the Aptitude Test for School
Beginners (ASB) to a sample of 45 Black Setswana-speaking Grade One children between the
ages of 5 years 9 months and 7 years 3 months. Significant correlations were found between
these assessment measures, ranging from r = 0.32 to r = 0.62. Tukulu (1996) completed a
correlational study using the Denver II Scales and the Griffiths Scales with Xhosa-speaking
pre-school children. Tukulu (1996) found that the Griffiths Scales is a “relevant diagnostic
measure for use with South African Xhosa-speaking children” (Baker, 2005, p.90). Luiz,
Foxcroft and Stewart (1999) investigated the construct validity of the Griffiths Scales, in
which a common factor analysis was used to examine the underlying dimensions of the
Scales. The sample of N = 430 South African children ranged between the ages of 54 and 83
months. The results of the study revealed that the Griffiths Scales tend to measure one factor,
and that the factor appears to be similar in the different race/cultural groups. The pattern of
correlation for South African and British subjects was also found to be similar, indicating that
the Scales are measuring a construct that is consistent across cultures and through time
(Stewart, 2005). Knoesen (2005) explored the reliability and construct-related validity of the
Locomotor Subscale of the GMDS-ER. Sixteen experts within the field of gross motor
development and assessment participated in a facet analysis with the aim of identifying the
constructs underlying the Locomotor Subscale to enable the researcher to develop a construct
model. In addition, a sample was collected of N = 1026 children between the ages of 30.9
months and 89.7 months from across the United Kingdom and Eire. Knoesen (2005) found
that satisfactory reliability coefficients and minimal measurement errors calculated for the
sample as whole as well as per gender and socio-economic status group, and provided
evidence for the reliability and internal consistency of the Locomotor Subscale as a whole as
well as per year group. The predominant construct underlying each unique item on the
Subscale was qualitatively identified and empirically verified for the sample as a whole, as
well as per gender and socio-economic status.
Due to the fact that the Griffiths Scales-Extended Revised is a diagnostic measure,
Luiz et al. (2006b) explored the Extended Revised Scales content-based evidence, including
an empirical analysis of the adequacy with which the test content represents the content
domain by means of a literature review and the consultation of experts. Content validity is
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when researchers evaluate the content of a measure to ensure that it is representative of the
area it is intended to cover, by using their expertise in the topic area to judge whether the
collection of items has failed to test certain skills or is unduly weighted towards some aspects
of the domain compared with others (Coolican, 2004). A facet analysis was conducted
separately on each subscale in order to provide proof of the validity of its contents. The
results indicated that the items in the six subscales are representative of their respective
content domain and that each item has a satisfactory degree of relevance to the construct
being measured.
4.7.6
The need for South African research on the Griffiths Mental Development
Scales-Extended Revised (GMDS-ER)
South Africa is a nation characterised by immense diversity in terms of the cultures,
languages, and socio-economic status of our people. Poverty and poor living conditions have
a major impact on the health status of children in South Africa and result in the classification
of ‘children at risk’ (Luiz, 1994). Despite a concerted effort by researchers to address the need
for more reliable and valid assessment measures of pre-school South African children, the
following shortcomings are still apparent: 1) specific tests are standardised for specific ethnic
groups to the exclusion of others, and there are limited standardised tests that assess the
development of black pre-school children; 2) specific tests are standardised for specific age
groups to the exclusion of others; and 3) existing developmental assessment measures are not
comprehensive, with most tests (except the Griffiths Scales) focusing on specific aspects of
development (Luiz, 1994). The Griffiths Scales have been widely used in the South African
context, as it is applicable to the wider population and has also undoubtedly demonstrated its
invaluable role in the assessment of South African children of all ethnic and socio-economic
groups. Luiz (1994) recognised that social and cultural factors impact performance on the
Scales, and suggested that it would be more valid to replace culturally loaded items that have
more influence on the verbal items with items that are equal in difficulty but more culturally
relevant.
Luiz (1994) believed that:
Future research will focus on adapting the Scales taking into account those biographic
and social factors, which previous studies have found to have a significant influence
on their performance. The goal is to construct a developmental profile for all South
African children (p.86).
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In accordance with the abovementioned goal, more and more studies have been
undertaken on the GMDS-ER in the South African context to ensure its applicability with
different cultural groups as well as contribute to the growing knowledge base of child
development in South Africa. Furthermore, the growing need for the GMDS-ER to be ‘tried
and tested’ within the South African society has led to the establishment of an ongoing
research project involving the testing of clinical as well as normal samples on the GMDS-ER.
This South African project is linked to ongoing and extensive research on the GMDS-ER in
the United Kingdom (Davidson, 2008). It is hoped that the findings from these studies will
contribute towards the standardisation and norming of the GMDS-ER for South African
children in particular (L. Stroud, personal communication, May 25, 2007).
4.7.7
Research studies conducted on the Griffiths Mental Development Scales and
Griffiths Mental Development Scales-Extended Revised (GMDS-ER)
The clinical merit of the Griffiths Scales is increasing. Research on the Griffiths
Scales have been conducted internationally from as far a field as Canada (Ramsey &
Fitzharding, 1977), Columbia (Cobos, Rodriques & De Venegas, 1971), China (Collins, Jupp,
Maberley, Morris & Eastman, 1987), Norway (Sletten, 1977), Australia, Greece, France,
Lebanon, Germany and the United States of America. Research on the Griffiths Scales has
also taken on local prominence in child development due to its application on a wide range of
populations (Allan, 1988; Bhamjee, 1991; Mothuloe, 1990; Schröder, 2004; Tukulu, 1996).
Initially, research studies consisted of case studies (Luiz, 1988a; 1988b; 1988c) and
correlational studies which examined the relationship between the Griffiths Scales and other
measures (Heimes, 1983; Lombard, 1989, Mothuloe, 1990; Worsfold, 1993). Such studies
preceded normative studies using larger samples of Black, White, Asian and Coloured
Children (Allan, 1988; 1992; Bhamjee, 1991; Mothuloe, 1990; Tukulu, 1996). These studies
were followed by validity studies (Stewart, 1997; Luiz, Foxcroft & Stewart, 1999; Povey,
2002). The research focus then shifted to the overall revision process of the Griffiths
Extended Scales (Barnard, 2000; Kotras, 2003) and on clinical populations (Kotras, 2001;
Schröder, 2004). Research on the Griffiths Scales has primarily been conducted in two areas,
namely clinical and technical studies. Since the revision of the Scales, several studies have
focused on the performance of clinical and normal populations on the original Griffiths Scales
and on the GMSD-ER. In addition, technical studies have been conducted on the Subscales of
the GMDS-ER, its psychometric properties and its validity and reliability as a developmental
assessment. Some of these studies will be reviewed in the following subsection.
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4.7.7.1 Clinical studies
Research relating to the clinical utility of the Scales has provided evidence that the
Scales are useful in the clinical assessment and diagnosis of children from normal as well as
diverse population groups. Stewart (2005) has agreed that the value of the Griffiths Scales is
illustrated in that they can be administered across all clinical populations and “have proved to
be a most effective and efficient tool in the assessment of young children, in a diversity of
cultural and social contexts” (p.25). The original Scales have been administered to a wide
range of children, including a hearing-impaired child (Luiz, 1988a), a battered child (Luiz,
1988b), borderline mentally handicapped pre-schoolers (Houston-McMillan, 1988), and a
physically disabled child (Krige, 1988).
Research on the original Scales also focused on the need for South African norms and
more specifically looking at whether British norms were appropriate for South African
children. Allan (1988) studied the extent to which the subject variables of gender, language
and socio-economic status influenced performance on the Scales. The possible confounding
variables of age, central nervous system development and urban-rural residence were held
constant, while gender, language and socio-economic status were built into the design. The
South African sample consisted of 60 children aged 5 years with equal numbers of each
gender and language group (English and Afrikaans-speaking children). The major findings of
Allan’s (1988) study were that: 1) South African 5-year-olds and their 5-year-old British
counterparts differed significantly on the General Quotient and in their performance on four
of the six Subscales; 2) the influence of the subject variables of gender and language group on
test performance was minimal; and 3) children in the different socio-economic groups
differed significantly on the General Quotient and in their performance on four of the six
Subscales. Therefore, this study indicated that the present British norms of the Griffiths
Scales were not that applicable for use with South African children. It was suggested that the
findings of this study should be taken into consideration in the interpretation of individual
Griffith’s assessments until the re-standardisation of the Scales is completed (Allan, 1988).
Allan’s (1992) doctoral thesis focused on the performance of South African normal
pre-school children on the original Griffiths Scales, and specifically her study explored the
claims of culture bias within the measure. The aims of her research were: a) to compare the
performance of South African black, coloured and white children on the Scales; b) to
establish the applicability of British norms for a South African sample of children from
different backgrounds; and c) to establish the extent to which variables such as gender,
language and socio-economic status influence test performance. In analysis of the first aim,
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the results of the study showed that overall there were performance differences within and
between the ethnic groups but no consistent patterns were noted. In analysis of the second
aim, which focused on the performances of the separate ethnic groups, 1) the Coloured and
Black group scores differed significantly from the White and Indian groups on all Subscales
except for the Personal-Social and Practical Reasoning Subscales; 2) significant differences
were also noted between the Indian and White groups on these Subscales; 3) Indian children
performed significantly lower than all others on the Locomotor Subscale; 4) Indian children
performed significantly higher than Black children on the Eye and Hand Co-ordination
Subscale; 5) White children performed significantly higher than Black or Coloured children
on the Language Subscale; and 6) Indian and White children performed significantly higher
than Black children on the Performance Subscale. Results of the second aim reported that,
compared to the British sample, all South African 5-year-olds performed significantly better
on the Locomotor Subscale. When the results obtained were taken into account, it was
concluded that: 1) item bias may hinder a national multi-cultural standardisation of the
GMDS for South African children; 2) British norms cannot be applied to White or Indian
South African children but appeared to be more applicable to Black and Coloured South
African children; and lastly, 3) when considering the final aim, gender was found to have
minimal influence on the performance of 5-year-old South African children, whereas
language and socio-economic status do.
Whilst the abovementioned research studies investigated performance on the original
Griffiths Scales, the attention will now turn to studies that have been conducted utilizing the
GMDS-ER. Since the introduction of the GMDS-ER, this updated measure has significantly
contributed to our growing knowledge base of child development within such clinical
samples. Clinical studies utilizing the GMDS-ER have focused on: autistic children (Gowar,
2003), HIV positive/AIDS infants (Kotras, 2001; Sandison, 2005), hearing impaired children
(Schröder, 2004), and children with cochlear implants (Makowem, 2005). Baker (2005)
investigated the performance of children with Attention Deficit Hyperactivity Disorder on the
GMDS-ER using a sample of N = 38 children, drawn from an existing database created during
the revision of the Scales. Baker (2005) found that the general performance of the ADHD
sample on the GMDS-ER was above average, and that their performance across the six
Subscales ranged from average to superior, with the poorest performance being on the Eye
and Hand Co-ordination Subscale, and the best performance being on the Performance
Subscale. Baker also compared the performance of her sample with a normal South African
sample. Significant differences were obtained between the ADHD and normal sample on the
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General Quotient (GQ) as well as on three of the six Subscales, namely the Hearing and
Speech, Eye and Hand Co-ordination and Performance Subscales. Davidson (2008) compared
the performance of first and second born twins on the GMDS-ER using a sample that
consisted of 22 pairs of twins. Davidson (2008) found no significant differences between the
first and second born twins’ general development. However, Davidson (2008) concluded that
the information generated from her study contributed to: 1) child development research; 2)
twin developmental research within a South African context; and 3) a greater group of studies
on the GMDS-ER currently underway in the United Kingdom and South Africa, which is
aiming to contribute to the international credibility of this measure. Such studies emphasize
the importance of regular developmental assessments and the importance of the Griffiths
Scales as a diagnostic tool (Luiz, 1997).
4.7.7.2 Technical studies
Research relating to technical studies refers to studies on the reliability and validity of
the Scales, in which research is generated to show that the GMDS-ER is a reliable and valid
assessment measure (Beail, 1985; Griffiths, 1984; Luiz, 1988c; Mothuloe, 1990; Stewart,
1997; Worsfold, 1993). Furthermore, technical research has also provided information on the
normal performance of South African children of different ages and population groups on the
GMDS and GMDS-ER (Baker, 2005). Kotras (1998) investigated the Language Subscale,
with a revision of the 20 small pictures and the large picture, with the goal of making them
more culturally relevant in a contemporary South African context. The results of Kotras’s
(1998) study recommended that the order of the 20 small pictures should be revised so that
separate norms for South African children could be constructed. Kotras (2003) extended her
research within the Language Subscale to her doctoral thesis in which she explored its
construct validity on the Revised Extended Griffiths Scales. The results of this study provided
evidence regarding the construct validity of the Language Subscale as well as a verified
construct-model. One of the more recent technical studies was conducted by Stewart (2005)
on the Extended Griffiths Scales, which aimed to propose new items and adapt existing items
for Subscales A, B, C, D, and E as part of a larger project which aimed to revise and
restandardise the Extended Griffiths Scales. The research was guided by seven aims and
divided into seven steps, which consisted of reviewing the existing items, adapting
problematic items, and writing and testing out new items. As the study was exploratory no
specific hypotheses were generated and the seven aims and steps mentioned previously
guided the methodological process. Stewart’s (2005) findings included the consolidation of
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the theoretical tenets on which the Griffiths Scales are based, and a content analysis of the
original items. Furthermore, these findings in the theoretical and the content arenas in turn
influenced the creation of the pool of new and adapted items, as well as the final item
recommendations. 31 Item changes were recommended for the Experimental version of the
Extended Griffiths Scales, as well as the adjustment of 31 cut-off time limits (Stewart, 2005).
The recent revision and restandardisation of the GMDS-ER has necessitated
investigations into its psychometric properties. This need for technical studies has resulted in
numerous research findings based on studies conducted on the Subscales of the GMDS-ER.
Barnard (2000) revised the Practical Reasoning Subscale, and Knoesen (2003) completed a
predictive validity study involving the assessment of urban pre-school children to determine
whether the GMDS-ER could be used to predict the scholastic performance of Grade One
learners. Furthermore, doctoral theses have also been conducted on the Subscales of the
GMDS-ER, such as Kotras’s (2003) exploration of the construct validity of the Revised
Extended Griffiths Language Subscale; Barnard’s (2004) exploration of the validity of the
Revised Griffiths Practical Reasoning Subscales; Knoesen’s (2005) exploration of the
reliability and construct-validity of the revised Locomotor Subscale; Moosajee’s (2007)
exploration of the validity of the revised Personal-Social Subscale, and Povey’s (2008)
exploration of the validity of the revised Eye and Hand Co-ordination Subscale. The research
findings of these studies found that these five subscales, namely Language, Practical
Reasoning, Locomotor, Personal-Social and Eye and Hand Co-ordination, yielded more than
one construct.
Other studies have also focused on studying normal South African children. Van
Rooyen (2005) conducted comparative research on normal South African (N = 129) and
British (N = 161) children on the GMDS-ER. Van Rooyen’s (2005) findings include: 1) South
African and British children’s overall performances on the GMDS-ER GQ are similar; 2) a
great deal of variability exists between the GMDS-ER profiles of normal South African and
British children (when individual subscales and year groups are considered); and 3) South
African children performed better on the Locomotor and Personal-Social Subscales, while
British children performed better on the Language and Practical Reasoning Subscales.
Performance on the Eye and Hand Co-ordination Subscale was similar for the two samples,
while the findings obtained on the Performance Subscale indicated that the performance was
too variable to come to any general conclusions. Van Heerden (2007) replicated Van
Rooyen’s (2005) study, and aimed to generate information on the applicability of the British
norms for the contemporary South African population. Van Heerden (2007) found that in
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contrast to Van Rooyen’s (2005) results, a significant difference does in fact exist between the
South African and British children’s overall developmental profiles as measured on the
GMDS-ER. In addition, Van Heerden also found that British children performed significantly
better on the Language, Eye and Hand Co-ordination and Practical Reasoning Subscales
(2007).
Furthermore, she found that there were no significant differences between the two
samples on the Performance Subscale, which indicates that the performance on this particular
Scale are similar (Van Heerden, 2007). Recommendations from these studies suggested that
further investigations into the applicability of the GMDS-ER for the diverse South African
context are needed and that the establishment of South African norms for the clinical
utilization of the GMDS-ER is essential. Both Van Rooyen (2005) and Van Heerden (2007)
recommended that caution should be exercised with regard to the utilization of the Britishbased norms in the South African context. The current study falls within the technical area as
it is assessing a normal population of a sample of South African pre-school boys and girls on
the GMDS-ER. In conclusion, Davidson (2008) highlighted the value of technical studies and
stated, “without technical studies continuously enhancing the measure’s psychometric
properties, the clinical studies performed using the same measure would be invalid and
unreliable” (p.63).
4.8
Chapter overview
Firstly, an overview was provided of the importance of child developmental
assessment, and specific mention was made of the goal of early childhood assessment within
the South African context. Developmental assessment was defined as “a process designed to
deepen understanding of a child’s competencies and resources and of the caregiving and
learning environments most likely to help a child make fullest use of his or her developmental
potential” (Greenspan, & Meissels, 1996, p.11). Two forms of developmental measures were
described, namely screening and diagnostic measures. It was mentioned that the GMDS-ER
falls within the diagnostic category. Secondly, it was emphasized that cultural differences
should be taken into account when test performance is interpreted (Foxcroft & Roodt, 2001;
2006). A review was provided of developmental assessment measures within South Africa,
and in this regard it was highlighted by Foxcroft and Roodt (2001; 2006) that during the last
decade, a concerted effort has been made by researchers to attend to the need for more reliable
and valid developmental measures for use with South African children. It was also explained
that researchers have focused their efforts on the construction of culture-reduced tests and
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have adapted, revised and normed assessment measures that have been extensively used in
other countries (Foxcroft & Roodt, 2001; 2006). Selected international developmental
measures that have been adapted for use in South Africa were then presented.
Thirdly, a historical overview of the Griffiths Scales was provided including the revision
process, which led to the development of the GMDS-ER. Furthermore, the nature and
description of the Subscales of the GMDS-ER was provided, followed by an overview of
research studies that have been conducted on the Scales to date.
The following chapter will present the problem statement and research methodology
that guided the completion of this study.
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CHAPTER FIVE
RESEARCH METHODOLOGY
5.1
Introduction
“Psychologists conduct research because they know they cannot rely on ‘feeling’,
‘intuition’ or just plain old ‘common sense’ to answer questions about people and their
behaviour” (Coolican, 2004, p.1). Many so called ‘common sense’ claims have been made
about gender differences that are mostly based on stereotypical notions or casual observations
of children in a playground. It is probable that such claims have not been based on supporting
empirical evidence. One may speculate that the reason why such claims are made is because
people have a desire to arrive at their own conclusions regarding the existence of gender
differences. This chapter outlines the problem investigated in the present study and the
primary and specific aims that guided the research process. The methodology employed in
conducting the study will be delineated, including the research design, the participants, the
sampling procedure and relevant inclusion criteria, as well as the assessment measures
utilized and the procedure followed in the collection of the data. Thereafter, a description of
the statistical analysis will be provided, followed by the ethical considerations relevant to the
present study.
5.2
Problem formulation and aims of the study
Despite the original and revised Griffiths Scales reflecting varied or insignificant
statistical differences in the performance of boys and girls on the Scales as documented in
chapter two, it is nonetheless imperative that variables such as gender be explored on the
Extended Revised version. As mentioned in the previous chapter, to date little research has
focused on comparing the differences in the development of South African pre-school boys
and girls utilizing the Griffiths Mental Development Scales-Extended Revised (GMDS-ER).
Therefore, it is to this much-needed area of research that the present study devoted itself. In
this regard, the first step in the research process is to formulate a research question that will
guide this investigative process. The research question that was formulated in the present
study focused on whether the boys and girls performed differently on the GMDS-ER. The
prevailing gender stereotypes, such as that boys excel in mathematics and girls excel in
language, prompted researchers to investigate gender differences in intellectual ability. As
discussed in chapter two, gender-related research during the 1960s and 1970s focused
narrowly on verbal, visual-spatial and quantitative abilities. The literature review reflected
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that no gender differences were found within overall intellectual functioning. However,
contradictory and inconclusive findings were obtained on whether a pattern of intellectual
differences exists between the gender groups. Furthermore, limited empirical investigations
have been conducted on developmental differences between the gender groups. As a result of
the myths surrounding gender differences coupled with the limited knowledge regarding the
developmental differences between the gender groups, the researcher chose to explore the
developmental similarities and differences between boys and girls on the GMDS-ER.
As the GMDS-ER was standardised for use in the United Kingdom, this study will not
only add to the growing body of knowledge regarding the possible differences in the
development of 5- and 6-year old boys and girls, but will also contribute towards expanding
our understanding of how South African children perform on the GMDS-ER. As more and
more South African studies are conducted, it will be possible to standardise and norm the
GMDS-ER for South Africa. Against this backdrop, this study aimed to explore and compare
the developmental profiles of a sample of normal South African pre-school boys and girls
between the ages of 5 and 6 years utilizing the GMDS-ER. In order to achieve this, the
following more specific aims were explored:
1. To explore and describe the developmental profiles of pre-school boys and girls (in
the 5- and 6-year-old age group), with respect to their overall performance on the
GMDS-ER as well as their performance on the six Subscales.
2. To compare the General Quotient (GQ) and the developmental profiles across the six
Subscales of pre-school boys and girls (in the 5- and 6-year-old age group) on the
GMDS-ER.
5.3
Research method
According to Knoesen (2003) the choice of a research method is an integral part of
any study and should be approached with care. The appropriate method that meets the aims
and requirements of the study is crucial to the success of the study. Mouton (2001) defined a
research method as a plan or blueprint of how one intends conducting the research. In
accordance, De Vos, Fouché, Strydom and Delport (2002) explain that a research method
focuses on the end product, formulates a research problem as a point of departure and focuses
on the logic of the research. The present study employed a quantitative method in order to
establish the similarities and differences that exist between normal South African pre-school
boys and girls between the ages of 5- and 6-years old. Quantitative research seeks to quantify
94
or numerically portray observations about human behaviour. The quantitative researcher
attempts to describe relationships among variables mathematically, and to apply some form of
numerical analysis to the social relations being examined (Jackson, 1995). Furthermore,
according to Louw and Edwards (1997) “quantification makes comparisons possible” (p.31).
This is evident in this study as the analysis of the results is numerically presented.
In order to achieve the aims of the study, an exploratory-descriptive research method
was utilized. Exploratory research is conducted to gain insight into a situation or phenomenon
where there is limited knowledge (Bless & Higson-Smith, 1995; De Vos et al., 2002). The
current study adopted the exploratory approach in order to gain insight into the area of gender
differences in South African pre-school children utilizing the GMDS-ER, as there is limited
research and information in this particular area. Exploratory-descriptive research is a primary
and necessary goal for the development of scientific knowledge (Cozby, 1993). It is hoped
that the results of the current study will contribute to the knowledge base on the performance
of South African children and in this regard prompt further studies to be undertaken utilizing
the GMDS-ER. Exploratory-descriptive research attempts to observe, record and describe the
behaviour of interest (Cozby, 1993). The developmental profiles of the sample will be
described with respect to their overall performance on the GMDS-ER as well as within the six
Subscales. Exploratory-descriptive research involves the systematic examination and
organisation of carefully observed information about the construct under study (Cozby, 1989,
1993; Dane, 1990). Within this framework, a between-subjects design in which a form of
matching was used to control extraneous variables was employed. Foxcroft (personal
communication, May 25, 2007) described the need for matching participants when conducting
gender-related research:
When a non-manipulated independent variable is used, the participants naturally fall
into pre-determined groups on the basis of particular subject characteristics. One of
the difficulties in having pre-determined groups is that they could differ on a number
of other variables. For example, although the children in this study naturally fall into a
male or female group by virtue of their gender, there may be a number of other
variables that could influence their performance on the GMDS-ER and ultimately
provide alternative explanations for the differences between the gender groups. In
view of this and in order to obtain a meaningful interpretation of the test results, it is
necessary to control for these potential extraneous variables by matching the
participants on age, socio-economic status and cultural group.
It has repeatedly been found in South African research that the variables of culture and
socio-economic status are related to performance on developmental and cognitive measures
(Allan, 1988; 1992; Bhamjee, 1991; Knoesen, 2003; Schröder, 2004; Stewart, 2005; Van
95
Heerden, 2007; Worsfold, 1993). As these extraneous variables could have affected the
interpretation of the test results, they had to be controlled for in this study. Pairs were created
and thus matched on the combination of these variables (age, socio-economic status and
culture). In practise, the researcher matched a coloured boy aged six years from a middle class
background with a coloured girl aged six years from a middle class background, and then the
boy in the pair was assigned to the six-year-old male group and the girl to the six-year-old
female group. By doing so, a meaningful comparison could be made of the developmental
profiles between the 5- and 6-year-old gender groups. The extraneous variables of cultural
group and socio-economic status which could have affected the outcome of the study, and the
manner in which they were controlled for in the present study, is discussed below.
a)
Culture
“Our culture has an all pervasive influence on the way we learn, think about things,
and behave…culture cannot be considered as a separate factor, exerting an influence apart
from other factors in the person’s environment as it is an integral part of that environment”
(Grieve, 2001, p.328). Research into development across different cultures has led to the
conclusion that cognitive development is inseparable from the context in which it occurs, and
those contexts are determined by the economic, family, and religious values provided by
one’s culture (Bjorklund, 1995). Cultural norms define appropriate behaviour for the group
members. Different developmental experiences across the cultural groups may thus lead to
differences in the behaviour of children from different cultural backgrounds (Allan, 1988). In
addition, Allan (1988) summed up the influence of culture on testing behaviour and explained
that the cultural milieu in which the child is reared will influence test behaviour and that such
cultural influences will be reflected in the child’s performance. In the South African context,
cultural factors need to be considered during the test adaptation and test construction
processes. The development of culture-fair assessments is crucial for our multi-cultural
context, in that it is a more realistic approach to test construction by focusing on experiences
that are common across different cultures. The GMDS-ER has been termed ‘culture-fair’ in
that it has been successfully used in several countries (e.g., United Kingdom, Eire, Portugal,
Australia, Hong Kong, South Africa and United States of America) and extensively
investigated to reduce cultural bias as far as possible (Luiz et al., 2006a; 2006b). Items that
were identified as being biased were removed and improvements subsequently made to ensure
that the impact of culture was minimised (Kotras, 1998; Luiz et al., 2006a; Stewart, 2005).
96
It is interesting to note that South African studies have found that cultural influences
have less of an impact on a child’s performance on the Griffiths Scales, when compared to the
impact of other variables. For example, studies have found that socio-economic status has a
greater impact on children’s performance on the Scales than culture (Allan, 1988; 1992;
Baker, 2005; Barnard, 2000; Bhamjee, 1991; Knoesen, 2003; Schröder, 2004).
Due to the fact that the GMDS-ER has not been translated into other languages as yet,
only participants whose first language was English could be included in the present study. As
a result, an equal distribution of the four cultural groups could not be obtained, as most of the
participants who fulfilled this language criterion were within the White and Coloured cultural
groups.
b)
Socio-economic status (SES)
Socio-economic status (SES) refers to the “broader indices of a person or family’s
social standing in society, where the major indicators of SES are education, occupation and
income” (Grieve, 2001, p.332). The socio-economic aspects of the environment have a
significant impact on the experiences that moderate abilities, attitudes and behaviour (Grieve,
2001). One of the areas in which SES has been documented to have a highly negative effect is
on cognitive development. Socio-economic status (SES) directly affects the available
educational resources along with the quality of the child’s psychosocial rearing environment.
Parents within a low SES group may lack the time to spend with their children as well as the
level of stimulation they can provide (González, 2001). Their ability to create a high quality
home environment is critical as the quality of a child’s early life environment plays a
determining role in the child’s level of brain stimulation and thus brain development (Najman
et al., 2004). Research has found that SES differences influence performance on a variety of
measures for children from all cultural groups (Allan, 1988; 1992; Baker, 2005; Barnard,
2000; Bhamjee, 1991; Knoesen, 2003, Schröder, 2004; Van Heerden, 2007). Schröder (2004)
has attributed this differential performance to the factors described above, namely that
children from the different SES groupings have different opportunities and access to the
necessary social and educational facilities.
The SES of the participants in the present study was controlled for and was used as
one of the variables on which the boy and girl pairs for the 5- and 6-year-old gender groups
were matched. Riordan’s (1978) socio-economic classification system was used to determine
the socio-economic status of the participants. Riordan (1978) set boundaries for upper, middle
and lower classes for the Black, Coloured, Asian and White population groups in Port
97
Elizabeth, based on the family breadwinners’ educational achievements and occupational
status. Foxcroft (1985) suggested that educational level provides a more reliable indicator of
socio-economic status than does the level of income, since the former is less likely to invoke
the emotional responses that questions regarding income might. Riordan’s (1978)
classification system has frequently been used for Griffiths’ studies in Port Elizabeth on both
the original and Extended Revised versions (Allan, 1988; 1992; Baker, 2005; Barnard, 2000;
Bhamjee, 1991; Foxcroft, 1985; Knoesen, 2003; Stewart. 2005; Van Heerden, 2007; Van
Rooyen, 2005). Furthermore, Allan (1988) investigated the validity of this classification
system by comparing the results to that of alternative systems and concluded that the system
proved valid for use in Port Elizabeth. It should be noted that although Riordan’s (1978)
classification system is fairly dated, it is the only classification system of its kind available in
South Africa, and was therefore the most useful way of obtaining the necessary information
(Baker, 2005). The breadwinners or primary caregivers of the children were required to record
their highest level of education on the Biographical Questionnaire. This was converted to a
numerical value according to Riordan’s (1978) classification system. The educational
classification of the breadwinner is provided in Table 2.
Table 2: Classification of breadwinner’s education
Breadwinner’s education
Score
University attendance
7
Post-matric training (not university)
6
Matric
5
Apprenticeship
4
Junior Certificate
3
Primary school
2
None at all
1
No response
0
The breadwinners or primary caregivers were requested to record their occupation on
the Biographical Questionnaire. The occupational classification of the breadwinner is
provided in Table 3.
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Table 3:
Classification of breadwinners occupation
Occupational Classification
Score
Top professional, executive, administrative and technical occupations
9
Professional, administrative and managerial workers
8
Independent commercial
7
Lower grade administrative, technical, clerical, with limited supervisory and
6
administrative responsibility
Artisans and skilled workers with trade qualifications
5
Routine clerical and administrative workers, service and sales workers
4
Semi-skilled production and manual workers
3
Unskilled production and manual workers
2
Not economically active or productive
1
No response
0
The aspect of this classification system that is the most dated is the classification
categories for the different cultural groups, and it was initially not going to be used in the
present study. Rather, the participants were initially going to be matched according to the
composite score from the occupation and education of the breadwinner. However, it became
clear that matching using this composite score severely restricted the number of pairs that
could be generated as only 13 pairs were obtained. It was then decided to use the boundaries
Riordan (1978) had set to classify the upper, middle and lower socio-economic groups to
allow for more scope with the matching procedure. Riordan’s (1978) classification of socioeconomic status according to these boundaries is provided in Table 4.
Table 4:
Classification of socio-economic status
Lower
Middle
Upper
Black
2-5
6-10
11-16
Coloured
2-6
7-10
11-16
Asian
2-6
7-10
11-16
White
2-10
11-13
14-16
The matching procedure will be described in more detail in section 5.5.1 after the
participants and sampling procedure have been described.
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5.4
Sampling procedure
A sample is a “small portion of the total set of objects, events or persons that together
comprise the subject of our study” (Seaberg, 1988, p.240). According to Powers et al. (1985),
a sample is studied in an effort to understand the population in which we are interested and as
such researchers are interested in describing the sample not primarily as an end in itself, but
rather as a means of helping us to explain some facet of the population. For the purposes of
the present study, the participants were selected through the use of non-probability, purposive
and convenience sampling. The non-probability sampling method is based on the fact that the
principle of randomisation is not implemented when selecting the participants (De Vos et al.,
2002). The probability of any particular member of the population being selected is not
known (Cozby, 1989). The disadvantage of non-probability sampling is that the researcher
cannot claim that the sample is representative of the larger population due to the unknown
probability that a participant will be selected. In addition, since statistical theories cannot be
applied to non-random samples, this results in the limited ability to generalise the properties
of the sample to the wider population. Replications of a non-probability study would need to
be undertaken in order to determine the generalisability of the results to the population
(Davidson, 2008; Rossouw, 1996; Worsfold, 1993). Furthermore, the researcher cannot
estimate the sampling error (Baker, 2005). However, non-probability sampling is
advantageous as the monetary costs and the time consuming process involved in probability
sampling is too high (Struwig & Stead, 2001); it is far less complicated, more economical,
and can be conducted “so as to take advantage of available subjects without the statistical
complexity of a probability sample” (Baker, 2005, p.114).
Within the non-probability framework, the methods of purposive and convenience
sampling were employed. In purposive sampling, the judgement of the researcher is used to
select the subjects who meet the objectives of the study (Siraj-Blatchford & Siraj-Blatchford,
2002). According to De Vos et al. (2002), in purposive sampling the sample is composed of
elements that contain the most “characteristic, representative or typical attributes of the
population” (p.207). In the present study, the inclusion criteria guided this selection process
and will be discussed shortly. Convenience sampling was also employed, as the sample was
chosen “purely on the basis of availability” (Struwig & Stead, 2001, p.111). Six pre-primary
and primary schools were contacted within Port Elizabeth to determine if they were willing to
have their learners who were in the required age range of 5- and 6-years-old assessed for the
present study and four schools consented. Participants meeting the inclusion criteria were also
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selected from the existing database on the GMDS-ER. Thus, the participants were chosen on
the basis of availability.
The participants were only included in the study if they met the following inclusion
criteria:
1.
Age
The participants had to fall between the age range of 5 years and 6 years 11 months.
2.
Gender
As the present study aimed to explore and compare the development of South African
pre-school boys and girls utilizing the GMDS-ER, the sample needed to consist of at least 30
boys and 30 girls to enable comparisons of the data to be made.
3.
Language
The participants had to have English as their first or home language, as the GMDS-ER
has not been translated into other languages as yet.
4.
Normalcy
The Biographical Questionnaire served as a screening measure to identify if any of the
participants had been diagnosed with a mental or physical disorder that would have had an
influence on their development and subsequent performance on the GMDS-ER. Examples of
such disorders include attention deficit hyperactivity disorder (ADHD), autism, dyslexia,
learning problems, delayed development as evidenced by developmental lags etc. The
Biographical Questionnaire requested relevant biographical and developmental information
about the participants and assisted in the application of these inclusion criteria. If any physical
or mental disorders were identified, the participant was not included in the sample due to the
possibility of skewed results. According to Luiz (2000), this method has been successfully
used in previous studies to determine normalcy.
5.5
Participants
Originally the total sample consisted of 79 children, of which 64 were assessed for the
purposes of the study and 15 were selected from the existing GMDS-ER database of the
Nelson Mandela Metropolitan University’s (NMMU) Psychology Clinic. To identify the
participants to be assessed, the researcher selected four pre-primary and primary schools that
spanned across Port Elizabeth. Two schools were selected from the middle-to-upper-class
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geographical region and two schools were selected from the lower-class geographical region
as it was hoped to have a sample with equal numbers from the upper, middle and lower socioeconomic status groups. Riordan’s (1978) socio-economic classification system was used to
classify the participants into the three groups. The principals and class teachers of the schools
selected those children who they believed met the age and normalcy criteria. The
Biographical Questionnaire screened the children to determine whether the potential
participants met the inclusion criteria. One parent requested that their child be excluded from
the study. Five children were excluded before the matched-pairs procedure began, as their
first languages were Xhosa and Afrikaans and thus they did not comply with the language
criterion for this study. The sample size reduced during the matched-pairs procedure, which is
described in the following section.
5.5.1
Matched-pairs procedure
When gender comparisons are made, it is vitally important that potential extraneous
variables are identified that may provide alternative explanations for the differences between
gender groups, and controlled for as strictly as possible. If this does not occur, the researcher
cannot conclude with certainty that if differences are found, that it is due to the nonmanipulated variable of gender. It was previously documented that variables such as socioeconomic status and culture have been found to impact child development and can influence
performance on assessment measures. Therefore, in order to arrive at any conclusions
regarding gender similarities or differences based on the findings of this study, matching the
participants on age, socio-economic status and culture controlled for these extraneous
variables. More specifically, the researcher created pairs based on a combination of the
abovementioned variables. In addition, to further control the impact of age, the data were
analysed separately for 5- and 6-year-olds. That is, a male and female group of 5-year-olds
and a male and female group of 6-year-olds were created. The boys in the pairs were assigned
to their corresponding male group and the girls in the pairs were assigned to their
corresponding female group.
Initially, the participants were matched on a combination of the following variables,
namely the boys were matched with girls of the same cultural group within a three-month age
interval on the same composite SES score. For example, a coloured boy aged 5 years 1 month
with a composite SES score of 11 was matched with a coloured girl aged 5 years 3 months
with a composite SES score of 11. Matching in this manner did not prove to be successful as
only 7 pairs could be generated. The age interval was then adjusted to five months to allow
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for more scope with matching the pairs. Literature on child development indicates that
development in 5- and 6-year-old children is not characterised by rapid growth as found in the
younger age groups. Therefore, 5- and 6-year old children can be matched according to 5month intervals, as their development is stable. When the participants were matched on the
combination of culture, 5-month age interval and same composite SES score, 16 pairs were
generated, which was still not sufficient for effective comparisons to be made. It was then
decided to classify the composite SES scores according to upper, middle and lower socioeconomic status using Riordan’s (1978) classification system in which boundaries were set
for the different cultural groups. This allowed for greater scope in matching the participants,
and the age range was further extended to within six-months and no greater. Therefore, the
participants were matched on the following variables, namely the boys and girls from the
same culture were matched using an age interval of 6-months within the same SES
classification group. Using the example above, a coloured boy aged 5 years 6 months from an
upper SES class was matched with a coloured girl of 5 years 1 month from an upper SES
class. Then the boy in the pair was assigned to the 5-year-old male group and the girl in the
pair to the 5-year-old female group. As a result, 32 pairs were obtained consisting of 64
children in total. The sample initially started off with 74 children; therefore 10 children were
excluded as a result of the matched-pairs procedure.
5.5.2
Description of the sample
The total sample included in the current study consisted of 32 matched pairs of boys
and girls, with 17 pairs in the age range of 5 years 0 months to 5 years 11 months; and 15
pairs in the age range of 6 years 0 months to 6 years 11 months. Thus, the total sample
included 64 children, with 34 in the 5-year group and 30 in the 6-year group. Table 5 presents
the breakdown of the sample by age category, culture, socio-economic status and gender.
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Table 5: Sample breakdown in terms of age, gender, cultural group and socio-economic status
Year V
Year VI
Total
5 years 0 months
6 years 0 months
5 years 0 months
to
to
to
5 years 11 months
6 years 11 months
6 years 11 months
n = 34
n = 30
N = 64
Male
17 (50%)
15 (50%)
32 (50%)
Female
17 (50%)
15 (50%)
32 (50%)
Black
0 (0%)
0 (0%)
0 (0%)
White
16 (47%)
28 (93%)
44 (69%)
Coloured
16 (47%)
2 (7%)
18 (28%)
Asian
2 (6%)
0 (0%)
2 (3%)
Upper
22 (65%)
22 (73%)
44 (69%)
Middle
6 (18%)
6 (20%)
12 (19%)
Lower
6 (18%)
2 (7%)
8 (13%)
Sample Size
Gender:
Cultural Group:
Socio-economic status:
The demographic breakdown of the sample in terms of age, cultural group and socioeconomic status will be discussed separately.
a)
Age
The mean age of the total sample was 71.31 months, with a standard deviation of 5.00,
the minimum age was 61.10 months and the maximum age was 82.30 months. The
breakdown of the total sample according to the two age categories for this study, namely the
5-and 6-year-old age groups is depicted in Figure 5.
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Figure 5:
Sample breakdown in terms of age categories
The total sample consisted of approximately equal numbers of participants in the two
age categories required for this study. There were 53% of participants in the 5-year-old age
group and 47% of participants in the 6-year-old age group. It is interesting to note that the
majority of the participants in the sample were from the upper socio-economic status group,
despite attempts being made by the researcher to select approximately equal numbers
representing each grouping. Pre-primary schools were selected from a range of geographical
locations in Port Elizabeth, which should have resulted in more children from a low socioeconomic status background. According to Potgieter (personal communication, September 20,
2008), classifying individuals according to the suburb in which they live reflects somewhat of
a Westernised mindset. It was found that many of the breadwinners or primary caregivers in
the perceived lower SES areas were educated and many of them worked within the
managerial and professional occupations.
b)
Cultural group
As previously mentioned, it was not possible to obtain an equal distribution of the four
cultural groups due to the English inclusion criterion. Due to the sampling method employed
in the present study, participants who met the inclusion criteria regardless of cultural group
were included. The variable of culture became important purely for matching the participants
in pairs, and not for comparative purposes. Therefore, most of the participants who met this
language criterion fell within the White and Coloured cultural groups. Figure 6 illustrates the
sample breakdown in terms of the cultural groups.
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Percentage of sample
Figure 6:
Sample breakdown in terms of cultural group
100
90
80
70
60
50
40
30
20
10
0
5-years-old
6-years-old
White
Asian
Coloured
Cultural groups
In the 5-year-old sample, 47% of the participants were in the White cultural group,
47% in the Coloured cultural group, and only 6% in the Asian cultural group. In the 6-yearold sample, 93% of the participants were in the White cultural group, 7% in the Coloured
cultural group and no participants from the Asian group.
c)
Socio-economic status (SES)
Figure 7 illustrates the breakdown of the sample into the various SES groups
according to the 5- and 6-year-old groups. The SES of the 5-year-old group comprised 65% of
the participants from the upper socio-economic group, 18% from the middle socio-economic
group, and 18% from the lower socio-economic status group. The SES of the 6-year-old
group comprised 73% from the upper socio-economic group, 20% from the middle socioeconomic group and 7% from the lower socio-economic group. Despite the fact that the
participants’ performance within the different SES groups will not be compared, the unequal
distribution of the SES groups will have to be considered carefully when interpreting the
results of this study as the majority of the sample in both the 5- and 6-year-old age groups
consisted of participants from the upper socio-economic group.
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Figure 7:
Sample breakdown in terms of socio-economic status
Percentage of sample
80
70
60
50
5-years-old
6-years-old
40
30
20
10
0
Lower
Middle
Upper
Socio-economic status groups
5.6
Assessment measures
The measures that were used to collect the data for the present study were the GMDS-
ER and the Biographical Questionnaire.
5.6.1
The Griffiths Mental Development Scales-Extended Revised (GMDS-ER)
The GMDS-ER was the assessment measure selected for the present study, as it
provides valuable insight into the child’s ability in comparison to other children within the
same age range (Davidson, 2008). A comprehensive literature review and conclusive NEXUS
search revealed that no studies on gender have been embarked upon in South Africa utilizing
the GMDS-ER. Developmental assessment measures like the GMDS-ER provide a platform
for assessing children’s performance relative to their peers, and emerges as a logical choice
for a study such as this to determine whether gender differences do in fact exist between preschool South African boys and girls. The GMDS-ER provided information on the
developmental profiles of the boys and girls in this sample, and enabled comparison of the
overall developmental profiles as well as on the six Subscales of the GMDS-ER to ascertain
where similarities and differences were obtained. As the GMDS-ER was discussed in detail in
chapter four, it will not be dealt with at length in this section.
Luiz et al. (2006b) investigated the reliability and validity of the GMDS-ER and
reported that the overall reliability of the GMDS-ER was highly satisfactory (0.993) and that
it was a valid diagnostic developmental measure in that content-based and construct-related
evidence was established. The numerous studies that investigated the Griffiths Scales’ validity
and reliability were documented in chapter four. It is worth mentioning that the new
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normative information and technical properties of the GMDS-ER enable the examiner to: 1)
convert the raw scores into percentiles and standard scores, 2) comment on significant
differences between subscales, and 3) make a qualitative interpretation of the standard scores
according to commonly accepted diagnostic criteria. However, it should be pointed out that as
the GMDS-ER has not been standardised for use in South Africa as yet, the norms developed
in the United Kingdom could not be used in this study. Instead, the raw scores obtained were
used in a criterion-referenced way by converting them to quotients based on the child’s
chronological age. This system was used for the original Griffiths Scales and still appears to
be the most appropriate method to use in South Africa (L. Stroud, personal communication,
May 25, 2007).
Participants were assessed on the GMDS-ER at their respective pre-primary schools,
and the test duration was approximately 90 minutes long. The participants were assessed by
psychologists, intern psychologists and masters’ psychology students-in-training that had all
received training in the administration and scoring of the GMDS-ER as part of a registered
Griffiths Course conducted in the Department of Psychology at the Nelson Mandela
Metropolitan University (NMMU).
5.6.2
Biographical Questionnaire
According to Foxcroft and Roodt (2001), “assessment practitioners need a thorough
knowledge of the individuals they assess prior to the assessment” (p.135). Van Heerden
(2007) highlighted the fact that the personal circumstances of the test-taker and the timing of
the assessment influence the test scores obtained. Therefore, the Biographical Questionnaire
was used to extract relevant biographical and developmental information about the
participants, and as such served as the screening measure for this study. The questionnaire
was in the form of a mailed questionnaire and provided the parent or guardian with
dichotomous questioning that required a ‘yes’ or ‘no’ answer (Davidson, 2008). Information
regarding the participants’ gender, age, cultural group, parent or guardian’s occupation and
educational level, as well as whether the participant had any physical or mental disorders was
requested. In addition, information regarding the participants’ developmental history and
competence in numerous personal-social areas was required in order to enable the scoring of
the Personal-Social Subscale of the GMDS-ER. The information on the participants’
developmental history furnished the researcher with sufficient information to determine
whether any delays in development may have occurred that would impact the child’s test
performance. Furthermore, the information obtained from the Biographical Questionnaire
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enabled the researcher to calculate the socio-economic status of the participants according to
Riordan’s (1978) socio-economic classification system as discussed previously. A copy of the
Biographical Questionnaire is included in Appendix D.
5.7
Research procedure
The following procedure was followed in order to achieve the aims of this study. The
research proposal was presented at a Department of Psychology research proposal meeting,
where the research proposal was accepted and submitted to the Faculty Research, Technology
and Innovation Committee (FRTI) and the Nelson Mandela Metropolitan University (NMMU)
Ethics Committee (Human). Once approved by the respective committees, various principals
of pre-primary schools in Port Elizabeth were contacted and information letters were sent to
them requesting their permission to allow children from their school to participate in the
study. Once their consent was obtained to do so, the principals and class teachers were made
aware of the inclusion criteria of age and normalcy and they identified children in their preprimary school that could participate.
Information letters, informed consent forms and the Biographical Questionnaires were
delivered personally to the pre-primary schools to be given to the parents or guardians of the
potential participants. The signed and return Informed Consent Forms were then screened to
ensure that the children met the inclusion criteria. Testing sessions were arranged to take
place at the pre-primary schools, where an empty classroom was allocated for the testing, as it
proved more convenient for the parents to have the assessments conducted in this manner.
The children were assessed on the GMDS-ER in the language in which they are schooled.
Whilst, the class teachers were instructed to only select English-speaking children, the
teachers included two Afrikaans speaking children. Test administrators who were fluent in
Afrikaans were requested to conduct those assessments, and the children’s profiles were
subsequently excluded from the sample. Test administrators scored their own protocols and
compiled an individualised report for each participant assessed. Furthermore, the parents of
the participants whose performance fell within the below average range were contacted
telephonically to provide feedback in addition to the individual report. No child needed to be
referred to the University Psychology Clinic for further scholastic assessment.
In addition to the individual reports, Pearson Publishers kindly donated School
Readiness parent guides and workbooks for the children in the study who fell within the
middle-to-low socio-economic status group. These were distributed along with the reports to
assist with the recommendations provided. Permission was obtained from Dr. Louise Stroud,
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a Registered Griffiths Tutor at the NMMU, to access the Griffiths database to select
additional participants for this study. Each client whose information was captured in the
database had signed a contract, which gave permission for their raw data to be used for
research purposes. Therefore, the database was accessed and the necessary raw data was
extracted for the purposes of this study. Data capturing then took place and a statistical
analysis was conducted. The treatise was then compiled and completed and feedback
regarding the overall findings will be provided to the parents in the form of a comprehensive
letter.
5.8
Ethical considerations
“Ethical principles are vital in assisting the researcher in preventing abuses and they
delineate the responsibilities of the investigator” (Barnard & Seymour, 2003, p.6). The
primary purpose of ethical principles and values is to protect the welfare and rights of
research participants and to reflect the basic ethical values of respect for individuals,
beneficence and justice (Ethics in Health Research in South Africa, 2000). Permission for the
proposed study was obtained from the Ethics Committee (Human) of the NMMU. The
following ethical considerations were adhered to and upheld throughout this study.
5.8.1
Informed consent
Firstly, consent was obtained from the principals of the pre-primary schools to select
participants from their schools for the present study. Then, informed consent was obtained
from the parents of the participants before the data collection was undertaken. Accompanying
the informed consent form was a cover letter that provided the parent with the necessary
information regarding the study, and its potential risks and benefits. If the parents did not
understand the information or had queries, the researcher’s contact details were provided on
the informed consent form. The informed consent form also informed the parents that consent
was voluntary, and that they were allowed to withdraw their children from the research
project at any point. When dealing with child participants in research, their wishes need to be
respected irrespective of whether their parents have provided consent. This form of consent is
referred to as substitute or third party consent. Third party consent is necessary when the
participants do not have the capacity to make decisions on their own, and in such an instance
consent needs to be obtained from the parent and child (Davidson, 2008; Drew, Hardman &
Hart, 1996). Furthermore, when working with a child, it is imperative that they are assured
that they do not have to participate if they do not want to and that they can terminate the
110
testing whenever they want to stop (Drew et al., 1996). Such an instance occurred in the
present study when a parent had indicated that they wanted their child to be assessed and
included in the study yet the child was very tearful and did not want to participate. Her wishes
were respected and her class teacher was informed of the decision. Therefore, in line with the
principle of informed consent the administration of the GMDS-ER only commenced once the
informed consent forms had been signed and received by the researcher.
5.8.2
Confidentiality and privacy
Research participants have a right to privacy and confidentiality. Participant
confidentiality was maintained at all times throughout the study as the researcher captured the
data. In addition, codes were assigned in place of participants’ names and surnames when the
data was sent to the statistician to be analysed. The test administrator who assessed the child
compiled confidential individualised reports and the supervisor of the present study checked
the reports to ensure they were accurate and of high quality. No names of participants have
been mentioned when writing up this research treatise, nor will any names of participants be
mentioned when the research findings are disseminated to the principals of the schools.
5.8.3
Fairness
As the participants were between the age range of 5- to 6-years-old and the items
administered were of varying difficulty, the standard GMDS-ER administration procedure
was followed. It was ensured that the participants were not faced with too many excessively
easy or difficult items by administering the Scales at approximately 3 months below their
chronological age to obtain a basal score, and to cease administration after the ceiling was
obtained, namely after 6 consecutive negative scores. Fairness entails treating the participant
with respect and dignity and one of the ways this can be ensured is by preventing them from
undergoing any physical or psychological harm during the testing process. During the present
study, it was apparent that the children enjoyed the process as it was in a familiar environment
as well as the fact that most of their friends were also being assessed. Therefore, the test
administrators were dealing with bundles of excitement during the testing process.
5.8.4
Inclusion criteria
The selection, exclusion and inclusion of participants was just and fair, based on the
inclusion criteria. No participant was inappropriately excluded on the basis of race, disability
or religious beliefs (Barnard & Seymour, 2003). This ethical consideration was upheld
111
throughout the study, as the participants that were excluded were done so on the basis of
either not meeting the inclusion criteria or not finding a match during the matched-pairs
procedure.
5.8.5
Investigator competence
“Researchers are ethically obliged to ensure that they are competent and adequately
skilled to undertake a proposed investigation” (De Vos et al., 2002, p.69). The test
administrators who assessed the children for the present study consisted of Masters
psychology students-in-training, as well as registered intern psychologists and registered
psychologists. These test administrators were reliable professionals who had been trained in
the administration of the GMDS-ER and who were ethically allowed to administer the
GMDS-ER.
5.8.6
Feedback
Feedback in the form of a confidential report for each participant was either given
personally or sent directly to the parents concerned. The supervisor of the present study
checked the individual reports to ensure that the test administrators exercised caution when
providing recommendations to the parents. Health professionals should not underestimate the
weight parents ascribe to the evaluative statements provided in reports, and this thought
guided the report process in this study. Verbal feedback was provided to those parents whose
children performed within the below average range on the GQ of the GMDS-ER. When this
was the case, the test administrators who assessed the children were required to provide
verbal feedback to the parents telephonically after having consulted with the researcher. In
addition, feedback regarding the overall findings of the research project will be mailed to
parents and principals of the pre-primary schools in the form of a comprehensive letter.
5.9
Data analysis
Data analysis is the statistical procedure that provides the answers to the specific aims
of a study. The objective of the present study was to explore and compare the developmental
profiles of a sample of South African pre-school boys and girls within the ages of 5- and 6years-old utilizing the GMDS-ER. Therefore, the data was analysed according to the specific
aims of the study, which were developed to realise the objective.
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5.9.1
The first aim of the study
The first aim of the study was to explore and describe the developmental profiles of a
sample of South African pre-school boys and girls (between the ages of 5- and 6-years-old),
with respect to their overall performance on the GMDS-ER as well as their performance on
the six Subscales. Descriptive statistics were employed to analyse the data according to the
first aim of the study. Descriptive statistics can be divided into two categories, namely
measures of central tendency and measures of dispersion (Davidson, 2008). Measures of
central tendency, such as means as well as measures of dispersion or variability, such as
ranges and standard deviations, were used to describe the data for this sample of boys and
girls per age group separately. The goal in measuring central tendency is to describe a
distribution of scores by determining a single value that identifies the centre of a distribution.
“The central value will be the score that is the best representative value for all of the
individuals in the distribution” (Gravetter & Wallnau, 2002, p.51). The mean is the arithmetic
average of a distribution and is the sum of the scores divided by the number of scores (Drew
et al., 1996; Gravetter & Wallnau, 2002). According to Coolican (2004), the mean is a
powerful statistic that is used in estimating population parameters and he believes that this
estimation is the basis for the more powerful parametric tests that can be used to investigate
significant differences or correlations. Therefore, the mean was used to describe the average
of the sample’s performance per age group on the GMDS-ER.
Measures of dispersion or variability were also used to analyse the data of the present
study, by looking at the range and standard deviation of the scores. “Variability provides a
quantitative measure of the degree to which scores in a distribution are spread out or clustered
together” (Gravetter & Wallnau, 2002, p.76). In this regard, the range is calculated by
working out the difference between the highest and the lowest raw scores within a distribution
(Drew et al., 1996). Thus, the range (indicating the highest and lowest scores) provides a
comprehensive description of the developmental profiles of the sample per gender group and
age group separately. The standard deviation approximates the average distance from the
mean and measures the extent to which scores are spread around the mean (Gravetter &
Wallnau, 2002; Louw & Edwards, 1997). Descriptive statistics were employed to explore and
describe the developmental profiles of the sample on the GMDS-ER for the boys and girls per
age group separately.
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5.9.2
The second aim of the study
The second aim of the study was to compare the General Quotient (GQ) and the
developmental profiles across the six Subscales of pre-school boys and girls (in the 5- and 6year-old age group) on the GMDS-ER. The second aim was achieved by conducting
independent sample t-tests to compare the GQs of the boys and girls per age group. This
enabled the researcher to determine whether the samples of boys in the 5-year-old age group
differed significantly from the girls in the 5-year-old age group, as well as with the boys in the
6-year-old age group compared with the girls in the 6-year-old age group. The independent
sample t-test is used to compare the means of two different groups of scores. The larger the
absolute value of t, the more likely it is to reflect a significant difference between the two
groups under comparison (Barnard, 2004). A Hotellings T2 test would be used to compare
the subscale profiles of boys and girls, followed by a Scheffe’s post-hoc t-test if an overall
difference in the profiles was found. With a Hotellings T2 test, the six subscales are compared
in one analysis, thereby enabling one to draw conclusions as to whether or not a difference
existed between the sample of boys and girls. Scheffe’s post-hoc t-test has the distinction of
being one of the safest of all possible post-hoc tests, because it uses an extremely cautious
method for reducing the risk of a Type I error. The Scheffe’s test uses an F-ratio to test for a
significant difference between any two-treatment conditions (Gravetter & Wallnau, 2002).
The reason why Scheffe’s test provides the greatest protection from Type I errors is because it
requires a larger sample mean difference before it is willing to conclude that the difference is
significant (Gravetter & Wallnau, 2002).
5.10
Chapter overview
This chapter delineated the methodological approach used in this study. The problem
statement, aims and research question were described. The research and sampling method was
explained, followed by a discussion of the sample composition and research procedure. A
description of the data analysis and ethical considerations relevant to the study were outlined.
The results obtained from the data analysis are presented and discussed in the
following chapter.
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CHAPTER SIX
RESULTS AND DISCUSSION
6.1
Introduction
Before the results are discussed in this chapter, it is important to review the aims of
this study. As mentioned in chapter five, the primary aim was to explore and compare the
developmental profiles of a sample of normal South African pre-school boys and girls
between the ages of 5 and 6 years utilizing the Griffiths Mental Development ScalesExtended Revised (GMDS-ER). In order to achieve this, the specific aims were: to explore
and describe the developmental profiles of pre-school boys and girls (in the 5- and 6-year-old
age group) with respect to their overall performance on the GMDS-ER as well as their
performance on the six Subscales; and to compare the General Quotients (GQs) and the
developmental profiles across the six Subscales of the pre-school boys and girls (in the 5- and
6-year-old age group) on the GMDS-ER.
Before the results of the descriptive statistics are provided and discussed in accordance
with the first aim of the study, the results from independent sample t-tests conducted on the
mean chronological age of the boys and girls will be presented, as this determined whether the
matching process was accurate. Thereafter, the results of the statistical analysis conducted to
achieve the two aims of the study will be presented.
To achieve the first aim, empirical findings will be presented in terms of a description
of the mean developmental profile of the whole sample on the GMDS-ER, including a
description of the sample’s performance across the six Subscales. Then, the mean
developmental profiles of the pre-school boys and girls per age group will be described
separately. These empirical findings were obtained using descriptive statistics. To achieve the
second aim, a comparison of the overall performance of the pre-school boys and girls on the
GQ is provided for the whole sample as well as per age group, followed by a comparison of
the sample’s Subscale profiles. These findings were obtained using an independent sample ttest to compare the GQs of the sample, and comparisons of the Subscale profiles were
obtained using a Hotellings T2.
For statistical purposes, it is important to note that mental age (MA), subquotient and
GQ scores were utilized in the data analysis of this study. As with other recent South African
studies (Davidson, 2008; Van Rooyen, 2005; Van Heerden, 2007), the scores were not
converted to percentiles and standard scores using the Analysis Manual (Luiz et al., 2006b),
as the GMDS-ER has not been standardised for South Africa as yet.
115
6.2
Comparison of gender groups in terms of age
Independent sample t-tests are used to compare the means of two different groups of
scores. The larger the absolute value of t, the more likely it is to reflect a significant difference
between the two groups under comparison (Barnard, 2004). Independent sample t-tests were
conducted on the overall mean chronological age between the genders as well as per age
group to determine whether there were any significant differences between them. If
significant differences were found, then this would indicate that the matched-pairs procedure
discussed in chapter five was not done correctly. If the differences were not significant, then
this would indicate that the matched-pairs procedure was accurate. The results of the
independent sample t-test conducted on the whole sample is presented in Table 6, followed by
the t-tests conducted per age group in Tables 7 and 8.
Table 6
Independent sample t-test comparing the mean chronological age of the boys and girls in the
whole sample
Mean
SD
Boys
70.94
5.13
Girls
71.69
4.92
* Non-significant p-value (p>0.05)
n
32
32
t
0.59
df
62
p*
0.56
Table 6 indicates that there was no significant difference between the mean
chronological age of the male versus the female group in the whole sample. This is important
for the matching procedure as it indicated that the matching was implemented correctly, and
that comparisons can be made as the mean chronological age between the gender groups is
similar. If a statistically significant difference were found, no comparisons would have been
possible. Statistical results for the two age groups separately will be presented in Tables 7 and
8.
Table 7
Independent sample t-test comparing the 5-year-old boys and girls on mean chronological age
Mean
Boys
67.13
Girls
68.03
* Non-significant p-value (p>0.05)
SD
3.04
2.82
n
17
17
t
0.88
df
31
p*
0.39
116
Table 7 indicates that there was no significant difference between the mean
chronological age of the male and female 5-year-old groups. Therefore, accurate comparisons
could be made between the gender groups in this age group.
Table 8
Independent sample t-test comparing the 6-year-old boys and girls on mean chronological age
Mean
SD
Boys
75.41
2.83
Girls
75.83
3.14
* Non-significant p -value (p >0.05)
n
15
15
t
0.39
df
28
p*
0.70
Table 8 indicates that there was no significant difference between the mean
chronological age of the male and female 6-year-old groups. Therefore, accurate comparisons
could be made between the gender groups in this age group.
6.3
Descriptive analysis of the sample’s performance on the GMDS-ER (Aim 1)
This section presents and discusses the findings of the study in relation to aim one,
which is to explore and describe the performance of the sample on the GMDS-ER. The mean
developmental profiles are provided for the sample as a whole, followed by the boys’ and
girls’ developmental profiles per age group.
6.3.1
Mean developmental profile of the whole sample
Table 9 provides a summary of the mean developmental quotient and sub-quotients for
the whole sample.
Table 9:
Overall mean and Subscale performance of the whole sample (N = 64)
GQ
AQ
BQ
CQ
DQ
EQ
FQ
Mean
116
120
116
120
109
111
118
Minimum Maximum
91
135
78
141
92
135
90
143
65
134
64
145
68
142
Range
44
63
43
53
69
81
74
SD
10
12
11
12
14
18
14
117
Figure 8 depicts the mean performance of the whole sample on the GQ and across the
six Subscales of the GMDS-ER.
Performance
Figure 8:
Developmental mean performance of the whole sample on the GMDS-ER
122
120
118
116
114
112
110
108
106
104
102
GQ
AQ
BQ
CQ
DQ
EQ
FQ
Subscales
The above Table and Figure reveal that the mean General Quotient (GQ) for the whole
sample was above average (Xˉ GQ = 116). Results on the Personal-Social (BQ) (Xˉ BQ = 116),
Performance (EQ) (Xˉ EQ = 111), and Practical Reasoning (FQ) (Xˉ FQ = 118) Subscales all
revealed above average performance. Superior performance was noted on the Locomotor
(AQ) (Xˉ AQ = 120) and Language (CQ) (Xˉ CQ = 120) Subscales. The Language Subscale has
been considered as the most intellectual of the Scales, and the Practical Reasoning Subscale
provides a good estimate of the higher order processes involved in logical reasoning. As can
be seen in Table 9, the sample’s performance on these Subscales was among their strongest
on the GMDS-ER.
A possible explanation for this sample’s superior to above average performance on
five of the six Subscales could be due to the fact that 88% of the sample consists of
participants from the upper and middle socio-economic groups, with 69% from the upper
socio-economic group. Therefore, it was assumed that their basic needs for food and shelter
had been met, and adequate resources had been provided in their early childhood to ensure
healthy development. This is evident as the participants have met the normalcy criteria and
thus been included in this study.
The Eye and Hand Co-ordination Subscale (DQ) (Xˉ DQ =109) was the only subscale
that recorded average performance. The largest range was found within the Performance
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Subscale (range 81), with the highest developmental sub-quotient of 145 and the lowest
developmental sub-quotient of 64. The lowest range was found within the Personal-Social
Subscale (range 43), with the highest developmental sub-quotient of 135 and the lowest
developmental sub-quotient of 92. The greatest variability in scores occurred within the Eye
and Hand Co-ordination, Performance and Practical Reasoning Subscales, as reflected by
their large ranges.
It is useful to review the findings of South African studies conducted on the GMDSER which have investigated the overall performance of normal 5- and 6-year-old children, as
they provide a benchmark against which to measure this sample’s performance (Knoesen,
2003; Van Heerden, 2007). In Van Heerden’s (2007) study, the Locomotor Subscale was
elevated above the other five Subscales, which is similar to the present study. Similarly,
Knoesen (2003) also found her sample’s performance on the Locomotor Subscale to be better
than on the other Subscales. South African children spend a considerable amount of time
outside playing with friends and family, thereby perfecting their locomotor skills. This
coupled with the fact that children are only required to attend formal schooling when they are
aged six turning seven years, could be possible contributing factors towards South African
children’s superior performance on this Subscale (Van Rooyen, 2005).
It is interesting to note that this sample’s performance on the Language Subscale is
considerably higher than in Van Heerden’s (2007) study, with a nine-point difference between
the two samples. The sub-quotients of the Locomotor and Personal-Social Subscales in Van
Heerden’s study are identical with the present study’s corresponding Subscales, whereas only
the Personal-Social Subscale and Eye and Hand Co-ordination Subscales of Knoesen’s (2003)
study were similar to the present study’s findings. Both Knoesen (2003) and Van Heerden
(2007) found their sample’s performance on the Eye and Hand Co-ordination Subscale to be
one of the weakest. In the present study a similar trend is found. Reasons that are often
provided to explain the poor performance of South African children on this Subscale revolve
around inadequate day-care facilities and pre-schools in the disadvantaged areas, which lay a
weak foundation when children enter formal schooling (Davidson, 2008). However, the
majority of this sample is from the upper socio-economic group, and they attend pre-schools
reputed to be well-equipped with the latest resources and experienced teachers. It may be
possible that the results obtained by the children in the low socio-economic group skewed the
mean sub-quotient for this Subscale. This is plausible as the minimum score within the low
SES group obtained on the Eye and Hand Co-ordination Subscale fell within the mild mental
119
retardation descriptive category. Therefore, it is important to analyse the findings of a study in
the context of its sample and individual participants.
6.3.2
Mean developmental profiles of the 5-year-old boys and girls
The mean developmental quotients in this age group are presented in Tables 10 and 11
below.
Table 10
Mean developmental profile for the 5-year-old boys (n = 17)
GQ
AQ
BQ
CQ
DQ
EQ
FQ
Mean
116
121
118
122
107
108
118
Minimum Maximum
91
135
93
141
93
134
90
143
74
134
64
137
68
140
Range
44
48
41
53
60
73
72
SD
14
16
11
18
19
22
18
Range
38
41
35
44
66
72
58
SD
11
12
10
12
18
23
14
Table 11
Mean developmental profile for the 5-year-old girls (n = 17)
GQ
AQ
BQ
CQ
DQ
EQ
FQ
Mean
116
118
122
121
109
108
118
Minimum Maximum
92
130
94
135
100
135
99
143
65
131
73
145
84
142
In reviewing the above results, it appears that the 5-year-old boys and girls obtained
similar results on the GMDS-ER. Interestingly, both the boys and girls obtained the same
above average GQ of 116, as illustrated by the purple shading in Tables 10 and 11. In
addition, the 5-year-old boys and girls obtained the same sub-quotients on the Performance
and Practical Reasoning Subscales, as indicated by the yellow shading. Their results on the
Performance Subscale (Subscale E) reveals average performance (Xˉ EQ =108), and their results
on the Practical Reasoning Subscales (Subscale F) reveals above average performance
120
(Xˉ FQ =118). The boys performed better on the Locomotor Subscale and only slightly higher
on the Language Subscale. The boys’ performance was superior on both the Locomotor
Subscale (Xˉ AQ =121) and the Language Subscale (Xˉ CQ =122). The girls performed better on
the Personal-Social Subscale and performed only slightly better on the Eye and Hand Coordination Subscale. The girls’ results on the Personal-Social Subscale indicate superior
performance (Xˉ BQ =122) and average performance on the Eye and Hand Co-ordination
Subscale (Xˉ DQ =109). Overall, the boys obtained their strongest performance on the Language
Subscale and their weakest performance was noted on the Performance Subscale. Overall, the
girls’ obtained their strongest performance on the Personal-Social Subscale and similarly,
their weakest performance was also on the Performance Subscale. When analysing the ranges
of the 5-year-old boys and girls, it appears that the GQ range was greater in the boys’
performance (range 44) than the girls, with the highest developmental quotient recorded at
135. Both 5-year-old boys and girls showed their largest range on the Performance Subscale.
The mean chronological ages and mental ages of the 5-year-old boys and girls is
presented graphically in Figure 9.
Figure 9:
Mean chronological ages and mental ages of the 5-year-old sample
81
Age (in months)
78
75
72
Boys (5-years-old)
69
Girls (5-years-old)
66
63
60
Chronological Age
Mental Age
The 5-year-old girls’ mean chronological age was 68 months and the 5-year-old boys’
mean chronological age was 67 months. As reflected in Figure 9, the 5-year-old girls’ mean
mental age was higher than the 5-year-old boys’. The girls obtained a mean mental age of 80
months, whereas the boys obtained a mean mental age of 78 months. Comprehensive
descriptive and inferential statistics will be dealt with under the umbrella of the second aim,
121
which focuses on the comparative performances between the genders per year group on the
GQ as well as across the six Subscales.
6.3.3
Mean developmental profiles of the 6-year-old boys and girls
The mean developmental quotients in this age group are presented in Tables 12 and
13.
Table 12
Mean developmental profile for the 6-year-old boys (n = 15)
GQ
AQ
BQ
CQ
DQ
EQ
FQ
Mean
117
121
113
120
111
116
119
Minimum Maximum
106
128
108
133
92
127
109
136
97
125
93
133
103
138
Range
22
25
35
27
28
40
35
SD
7
8
11
8
8
13
12
Range
24
52
30
39
31
38
58
SD
5
12
10
10
8
12
13
Table 13
Mean developmental profile for the 6-year-old girls (n = 15)
GQ
AQ
BQ
CQ
DQ
EQ
FQ
Mean
114
117
110
119
111
110
117
Minimum Maximum
100
124
78
130
93
123
95
134
93
124
88
126
77
135
In reviewing the above findings in Tables 12 and 13, it is apparent that the genders’
performance within this age group differed more in the quotients and sub-quotients obtained
across the six Subscales, than was the case in the 5-year-old age group. In careful analysis of
the quotients, it is evident that the 6-year-old boys obtained higher quotients than the girls on
each Subscale; with the exception of the Eye and Hand Co-ordination Subscale, in which the
same sub-quotient was obtained as illustrated by the blue shading in Tables 12 and 13. Both
genders obtained an above average GQ, however the 6-year-old boys’ mean GQ was slightly
122
higher (Xˉ GQ =117, SD 7, range 22) than the girls’ mean GQ (Xˉ GQ =114, SD 5, range 24). The
6-year-old boys in the present study obtained superior performance on the Locomotor
(Xˉ AQ =121) and the Language Subscales (Xˉ CQ =120). On the rest of the Subscales, the boys’
obtained above average performances. The 6-year-old girls in the present study obtained
above average performance across all six Subscales.
The greatest discrepancy between the genders’ existed on the Performance Subscale,
with a six-point difference in the sub-quotients obtained. Across the other five Subscales, the
difference favouring the 6-year-old boys’ in the sample was small. The 6-year-old girls in the
present study did not perform better than the boys on any of the Subscales. The girls’
strongest performance was on the Language Subscale, and their weakest performance relative
to their other Subscales was on the Performance Subscale. The boys’ strongest performance
was on the Locomotor Subscale, and their weakest performance relative to their other
Subscales was on the Eye and Hand Co-ordination Subscale. In the 6-year-old girls’ sample,
the largest range occurred on the Practical Reasoning (range 58) and Locomotor (range 52)
Subscales, with both recording a maximum score within the very superior descriptive
category, and recording a minimum score within the borderline descriptive category. In the 6year-old boys’ sample, the ranges were considerably smaller, with the largest range occurring
on the Performance Subscale (range 40), followed by the Personal-Social and Practical
Reasoning Subscales, in which the same range was obtained (range 35). The mean
chronological ages and mental ages of the 6-year-old boys and girls is presented graphically
in Figure 10.
Figure 10:
Mean chronological ages and mental ages of the 6-year-old sample
90
Age (in months)
87
84
81
Boys (6-years-old)
78
Girls (6-years-old)
75
72
69
Chronological Age
Mental Age
123
The 6-year-old girls’ mean chronological age was 76 months and the 6-year-old boys’
mean chronological age was 75 months. Despite the observation that the 6-year-old boys
obtained higher developmental sub-quotients, both 6-year-old genders obtained the same
mental age on the GMDS-ER, which was 88 months old. The youngest mental age recorded
for the 6-year-old girls’ sample was 73 months and the oldest mental age recorded was 117
months. The youngest mental age recorded for the 6-year-old boys’ sample was 80 months
and the oldest mental age recorded was 95 months.
6.4
Comparisons of the sample’s performance on the GMDS-ER (Aim 2)
To achieve the second aim, a comparison of the overall performance of the pre-school
boys and girls on the GQ is presented and discussed in this section, followed by a comparison
of the performance per age group on the GQ. These findings were obtained using an
independent samples t-test to compare the mean GQs of the boys and girls at the α-level of
0.05.
6.4.1
Comparison of overall performance of the gender groups
The results of the independent sample t-test that tested for a significant difference
between the GQ of the boys and girls in the whole sample are presented in Table 14.
Table 14
Independent sample t-test comparing the GQ of the pre-school boys and girls in the whole
sample
Mean
SD
116.44
10.80
Boys
115.19
8.83
Girls
* Non-significant p-value (p>0.05)
n
32
32
t
-0.51
df
62
p*
0.6131
When comparing the performance of the 32 pairs of pre-school boys and girls in the
whole sample, no significant difference was found between the mean GQs of the boys and the
girls. The results of the independent sample t-test conducted on the GQs of the pre-school
boys and girls within the 5-year-old age group are presented in Table 15.
124
Table 15
Independent sample t-test comparing the GQ of the pre-school boys and girls in the 5-year-old
age group
Mean
SD
115.91
13.99
Boys
116.14
11.11
Girls
* Non-significant p-value (p>0.05)
n
17
17
t
0.05
df
31
p*
0.9587
As reflected in Table 15, no significant differences were found between the 5-year-old
boys and girls on the mean GQs. The results of the independent sample t-test conducted on
the GQs of the pre-school boys and girls within the 6-year-old age group are presented in
Table 16.
Table 16
Independent sample t-test comparing the GQ of the pre-school boys and girls in the 6-year-old
age group
Mean
SD
116.71
6.83
Boys
114.12
5.40
Girls
* Non-significant p-value (p>0.05)
n
15
15
t
-1.15
df
28
p*
0.2583
Table 16 indicates that no significant differences were found in the overall
performance of the 6-year-old boys and girls. According to Foxcroft (personal
communication, December 3, 2008), the fact that these results indicate non-significant
differences between boys and girls in this study reflects positively on the revision of the
Griffiths Scales, as it suggests that the revision process was sensitive to not building in gender
bias.
Previous South African studies conducted on the original Griffiths Scales done by
Allan (1988), Tukulu (1996) and Ward (1997) investigated the influence of gender on the
performance of their samples, and also found that the mean GQs of the two gender groups did
not differ significantly. Allan (1988) focused on the performance of White 5-year-old boys
and girls, and the results of a multiple t-test indicated that there was no significant difference
between the GQs of the boys (M = 109.13, SD = 10.5) and girls (M = 110.27, SD = 7.9).
Tukulu (1996) focused on the performance of Black, Xhosa-speaking children between the
ages of 3 and 6 years, and the results of an independent sample t-test revealed that there was
no significant difference between the mean GQs of the boys (M = 95.57, SD = 9.48) and girls
125
(M = 99.47, SD = 11.12). In a similar study, Ward (1997) focused on the performance of
Coloured children between the ages of 3 and 6 years, and the results of the t-test revealed no
significant differences between the GQs of the boys. Asian, Coloured and White children
were included in the current sample, however no comparisons were made of the performance
of the different cultural groups, as it was not within the focus of this study. Therefore, the
results of the independent sample t-tests conducted in the present study coincide with the
findings obtained in previous studies on the topic. Only one study on the GMDS-ER utilized
an independent sample t-test to briefly investigate whether gender influenced the performance
of his sample (Van Rooyen, 2005). In contrast with the findings of the present study, Van
Rooyen (2005) compared a South African and British sample, and found a significant
difference between the GQ performance of the South African boys (M = 110.47) and girls
(M = 116.48). Despite the fact that these studies have also looked at the influence of gender
on the Griffiths Scales and will be referred to extensively in the following section, it needs to
be pointed out that none of these studies have focused solely on comparative performances of
their samples, and as such have not controlled for extraneous variables. Therefore, it cannot
be claimed with certainty that the results reported on from their studies are due to the sole
influence of gender. This study is the first of its kind on the GMDS-ER in which gender
differences were explored. Furthermore, the strict process of matching the boys and girls into
pairs and assigning them to their relevant age groups to control for the extraneous variables of
age, socio-economic status and culture has not been done before in studies on the GMDS-ER.
6.5
Comparison of the Subscale profiles on the GMDS-ER (Aim 2)
A Hotellings T2 test was used in this study to compare the subscale profiles of the
whole sample, as well as the subscale profiles of the boys and girls per age group. An overall
Hotellings T2 test revealed that there were no significant differences across the six Subscales
of the GMDS-ER in the whole sample (p = 0.720). With regards to the 5-year-old boys and
girls in the sample, an overall Hotellings T2 test revealed that there were no significant
differences between the genders in this age group across the six Subscales of the GMDS-ER
(p = 0.7135). With regards to the 6-year-old boys and girls in the sample, an overall
Hotellings T2 test revealed that there were no significant differences between the genders in
this age group across the six Subscales of the GMDS-ER (p = 0.8351).
Although the results of the independent sample t-tests and Hotellings T2 tests have
shown that there were no significant differences in the performance of this sample on the
GMDS-ER, the descriptive analysis indicated that the boys and girls in the sample performed
126
differently on some of the Subscales. Figure 11 graphically depicts the developmental profiles
of the genders within the two age groups under comparison. In addition, Table 17 summarises
the comparison between the boys and girls in the two age groups in terms of their mean GQs
and sub-quotients. It is important to alert the reader to the fact that in the following section,
the researcher is not attempting to make any causal inferences based on the results of the
descriptive analysis, but aims to merely emphasize the descriptive observations noted and to
point out areas that would benefit from further investigation.
Figure 11:
The comparative Subscale performances of 5- and 6-year-old boys and girls
125
Developmental
Sub-quotients
120
Girls (5-years-old)
Boys (5-years-old)
Girls (6 years old)
Boys (6 years-old)
115
110
105
100
95
GQ
AQ
BQ
CQ
DQ
EQ
FQ
Subscales
Table 17
Summary of the sample’s mean performance in terms of GQ and sub-quotients across the 5and 6-year-old age groups
GQ
AQ
BQ
CQ
DQ
EQ
FQ
5-years-old
Boys
Girls
116
116
121
118
118
122
122
121
107
109
108
108
118
118
6-years-old
Boys
Girls
117
114
121
117
113
110
120
119
111
111
116
110
119
117
127
Although no significant differences were found, the 6-year-old boys appeared to
obtain the highest mean GQ in the overall sample. In both age groups, the boys appeared to
perform better than the girls on the Locomotor Subscale (AQ). The 5-year-old boys
performed slightly better on the Language Subscale (CQ), with a one-point difference
separating their mean score from the 5-year-old girls’ score. Both the 6-year-old boys and
girls obtained the highest mean performance across the sample on the Eye and Hand Coordination Subscale (DQ). The 6-year-old boys appeared to obtain the highest mean
performance on the Performance Subscale (EQ) and only performed slightly better than the
rest of the sample on the Practical Reasoning Subscale (FQ). The 5-year-old girls appeared to
perform better than the rest of the sample on the Personal-Social Subscale (BQ). Figure 11
illustrates that the sample as whole performed strongest on the Personal-Social (BQ),
Language (CQ) and Locomotor (AQ) Subscales, and their weakest performance relative to the
other Subscales was on the Eye and Hand Co-ordination (DQ) and Performance (EQ)
Subscales. The genders’ performance across the six Subscales will now be discussed.
6.5.1
Locomotor Subscale
Whilst not being statistically significant, it was noted in Figure 11 that the boys in
both age groups performed better than the girls on the Locomotor Subscale. Both 5- and 6year-old boys displayed superior performance on this Subscale (Xˉ AQ = 121). The 6-year-old
girls obtained the lowest sub-quotient on this Subscale within the sample. It is generally
accepted that developmental gender differences exist in gross-motor skills. On tasks related to
muscular strength, pre-school boys perform significantly better than girls, such as ball
throwing speed and throwing distance (Blakemore et al., 2009). In accordance, Van Rooyen
(2005) found that the boys in his sample obtained a higher sub-quotient than the girls on the
Locomotor Subscale of the GMDS-ER. Although it was not significantly different, he found
that the boys performed within the superior range. Furthermore, Knoesen (2003) also found
that the boys in her sample performed better than the girls on the Locomotor Subscale of the
Revised Griffiths Scales. Knoesen (2003) did not test whether the differences were
significant. The results presented above support the findings of the present study that boys
perform better on gross-motor skills and activities.
Studies investigating the influence of gender on the original Griffiths Scales add
additional support for the observed difference noted on this Subscale favouring boys. Allan
(1988) also found that the 5-year-old boys in her sample obtained superior performance on the
Locomotor Subscale. Similarly, Ward (1997) found a difference in favour of boys on the
128
Locomotor Subscale, in which superior performance was obtained. Both findings were merely
descriptive, and thus non-significant. Following the same trend, superior performance was
noted in the findings of the present study when analysing the boys’ performance within the
sample. In contrast with the above findings, Tukulu (1996) found that the girls in her sample
obtained a higher sub-quotient on this Subscale, which was in the average range.
Despite the fact that the above findings support the descriptive gender difference noted
on this Subscale in the present study, it should be emphasized that these differences did not
reach the required level of significance. Consequently, it can be concluded that the
performance of the boys and girls on the Locomotor Subscale was essentially similar in this
study.
6.5.2
Personal-Social Subscale
On this particular Subscale, Figure 11 illustrates that the 5-year-old girls obtained the
highest sub-quotient within the overall sample (Xˉ BQ = 122), which was within the superior
range, yet not significantly different in comparison to the 5-year-old boys. The 6-year-old
girls obtained the lowest sub-quotient in the sample, which was above average (Xˉ BQ = 110).
Van Rooyen (2005) found that the girls within his sample obtained a superior sub-quotient to
the boys on the GMDS-ER. Similarly, the girls within Knoesen’s (2003) study also performed
better than the boys on the Revised Griffiths Scales. In addition, Tukulu’s (1996) study on the
original Griffiths Scales revealed that the girls within her sample performed better than the
boys. All these studies support the findings obtained in the present study on the PersonalSocial Subscale.
However, three previous studies conducted on the original Griffiths Scales paint a
different picture. In Allan’s (1988) study, the boys obtained a higher sub-quotient on
Personal-Social Subscale when compared to the girls. In addition, Ward (1997) too found a
difference in favour of the boys on the Personal-Social Subscale. However, none of these
differences reached the required level of significance and were merely descriptive
observations noted by the respective researchers. In contrast, a significant gender difference
was found in Bhamjee’s (1991) study, with the girls obtaining a significantly higher subquotient than the boys on the Personal-Social Subscale.
Interestingly, whilst the 5-year-old girls in this sample performed the strongest on this
Subscale, the 6-year-old girls obtained the lowest sub-quotient, which was nonetheless above
average. Irrespective, an overview of the abovementioned South African studies indicates that
there is a clear trend in favour of girls when looking at performance between the gender
129
groups on the Personal-Social Subscale, which adds support to the findings obtained in the
present study. It is interesting that across the studies reviewed on the Griffiths Scales, it
appears that girls consistently perform better than boys on this Subscale. As a strong emphasis
is placed in the Personal-Social Subscale on the child’s ability to interact with peers, a
possible explanation for this gender difference could exist in the concept of gender roles and
“gender-typed styles of social interaction” (Ding & Littleton, 2005, p.170). Blatchford, Baines
and Pellegrini (2003) found that boys were more likely than girls to engage in fantasy play
and ball games, whereas girls were more likely to engage in conversation, drawing, reading,
and skipping. Thorne (1993) found that boys’ conversations revolve around competitive
discussions about strengths and physical ability in which any activity is turned into a contest.
As a result, they may experience more conflict in their social interactions with their peers.
Gender differences in aggression were documented in chapter two, which further illustrates
Thorne’s point about how quickly such competitive discussions can aggressively escalate.
“Studies of children’s friendships have revealed gender differences that seem to mirror gender
roles in society at large” (Ding & Littleton, 2005, p.171). In addition, gender roles are
influenced by assumptions that exist regarding the division of labour between men and
women, boys and girls, within the average household. For instance, it is assumed that boys
may be less interested in activities on the Personal-Social Subscale such as tying a bow-knot,
setting a table, and shampooing hair for instance, as it is not masculine or competitive enough.
On the other hand, it is assumed that girls may be more inclined to master these household
tasks in order to achieve a sense of competency and identity owing to the fact that it is
perceived as gender appropriate. For instance, setting a table and washing one’s hair may
interest a little girl far more because she sees that her mommy does it, whereas a little boy
may not see his daddy do it as often so he does not view this task through the same lens.
However, it is important for the reader to note the abovementioned examples provided, as
being assumptions. In addition, it must also be pointed out that these explanations provided
are purely speculative and in need of investigation.
Despite the fact that the above findings support the descriptive gender difference noted
on this Subscale in the present study, it should be emphasized that these differences did not
reach the required level of significance. Consequently, it can be concluded that the
performance of the boys and girls on the Personal-Social Subscale was essentially similar in
this study.
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6.5.3
Language Subscale
Figure 11 illustrates that the 5-year-old boys within this sample obtained the highest
sub-quotient (Xˉ CQ = 122) on the Language Subscale, which was within the superior range,
followed closely by the 5-year-old girls (Xˉ CQ = 121). The performance of the 6-year-old
group of boys and girls was essentially similar, with the boys (Xˉ CQ = 120) performing
slightly better than the girls (Xˉ CQ = 119). Whilst, none of these slight differences reached
statistical significance, it is interesting to note that the boys in both age groups were slightly
ahead of their female counterparts. Overall, it is evident that the sample performed very well
on this Subscale.
Research findings obtained on both the original Griffiths Scales and the GMDS-ER
conflict with the findings of the present study. On the GMDS-ER, Van Rooyen (2005) found
that the girls performed significantly better on the Language Subscale than the boys. On the
Revised Griffiths Scales, the girls in Knoesen’s (2003) study also obtained a higher subquotient than the boys on this Subscale, which was known as the Hearing and Speech
Subscale on this version of the Griffiths Scales. As mentioned, the differences found in
Knoesen’s (2003) study were not tested for significance. On the original Griffiths Scales, the
girls performed only slightly better than the boys (Allan, 1988; Tukulu, 1996). In Ward’s
(1997) study on the original Griffiths Scales, the girls performed significantly better than the
boys at the p ≥ 0.01 significance level. However, it is interesting to note that had the
significance level not been adjusted to p ≥ 0.01, the boys in Ward’s sample would have
performed significantly better than the girls on this Subscale at the p ≥ 0.05 level.
Nonetheless, this clear trend reflecting a female advantage in verbal ability was not observed
in the results of the present study.
Moore (1967) compared the GQ and CQ of boys and girls and found that girls
performed significantly better on the CQ as age increased. Yet, in the present study the 5year-old group obtained higher CQs than the 6-year-old group. In addition, a larger
percentage of children in the 5-year-old age group are from the lower socio-economic group
than in the 6-year-old age group, and a larger percentage of children in the 6-year-old age
group are from the middle-to-upper socio-economic group. In this instance, the results in the
present study contradict Moore’s (1967) findings.
Furthermore, as chapter two indicated gender differences in verbal ability have been
one of the ‘well-established’ facts of psychological research. To recap, Bornstein et al. (2004)
found that girls between the ages of two and six were consistently ahead of boys on almost all
of language development measures they were tested on, but not before or after. Hurlock
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(1981) asserted that boys’ sentences are shorter and less grammatically correct than girls at
every age, with smaller vocabularies and less accurate pronunciations. Also, McCarthy and
Kirk (1963) found that boys across all age levels were better than girls at visual coding.
In this study, there was only a one-point difference in scores between the boys and
girls in both age groups. Therefore, despite this slight (non-significant) difference observed,
the results on this Subscale are essentially comparable between the boys and girls. This
observation adds support to the gender similarities view in verbal ability discussed in chapter
two. In line with this view, several research studies yielded no evidence of a substantial
gender difference in verbal ability (Bjorklund, 1995; Feingold, 1988; Hedges & Nowell,
1995; Hyde, 1981; Hyde & Linn, 1988, Marsh, 1989; Plomin & Foch, 1981).
6.5.4
Eye and Hand Co-ordination Subscale
On the Eye and Hand Co-ordination Subscale, Figure 11 illustrates that both boys and
girls in the 6-year-old age group showed above average performance, and thus obtained the
joint highest sub-quotient. In the 5-year-old age group, the boys displayed average
performance and obtained the lowest sub-quotient on this Subscale. No significant differences
were found on the Eye and Hand Co-ordination Subscale.
Research findings obtained on both the original Griffiths Scales and the GMDS-ER
have obtained different findings. On the GMDS-ER, Van Rooyen (2005) found a significant
difference in his sample’s performance on this Subscale, with the girls performing
significantly better than the boys. On the Revised Griffiths Scales, Knoesen (2003) also found
that girls performed better than the boys, but could not comment on whether this difference
was significant.
This trend dates back to the studies conducted on the original Griffiths Scales, in
which girls were found to achieve higher sub-quotients than the boys, yet these differences
were not significant (Allan, 1988; Ward, 1997). Tukulu (1996) obtained similar findings and
remarked that “had the significance level not been adjusted, the girls would have performed
significantly better than the boys on Scale D (Eye and Hand Co-ordination)” (p.75). In none
of these studies reviewed, did the boys achieve the same sub-quotients as the girls. In this
regard, the findings of the present study challenge the studies documented above.
According to Blakemore et al. (2009), in assessments where children’s fine-motor
skills are assessed, girls are found to perform slightly better. Whilst, this was not observed in
the two 6-year-old gender groups, it was observed with the 5-year-old boys and girls where
the girls obtained a slightly higher sub-quotient than their male counterparts. The Eye and
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Hand Co-ordination Subscale also assesses a child’s visual-perceptual and perceptual-motor
skills as well as sensorimotor ability. As discussed in chapter two, Maccoby and Jacklin
(1974) found that gender differences were well-established in the area of visual-spatial ability.
A large body of research conducted over the last 25 years has revealed substantial gender
differences for some, but not all, of the measures that reflect visual-spatial information
processing (Halpern et al., 2007). Levine et al. (1999) concluded that gender differences in
favour of boys are present on spatial tasks by age 4 years 5 months. Conversely, these
findings are not corroborated by the results of the present study. In this study, the
performance of the 6-year-old boys and girls was parallel. Despite the fact that the
performance between the gender groups differed slightly in the 5-year-old age group, it was
non-significant and essentially similar.
Hyde (2005) reviewed the major meta-analyses that have been conducted on
psychological gender differences and included studies conducted on the visual-spatial abilities
conducted with children on areas of spatial relations, spatial perception, mental rotation,
spatial visualizations, and the progressive matrices. The effect sizes from these studies ranged
between close-to-zero to small. This adds additional support for the findings obtained by the
sample on this Subscale.
It should be emphasized that the differences observed between the 5-year-old boys and
girls on the Eye and Hand Co-ordination Subscale did not reach the required level of
significance. Consequently, it can be concluded that the performance of the boys and girls on
the Eye and Hand Co-ordination Subscale was essentially similar in this study when
compared to previous studies.
6.5.5
Performance Subscale
On this particular Subscale, Figure 11 illustrates that the 6-year-old boys obtained the
strongest performance, which was above average (Xˉ EQ = 116). This observed difference did
not reach the required level of significance, and consequently performance between the
gender groups on this Subscale was essentially similar in this study. The lowest sub-quotient
was shared between the 5-year-old boys and girls, with both showing average performances
(Xˉ EQ = 108).
In contrast, Van Rooyen (2005) found a significant difference on the Performance
Subscale of the GMDS-ER, where the girls performed better than the boys. On the Revised
Griffiths Scales, Knoesen (2003) found a difference on this Subscale showing a female
advantage, with significance not tested for as mentioned previously.
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This trend showing a female advantage on the Performance Subscale was also
apparent when reviewing findings of studies on the original Griffiths Scales, where girls
appeared to perform better than boys (Allan, 1988; Tukulu, 1996; Ward, 1997). Ward (1997)
stated that had the significance level not been adjusted in her study, the boys would have
performed significantly better on the Performance Subscale. It is interesting to note that in
some international studies, in which female superiority in visual-spatial skills during the preschool years has been documented, have shown that in subsequent years the gender difference
disappears and that the genders are equal until adolescence (Berry, 1966; Coates, 1974). The
above literature suggests that the female advantage Van Rooyen (2005) found in his study is
likely to disappear as the children advance in primary school.
Whilst not significant, it appears that the findings obtained in the present study go
against the grain when compared to other studies looking at the influence of gender on the
Griffiths Scales. As discussed in chapter two, Townes et al. (1980) found that boys are more
advanced in spatial and motor skills than girls. Boys are found to be more accurate than girls
at spatial tasks that measure accuracy of spatial transformations, and have obtained higher
scores on the Mazes subtest of the Wecshler Pre-school and Primary Scale of Intelligence
(Levine et al., 1999). The results presented above support these findings in the sense that
although non-significant, the 6-year-old boys performed better on this Subscale than the girls.
However, as mentioned, the fact that this difference was not significant means that
statistically the performance of boys and girls on the Performance Subscale was similar.
In line with the gender similarities view, Maccoby and Jacklin (1974) located several
studies in which visual-spatial ability has been studied in children, such as the spatial subtests
of the Differential Aptitudes Test and the Primary Mental Abilities Test, including mazes,
formboards and block counting. On the whole, they found no gender differences in these
measures in the early childhood and pre-school years. Brainerd and Vanden Huevel (1974)
also found no significant differences when they studied a sample of 120 children between the
ages of 5- and 6-years-old in which they had to choose two-dimensional drawings to represent
three-dimensional objects.
6.5.6
Practical Reasoning Subscale
On the Practical Reasoning Subscale, Figure 11 illustrates that the 6-year-old boys
obtained the highest sub-quotient and performed within the above average range (Xˉ FQ = 119),
followed closely by the boys and girls within the 5-year-old age group who obtained the same
sub-quotient (Xˉ FQ = 118). The 6-year-old girls also displayed above average performance,
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but obtained the lowest sub-quotient on this Subscale. It is important to emphasize that this
observed difference did not reach the required level of significance, and consequently
performance between the gender groups on this Subscale was essentially similar in this study.
In contrast, Van Rooyen (2005) found that girls performed significantly better than
boys on this Subscale. Similarly, Knoesen’s (2003) findings revealed a female advantage. On
the original Griffiths Scales, Allan (1988) found no significant gender difference on the
Practical Reasoning Subscale as the boys and girls in her sample showed the same results.
However, Tukulu (1996) found that girls performed slightly better than boys on this Subscale,
yet Ward (1997) found the opposite, in which boys were found to perform slightly better.
Although non-significant, the results of the present study support the findings obtained by
Ward (1997) that boys perform better on quantitative tasks as measured by the Practical
Reasoning Subscale.
As demonstrated by the various abovementioned findings on the Griffiths Scales, the
literature on gender differences also provides contradictory evidence. For instance, while
many researchers have found a male advantage when the mathematical concepts require more
reasoning and are more spatial in nature (Geary, 1996; Halpern et al., 2007; Hyde et al.,
1990), others have found that females have a clear advantage on quantitative tasks, but that
this reverses sometime before puberty where males then maintain their superior performance
into old age (Hyde et al., 1990; Neisser et al., 1996).
However, Hyde et al. (1990) conducted a meta-analysis of gender differences with
regard to performance in mathematics. This was based on 100 studies that provided effect
sizes for 254 separate samples and represented the testing of over three million people. Hyde
et al. (1990) concluded that there were no gender differences in understanding of
mathematical concepts and in problem solving in the early childhood years. Therefore, as the
results of the Hotellings T2 revealed no significant differences within this Subscale, the
findings obtained on this Subscale add support for the gender similarities viewpoint.
6.6
Chapter overview
This chapter provided the reader with the results of the present study. The aims of the
study were revisited at the beginning of the chapter to contextualise the findings. Before the
results of the descriptive statistics were provided in accordance with the first aim, results from
independent sample t-tests were presented and they revealed that the matched-pairs procedure
was implemented correctly.
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To achieve the first aim, results of the descriptive analyses were presented on the
mean developmental profile of the whole sample on the GMDS-ER, as well as a description
of the sample’s performance across the six Subscales. The mean developmental profiles of the
pre-school boys and girls per age group were then described separately. To achieve the second
aim, the results of the inferential analyses were presented in which the sample’s performance
was compared on the GMDS-ER. More specifically, the GQ of the whole sample was
compared as well as the GQ of the sample per age group to determine whether any significant
differences existed. The sample’s Subscale profiles were compared using a Hotellings T2. No
significant difference was found after administering the independent sample t-test and the
Hotellings T2.
Whilst no statistically significant differences were found between the boys and girls
within the sample, the researcher observed some interesting trends in the sample’s
performance in comparison with other studies looking at the influence of gender on
performance on the Griffiths Scales. It was found that 6-year-old boys obtained the highest
mean GQ in the overall sample. In both age groups, the boys appeared to perform better than
the girls on the Locomotor Subscale. The 5-year-old boys performed slightly better on the
Language Subscale. Both the 6-year-old boys and girls obtained the highest mean
performance across the sample on the Eye and Hand Co-ordination Subscale. The 6-year-old
boys obtained the highest mean performance on the Performance Subscale and only
performed slightly better than the rest of the sample on the Practical Reasoning Subscale. The
5-year-old girls performed better than the rest of the sample on the Personal-Social Subscale.
As discussed in chapter three, Griffiths’ (1954; 1970; 1984) theoretical view of child
development is consistent with contemporary child development theory such as Demetriou et
al.’s (2002) developmental model of information processing. Both theorists acknowledge the
influence physiological and socio-cultural factors have on development, and that these factors
are the cause of individual differences found in children’s intellectual abilities (Demetriou et
al., 2002; Griffiths, 1954). In this study age, socio-economic status and culture were identified
as factors that may have influenced the development of the boys and girls in this sample, and
were thus controlled for during the matched-pairs procedure discussed in chapter five. In
addition, Griffiths and Demetriou identified fairly similar domains of development and
Demetriou found that development often progresses unevenly across the domains (Griffiths,
1954; 1970; 1984; Demetriou et al., 2002; Demetriou & Raftapoulos, 2004). Accordingly, the
researcher noted variations in the test scores across gender and age group on the six Subscales
of the GMDS-ER, with the exception of the Eye and Hand Co-ordination Subscale in the 6-
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year-old age group. In conclusion, the utilization of the GMDS-ER enabled a comparison to
be made of the gender groups in the sample from a developmental perspective, thus filling a
void in gender-related research and setting it apart from previous studies that focused
narrowly on gender differences within verbal, visual-spatial and quantitative abilities.
The following chapter will integrate the findings of the present study by providing a
summary of the trends observed in the sample’s performance on the GMDS-ER as well as
allow the researcher to make concluding comments about the study. In addition, limitations
and recommendations for future studies will also be provided.
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CHAPTER SEVEN
CONCLUSIONS, LIMITATIONS AND RECOMMENDATIONS FOR FUTURE
RESEARCH
7.1
Introduction
This chapter presents the conclusions, limitations and recommendations of this study.
As the GMDS-ER was standardised for use in the United Kingdom, the current study not only
added to the growing body of knowledge regarding the possible developmental differences
between a sample of pre-school boys and girls aged between 5-years to 6-years-old, but also
contributed towards an understanding of how normal South African pre-school children in
this age group perform on the Griffiths Mental Development Scales-Extended Revised
(GMDS-ER). As more and more South African studies are conducted, it will be possible to
standardise and norm the GMDS-ER for this country. In light of this, the present study
provided a valuable contribution, as its findings along with many others will be added to the
GMDS-ER database, which will be used to generate norms for the South African context.
7.2
Conclusions
The overall purpose of this study was to generate comparative information regarding
the general development of 5- and 6-year-old South African pre-school boys and girls. In
order to achieve this, the study narrowed its focus to the city of Port Elizabeth and aimed to
explore and compare the developmental profiles of a sample of normal pre-school boys and
girls between the abovementioned age groups utilizing the GMDS-ER. Overall, the total
sample included 64 children, consisting of 32 pairs of boys and girls.
Results of the data analysis revealed that there were no significant differences between
the performance of the boys and girls within the two age groups. However, certain trends did
emerge from a qualitative review of the mean scores. It was noted that the 6-year-old boys
performed slightly better across the Subscales, and specifically on four of the six Subscales,
namely the Locomotor, Eye and Hand Co-ordination, Performance and Practical Reasoning
Subscales. The 5-year-old boys obtained the highest sub-quotient on the Language Subscale,
and the 5-year-old girls obtained the highest sub-quotient on the Personal-Social Subscale.
As no significant differences were found, it can be concluded that the developmental
profiles of this particular sample of pre-school boys and girls was essentially similar.
Furthermore, the fact that no gender differences were found indicates that the revision process
of the GMDS-ER was sensitive to not building in items that are gender biased (Foxcroft,
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personal communication, December 3, 2008). Many intelligence measures have ensured that
test items that have shown gender bias have been removed in the test construction process.
The GMDS-ER has also been careful in this regard, thereby ranking it favourably amongst
psychometric measures.
In chapter two, it was documented that there are two opposing perspectives with
regards to gender differences in development. As reflected, literature on the topic is fraught
with contradictory empirical evidence, which is understandable in the sense that the many
studies conducted differed with regards to methodologies employed and sample sizes used.
Ideally, had the studies been replicated as closely as possible to the earliest studies from the
1960s, the differing findings may have proved easier to follow in a literature review on this
topic. In this regard, meta-analyses have enabled valuable deductions to be made in this area
due to their ability to condense the findings from many studies (Blakemore et al., 2009).
However, it is disappointing that very few studies have assessed whether gender differences
exist from a holistic developmental perspective. Historically, the majority of the studies
shown in the literature review focused on the psychometric conception of intelligence at the
time, which was shaped by verbal, quantitative and visual-spatial ability (Deaux, 1984;
Fennema & Sherman, 1977; Geary, 1989; 1994; 1996; Halpern, 1986; 1989; 1997; Halpern et
al., 2007; Linn & Peterson, 1985; Maccoby & Jacklin, 1974; Naglieri & Rojahn, 2001; Voyer,
Voyer & Bryden, 1995).
Information generated from this study has made a valuable contribution to the field of
child and gender development research in South Africa. It is one of the first studies conducted
in this country that has comprehensively investigated whether boys and girls differ in their
performance on the recently released GMDS-ER. When it comes to developmental measures,
the Griffiths Scales is well-established psychometrically in its holistic view of child
development and is useful in detecting developmental difficulties in early childhood. The
recently released GMDS-ER is the latest offering of the Scales and it continues the rich
tradition of being a valuable diagnostic aid to practitioners with its new normative and
technical properties. Thus, the GMDS-ER was considered to be the most appropriate
developmental measure to guide the researcher with the comparison of the performance of the
boys and girls within the present study.
The limitations that were encountered in the present study are acknowledged in the
following section. It is hoped that future researchers will peruse the following section to
enable them to make the necessary improvements, and thereby further add to the growing
body of knowledge on the topic.
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7.3
Limitations
Limitations are inherent in all research studies. The limitations found in this study will
be discussed in this section, as it serves to benefit future research conducted on child
development using the GMDS-ER.
7.3.1
Limitations of the research method
The research method employed in the present study was exploratory-descriptive.
When using exploratory research, it is not possible to predict or explain behaviour via the
manipulation and measurement of different variables (Knoesen, 2003). As a result,
conclusions regarding causal relationships cannot be made. It needs to be pointed out that it
was never the intention of the study to make cause-and-effect conclusions regarding the
developmental progression of boys and girls, but merely to examine and describe the
developmental profiles of the gender groups, to determine whether any differences exist.
Therefore, in view of this purpose of the study, this limitation was contained.
7.3.2
Limitations of the sampling procedure
The researcher through the use of non-probability, purposive and convenience
sampling chose the participants for this study. In non-probability sampling, the probability of
any particular member of the population being chosen is unknown, and the selection of the
sample is arbitrary as the researcher plays an active role in the selection of the sample to best
suit the aims of the study (Struwig & Stead, 2001). As a result, the researcher’s ability to
generalise the findings of the study beyond the sample to the larger population is severely
limited. However, due to the fact that the research method was exploratory-descriptive, it was
not the intention of the present study to generalise the findings to the general population of
South African boys and girls within the 5- and 6-year-old age group.
In the present study, it was essential that the extraneous variables of socio-economic
status and cultural group were controlled for in order to obtain a meaningful interpretation of
the test results. As a result, it is reasonable to expect that the findings of this study were
mostly due to the non-manipulated independent variable of gender and not due to the
influence of uncontrolled extraneous variables. Therefore, the internal validity of this study
has been maintained.
Another limitation within this study was that the majority of the sample consisted of
White children, with a smaller number of children from the Coloured and Asian cultural
groups due to the English language inclusion criterion. As the GMDS-ER has not been
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standardised into other languages as yet, this could not have been prevented. However, it is
interesting to note that in a previous research study conducted by Allan (1992) on the original
Griffiths Scales, no significant differences were found between the cultural groups with
regards to their overall performance on the General Quotient, Personal-Social and Practical
Reasoning Subscale. On the remaining four subscales, no significant differences were found
between the performances of the Black and Coloured children, as with White and Asian
children. White children were found to perform significantly better on the Hearing and
Speech Subscale (currently termed ‘Language Subscale’ on the GMDS-ER). When the
GMDS-ER becomes normed and standardised for the South African population, it is hoped
that it will also be translated into other languages, making it accessible to all South African
children. Further studies conducted on the performance of children from these different
cultural groups will also contribute towards the growing knowledge base of child
development in South Africa.
7.3.3
Limitations regarding various test administrators utilized in the study
Ideally, one test administrator should assess all participants and score all test protocols
to obtain a standardised procedure. However, due to the time consuming process it entails,
this was not feasible for the present study. Therefore, various test administrators were used to
assess the participants. According to Stewart (2005), “this increases the chances of inter-tester
variance in the administration and scoring of items” (p.416). This variance was contained to a
certain extent by having the same moderator evaluate all test protocols. In addition, the
supervisors of the study scrutinised the scoring and interpretations of the test protocols so that
accurate information could be reported on. Furthermore, the test administrators were all
trained by the same registered Griffiths tutor.
7.3.4
Limitations regarding the lack of norms for the South African population on the
GMDS-ER
As the GMDS-ER has not been standardised for use in South Africa, the norms
developed in the United Kingdom were not used in this study. Instead, the scores obtained
were used in a criterion-referenced way by converting them to quotients based on the child’s
chronological age. As mentioned in chapter five, this scoring system was used for the original
Griffiths Scales, and appeared to be the most appropriate method to use in the GMDS-ER
assessment of South African children. The lack of South African norms serves as a limitation
within this study because it was not possible to ascertain the samples’ performance relative to
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their South African peers. This would have been an added advantage when analysing the
findings of this study. However, this limitation is being addressed as there is an ongoing
research project currently underway involving the testing of clinical as well as normal
samples of children on the GMDS-ER. It is hoped that the findings from studies such as these
will contribute towards the norming and standardisation of the GMDS-ER in South Africa.
7.4
Recommendations for future research
With the abovementioned limitations in mind, the following recommendations for
future research were made:
1. The present study should be replicated with a larger, more representative sample
within the Nelson Mandela Metropole. A large-scale comparison would generate
valuable information on child development, such as the development of normative
typologies per age group contributing towards the creation of South African norms on
the GMDS-ER. An additional advantage to having a larger sample is that it would
thoroughly investigate whether gender bias has been eliminated from the construction
of the GMDS-ER.
2. Due to the limited representation of children from the Black and Asian cultural groups
in the present study, further investigation comparing the genders within these cultural
groups should be undertaken. In this regard, future studies should focus on translating
the items of the GMDS-ER into other languages to enable the abovementioned
recommended studies to be conducted in a fair and ethical manner. Also, test
administrators should be fluent in the mother tongue of the child.
3.
There is a need for the adjustment of Riordan’s (1978) socio-economic classification
system, as it is fairly dated. The aspect of this system that is the most dated is the
classification categories for the different cultural groups. A socio-economic
classification system for a contemporary South African population ought to
incorporate factors such as household type, household composition, education level,
work status and access to water, to enable a holistic conceptualisation of socioeconomic status (Potgieter et al., 1999). Thus, the concept of socio-economic status in
the South African context needs to be reviewed as several classification systems are
inclined to adopt the Westernised perspective, which focuses mostly on level of
education and income. In a third world country, environmental and contextual factors
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influence a family’s socio-economic standing and thus needs to be considered when
conceptualising socio-economic status.
4. Finally, it is highly recommended that continued research using the GMDS-ER in
South Africa should be conducted. This has become a crucial necessity in the South
African context as it plays a fundamental role in the early identification of problems,
and therefore a set of norms applicable to our context is required. Continued research
will contribute to the generation of South African norms for the GMDS-ER so that this
assessment measure can be classified by the Psychometrics Committee of the
Professional Board for Psychology of the Health Professions Council of South Africa
(HPCSA) as a diagnostic developmental measure for use in this country.
7.5
Chapter overview
This chapter provided the reader with the conclusions of the study; as well as an
understanding of the limitations encountered in order to facilitate improvements for future
research, and also provided recommendations for those wishing to further their interest in this
topic. To recap, it was concluded that no significant differences were found between the
overall performance of the boys and girls in this study. Therefore, the conclusions support the
gender similarities viewpoint. This study not only contributed immensely to the growing body
of knowledge regarding the performance of the gender groups on the GMDS-ER, but also
towards an understanding of how normal South African pre-school children in this age group
perform on the GMDS-ER.
Childhood is a fascinating world of discovery, which children actively explore by
formulating ideas and testing hypotheses. In a sense perhaps their natural curiosity should be
respected as something akin to mini research. In this exploration children think and behave in
ways that are both amusing as well as thought provoking (Craig, 1996). The following
quotation by Hymes Jr. (2006) perfectly elucidates the value of recognising the importance of
play in child development.
Play for young children is not recreation activity...It is not leisure-time activity nor
escape activity.... Play is thinking time for young children. It is language time.
Problem-solving time. It is memory time, planning time, investigating time. It is
organization-of-ideas time, when the young child uses his mind and body and his
social skills and all his powers in response to the stimuli he has met (Retrieved online
December 10, 2008, http://www.enotes.com/famous-quotes/play-for-young-childrenis-not-recreation-activity).
143
The GMDS-ER holds the key that unlocks the door to the young child’s world, and
endears itself to children due to its playful character. One of the values of the GMDS-ER is
that it is based on the concept of play, which is a universal behaviour across all cultures. It is
this researcher’s opinion that the GMDS-ER can be considered to be an essential
developmental assessment measure for the multi-cultural South African context.
144
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169
APPENDIX A
NELSON MANDELA METROPOLITAN UNIVERSITY
INFORMATION AND INFORMED CONSENT FORM
Title of the
research
project
Principal
Investigator
Address
Postal Code
Contact
telephone
number
Comparing the Development of a Sample of South
African Preschool Boys and Girls Utilizing the Griffiths
Mental Development Scales-Extended Revised
Tamarin Jakins
Psychology Department, Faculty of Health Sciences
Nelson Mandela Metropolitan University South Campus
P.O. Box 77000
Port Elizabeth
6031
(041) 504 2330
A.
DECLARATION BY OR ON BEHALF OF PARTICIPANT
(Person legally competent to give consent on behalf of the participant)
I, the undersigned
I.D. number
(Full Name)
in my capacity as parent / guardian
of the participant
I.D. number
Address (of participant)
(Child’s Full Name)
Initial
170
A.1.
I HEREBY CONFIRM AS FOLLOWS:
Initial
1.
The participant was invited to participate in the above-mentioned
research project that is being undertaken by Ms. Tamarin Jakins of the
Department of Psychology, in the Faculty of Health Sciences of the
Nelson Mandela Metropolitan University.
2. The following aspects have been explained to me, the representative
Initial
of the participant:
Aim: The investigator is studying the developmental profiles of a sample of
normal South African preschool boys and girls (5 and 6 years old).
The information will be used:
-
to contribute to the completion of a Masters research project;
-
to contribute to research on the development between the genders
within a South African context on the Griffiths Mental Development
Scales-Extended Revised.
Procedures:
Initial
I understand that my child will be participating in an approximate two hour
assessment in which the Griffiths Mental Development Scales-Extended
Revised will be administered.
Risks: None
Initial
Possible Benefits:
Initial
As a result of my child’s participation in this study, I will be informed of
any developmental concerns which he or she is experiencing and will have
the opportunity to assess them further.
Confidentiality:
Initial
My child’s identity will not be revealed in any discussion, description or
scientific publications by the investigator.
Access to findings:
Any new information/or benefit that develops during the course of the study
will be shared as follows:
-
in the form of an individual report for each child disseminating their
assessment results and developmental profile.
Initial
171
-
general report of the overall results of the research project.
Initial
Voluntary participation/ refusal/ discontinuation:
My child’s participation is voluntary
YES
NO
My decision whether or not to participate will in no way affect my present
or future care/ employment/
TRUE
lifestyle
FALSE
3. The information above was explained to me, the parent / guardian of the
Initial
participant by : _________________________ (Name of relevant person)
in Afrikaans / English / Xhosa / Other ___________________
and I am in command of this language / it was satisfactorily translated to
me by ______________________ (Name of translator)
I was given the opportunity to ask questions and all these questions were
answered satisfactorily.
4. No pressure was exerted on me to consent to participation and I
Initial
understand that I may withdraw at any stage without penalisation.
5. Participation in this study will not result in any additional cost to myself.
A.2 I HEREBY VOLUNTARILY CONSENT TO PARTICIPATE IN THE
ABOVE-MENTIONED PROJECT
Signed/confirmed at
on
Signature of witness
Signature parent / guardian
Full name of witness
2008
172
B.
STATEMENT BY OR ON BEHALF OF INVESTIGATOR
I, Tamarin Jakins, declare that
-
I have explained the information given in this document to
(name of participant)
and/or his/her parent / guardian
(name of parent/ guardian)
-
he/she was encouraged and given ample time to ask me any questions;
-
this conversation was conducted in Afrikaans / English / Xhosa / Other
and no translator was used / this conversation was translated into
(language)
-
by
I have detached Section C and handed it to the participant
YES
Signed/confirmed at
on
Signature of witness
Signature of interviewer
Full name of witness
NO
2008
173
C.
IMPORTANT MESSAGE TO REPRESENTATIVE OF PARTICIPANT
Dear representative of the participant
Thank you for allowing your child to participate in my study. Should, at any time during the
study:
-
an emergency arise as a result of the research, or
you require any further information with regard to the study, or
any of the following occur:
- The participant needs to terminate participation or
- The participant is unable to attend a scheduled appointment
(indicate any circumstances which should be reported to the investigator)
Kindly contact
at telephone number
Tamarin Jakins
(041) 504 2330
174
APPENDIX B
Dear Principal
Date
Participation in a research study conducted by the Department of Psychology,
Nelson Mandela Metropolitan University
As per our telephonic discussion, my name is Tamarin Jakins and I am currently completing
my Masters Degree in Counselling Psychology at the Nelson Mandela Metropolitan
University.
A large component of the degree entails conducting a research project. The purpose of this
study is to generate comparative information regarding the general development of a sample
of South African pre-school boys and girls, between the ages of 5 and 6 years old, utilizing
the Griffiths Mental Development Scales-Extended Revised (GMDS-ER). The six areas of
general development that are measured on the subscales of the GMDS-ER include:
Locomotor, Personal-Social, Language, Eye-Hand Co-ordination, Performance and Practical
Reasoning.
The original Griffiths Scales were developed in Britain in the 1960s and are used
internationally for the developmental assessment of young children between the ages of 2 and
8 years old. A research team based at the Psychology Department of the Nelson Mandela
Metropolitan University have recently revised the Scales, making them more culture fair. The
Scales provide the researcher with a General Quotient (GQ) and an age equivalent, which
provides an indication of the child’s overall development.
Participants will be asked to complete tasks that are age appropriate and based on the concept
of play. Examples of tasks include: threading beads, naming objects seen in a picture, kicking
a ball, tying a knot and drawing. Please remain assured that the children participating in the
study will be free to refuse or withdraw at any stage of the assessment and will be informed of
this.
175
The administrators of the assessment will consist of Psychologists, Intern Psychologists and
Psychologists-in-Training, who have undergone training in the GMDS-ER. The assessment
could take approximately two hours for each child and will preferably take place at the
University Psychology Clinic (UCLIN). However, alternative arrangements can be made if
necessary. A brief feedback session, in addition to an individual report, will be provided to the
parents. Upon receiving the results, should further assessment be required, it will be arranged
through UCLIN. In addition, feedback regarding the overall findings of the research project
will be provided to the parents and principals of the participating preschools in the form of a
comprehensive letter.
Prior to commencement of the research, I hereby request your permission to allow children at
your pre-school, in the 5- and 6-year-old age group, to participate in the study. The
information and assessment results obtained will be treated as strictly confidential. Attached
please find a copy of the Covering letter, Biographical Questionnaire and the Informed
Consent Form to be completed by the parents and/or guardians of the participants in the
study. Please note that if parents do not wish their child to participate, they are not under any
obligation and can indicate this on the consent form.
Should you require any further information regarding the research project, please do not
hesitate to contact me at UCLIN on (041) 504 2330, or by e-mail at
[email protected].
I would like to stress that the success of this project depends entirely on your voluntary cooperation and I thank you in advance for your interest.
Yours Sincerely,
_______________
Ms. Tamarin Jakins
Intern Counselling Psychologist
______________
_________________
Dr. Louise Stroud
Prof. Cheryl Foxcroft
Supervisor
Co-supervisor
176
APPENDIX C
Dear Parent / Guardian
Date
Participation in a research study conducted by the Department of Psychology,
Nelson Mandela Metropolitan University
As per our telephonic discussion, my name is Tamarin Jakins and I am currently completing
my Masters Degree in Counselling Psychology at the Nelson Mandela Metropolitan
University.
A large component of the degree entails conducting a research project. The purpose of this
study is to generate comparative information regarding the general development of a sample
of South African pre-school boys and girls, between the ages of 5 and 6 years old, utilizing
the Griffiths Mental Development Scales-Extended Revised (GMDS-ER). The six areas of
general development that are measured on the subscales of the GMDS-ER include:
Locomotor, Personal-Social, Language, Eye-Hand Co-ordination, Performance and Practical
Reasoning.
The original Griffiths Scales were developed in Britain in the 1960s and are used
internationally for the developmental assessment of young children between the ages of 2 and
8 years old. A research team based at the Psychology Department of the Nelson Mandela
Metropolitan University have recently revised the Scales, making them more culture fair. The
Scales provide the researcher with a General Quotient (GQ) and an age equivalent, which
provides an indication of the child’s overall development.
Participants will be asked to complete tasks that are age appropriate and based on the concept
of play. Examples of tasks include: threading beads, naming objects seen in a picture, kicking
a ball, tying a knot and drawing. Please remain assured that your child will be free to refuse or
withdraw at any stage of the assessment and will be informed of this.
177
The administrators of the assessment will consist of Psychologists, Intern Psychologists and
Psychologists-in-Training, who have undergone training in the GMDS-ER. The assessment
could take approximately two hours for each child and will preferably take place at the
University Psychology Clinic (UCLIN). However, alternative arrangements can be made if
necessary. A brief feedback session, in addition to an individual report, will be provided.
Upon receiving the results, should further assessment be required, it will be arranged through
UCLIN.
Prior to commencement of the research, I hereby request your permission to allow your child
to participate. It is kindly requested that you complete the attached Biographical
Questionnaire and Information and Informed Consent Form. Upon completion, it would
be greatly appreciated if you could enclose the completed documents in the provided pre-paid
and addressed envelope and return it to me as soon as possible. The information and
assessment results obtained will be treated as strictly confidential. Please note that if you do
not wish your child to participate in the project, you may indicate this on the consent form.
Should you require any further information regarding the research project, please do not
hesitate to contact me at UCLIN on (041) 504 2330, or by e-mail at
[email protected].
I would like to stress that the success of this project depends entirely on your voluntary cooperation and I thank you in advance for your interest.
Yours Sincerely,
___________________
Ms. Tamarin Jakins
Intern Counselling Psychologist
__________________
_________________
Dr. Louise Stroud
Prof. Cheryl Foxcroft
Supervisor
Co-supervisor
178
APPENDIX D
BIOGRAPHICAL QUESTIONNAIRE
SECTION A
PERSONAL DETAILS
Child’s name and surname:_______________________________________________
Address:
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
Suburb: ___________________________________
Telephone number: __________________________
Date of Birth: _______/_______/_______
Gender:
M
F
Race/Cultural Group:
Black Coloured Asian
White
Current Pre-school/School: ___________________________________
Pre-school/School Telephone No: ______________________________
Home language: ____________________
Has your child been diagnosed with a mental and/or physical disorder? If yes, please specify.
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
Breadwinner’s/Guardian’s Occupation: ___________________________________
Breadwinner’s/Guardian’s Educational Level: (Please tick the highest level achieved)
None
Primary School
Junior Certificate
Apprenticeship
Matric Certificate (standard 10/ grade12)
Further Training (not at University)
179
University degree or diploma
SECTION B
1. Birth History:
Please describe anything unusual about the pregnancy or delivery:
___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
____________________
Please tick the appropriate answer (Y = Yes, N = No):
2
3
4
5
6
7
8
Was your pregnancy planned?
Did you give birth to your child naturally?
Was your child anoxic (i.e. did he/she lack oxygen at birth)?
Was your child born prematurely or after more than 41 weeks of
pregnancy? Length of pregnancy:……………………....months
Did you bond easily with your child?
Did you breast-feed your child?
Did you experience postpartum depression?
Motor Development
9
At what age did your child Sit:……………………….. months
Crawl: ……………………..months
Walk:………………………months
10
Is your child extremely under active?
11
Is your child noticeably physically overactive?
12
Is your child clumsy?
Language Development
13
Did your child have difficulty with sucking and chewing?
14
At what age did your child start to babble? ………………(months)
15
Does your child use single words? If yes, at what age? ……….(months)
16
Does your child speak in sentences? If yes, at what age? ………..(years)
17
Does your child ask repetitive questions?
18
Does your child talk to him/herself excessively?
19
Does your child echo words or phrases constantly?
Emotional Development
20
Does your child cry or laugh for no reason?
21
Does your child prefer to be alone?
22
Does your child enjoy cuddling and respond to affection?
23
Does your child have temper tantrums regularly?
24
Does your child display extreme distress for no apparent reason?
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
180
Social Development
25
Does your child have difficulty in mixing with other children?
26
Does your child make little or no eye contact?
27
Does your child form inappropriate attachment to certain objects?
Sensory / Hearing Development
28
Does your child appear as if he / she does not hear you?
29
Does your child cover his/her ears?
30
Is your child upset by noises?
General
31
Is your child on any kind of medication? If yes, for what?
………………………………………………………………………..
32
Does your child stutter?
33
Does your child faint frequently?
34
Does your child bite his / her nails excessively?
35
Hs your child ever had any childhood diseases?
(If yes, please list all childhood diseases and the ages at which they
occurred)
………………………………………………………………..Age…...…
………………………………………………………………..Age….......
..................................................................................................Age…...…
………………………………………………………………..Age…...…
………………………………………………………………..Age……...
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
SECTION C
The following questions are applicable to children of a broad age range; therefore, we do not
necessarily expect your child to be capable of the tasks listed below. We would appreciate a
completely honest evaluation of your child’s ability. Please do not be concerned if your child
is not yet able to complete each of the activities.
1. Does your child help with small household tasks?
2. Does your child help with routine tasks when requested?
3. Does your child help tidy a room?
4. Does your child bath or shower with minimal assistance?
5. Does your child clean his / her own teeth?
6. Does your child wash his / her own hands and face but needs assistance with
drying?
7. Does your child wash and dry his / her own hands and face but needs
checking?
8. Does your child wash and dry his / her own hands and face without
assistance?
9. Does your child need some assistance to bath or shower?
10. Does your child bath or shower without assistance?
11. Does your child bath or shower, and dry him / herself without assistance?
12 Does your child need assistance to put on his / her own shoes and socks,
e.g. putting shoes on correct feet?
13. Does your child put on his / her own shoes and socks without assistance?
14. Does your child choose his / her own clothes?
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
181
15. Does your child deliver a simple message?
16. Does your child go on instruction to get a specific item in a public area,
e.g. go and get bread from the counter and bring it to mother?
17. Does your child go alone on errands to nearby shops, etc.?
18. Does your child make a small purchase in a shop with some assistance, e.g.
checking the change?
19. Does your child make a small purchase in a shop without assistance?
20. Does your child demonstrate an understanding that it is unsafe to accept
rides, foods or money from a stranger?
21. Does your child need to be reminded to follow the rules in a simple game?
22. Does your child follow a rule in a simple game, without being reminded?
23. Does your child neaten (brush or comb) own hair in the morning?
24. Does your child ask to use the toilet?
25. Does your child have bladder control during the day, with a few accidents?
26. Does your child have complete bladder control during the day and night?
27. Does your child get a drink of water from the tap without your assistance?
28. Does your child get a drink of water from the tap with some assistance?
29. Does your child eat without assistance?
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Y/N
Thank you for your co-operation in filling in this Questionnaire. All the information that you
have supplied us with will be treated as strictly confidential.
182
APPENDIX E
CONFIDENTIAL REPORT
Mr. and Mrs. Surname
Address
Port Elizabeth
6001
Date
Dear Mr. and Mrs. Surname
DEVELOPMENTAL ASSESSMENT OF CHILD
Thank you for allowing Child to participate in the study utilizing the Griffiths Mental
Development Scales-Extended Revised (GMDS-ER), on exploring and comparing the
development of a sample of South African preschool boys and girls.
The GMDS-ER assesses the mental development of young children from two to eight years
by measuring the development and maturation of a child’s attributes and abilities across six
different avenues of learning, namely a) Gross Motor/ Locomotor, b) Personal-Social, c)
Language, d) Eye Hand Co-ordination, e) Performance, and f) Practical Reasoning skills and
abilities.
BIOGRAPHICAL DETAILS
Name
:
Gender
:
Date of Assessment
:
Date of Birth
:
Age at time of assessment
:
School
:
Child’s scores on the GMDS-ER provide an estimate of his / her developmental level and are
a reflection of his / her performance on the day, at that time.
183
RESULTS OF THE ASSESSMENT
Subscale
Locomotor Skills:
This scale assesses gross motor skills including the
ability to balance, co-ordinate and control
movements.
Examples: the ability to run fast outdoors, bounce
and catch a ball, hop on one foot etc.
Personal-Social Development:
This scale assesses proficiency in the activities of
daily living, independence and an ability to interact
with other children.
Examples: the ability to give a home address, to
fasten shoe buckle and eat with knife and fork etc.
Language:
This scale assesses verbal ability, the
understanding of the meaning of words and the
ability to use language effectively (receptive and
expressive language).
Examples: naming colours, relating a story about a
given picture and repeating 6-16 syllable sentences
etc.
Eye and Hand Co-ordination:
This scale assesses fine-motor skills and relates to
visual abilities with handwork.
Examples: drawing, writing, threading beads and
cutting with scissors etc.
Practical Skills:
This scale assesses manipulation skills including
speed of working and precision.
Examples: working with form boards of 4,6 and 11
shapes; building blocks to resemble given patterns.
Practical Reasoning:
This scale assesses problem-solving ability, basic
mathematical comprehension and moral reasoning.
It indicates the child’s ability to benefit from formal
schooling.
Examples: memory recall and repetition of 1 to 5
digits, picture arrangements of cards to tell a story,
visual memory etc.
Mental Age
Category of
(in months)
Performance
Above/Below
age (in
months)
184
GENERAL DEVELOPMENT
Child’s mental age of ? years and ? month (? months) indicates that his/her general developmental
functioning, as measured on the Griffiths Mental Development Scales-Extended Revised, is ? months above
/ below his chronological age. Based on the overall performance, Child’s performance can be described as
being below average / average / above average / superior.
RECOMMENDATIONS
1.
The results presented above are based on an hour and a half assessment. It is
possible that your observations of Child may be different to the ones made by myself
during this assessment. Please keep this in mind when reading this report and
consider that the recommendations are based on the observations made during the
assessment session.
2.
As suggested to all participants in the study, it is recommended that Child’s sight and
hearing is assessed to ensure that these senses are functioning at their full potential.
This recommendation should only be followed if Child has not yet had these
assessments.
3.
Child performed lower on the Practical Reasoning subscale than the other five
subscales. Performance on this subscale can be improved by encouraging him or her
to complete tasks that will stimulate his or her practical reasoning and numerical
abilities, such as:
•
Learning mathematical concepts such as counting by using buttons, lids of
bottles etc.
•
Learning the names of money (coins)
•
Learning the difference between ‘morning’ and ‘afternoon’
I trust you will find this information useful. Should you require any further information, please
do not hesitate to contact me at the Psychology Clinic (UCLIN) on (041) 504 2330.
Yours Sincerely,
Ms. Tamarin Jakins
Dr. Louise Stroud
Test Administrator / Principal Researcher
Research Supervisor
Intern Counselling Psychologist
Clinical Psychologist