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Qualitative Data Analysis with ATLAS.ti 7 Windows
Language of Instruction: English
Instructor: Ricardo B. Contreras, PhD, applied anthropologist. Director of ATLAS.ti
Training and Partnership Development.
Requirements: Basic knowledge of Windows and a personal computer with ATLAS.ti
installed (demo or full version 7.5 preferred).
Duration: 14 hours.
Introduction
In this workshop, we teach the key functions of ATLAS.ti emphasizing data integration,
organization, and systematic documentation of the analysis process. The teaching
methodology combines lecturing and hands-on work with sample source documents
provided by the instructor. Teaching will be interactive. Participants will be given a set
of supplementary learning material.
Note: Although this outline lists the class contents in a lineal way, in class they will be
taught iteratively, making an effort to integrate as much as possible the different tools
that the software provides.
Learning Objectives
1. Participants will learn about the methodological principles behind ATLAS.ti.
2. Participants will learn the fundamental functions of ATLAS.ti for data
description, exploration, analysis, and interpretation.
3. Participants will learn to use ATLAS.ti following an approach emphasizing
function integration, data organization, and documentation.
Methodology
The teaching methodology combines lecturing with hands-on work. In the first hour and
a half, the instructor will introduce ATLAS.ti, including a description and explanation of
the hermeneutic unit, the central concept of the ATLAS.ti structure. Following,
participants will create a hermeneutic unit and practice the different functions that the
instructor will teach. Teaching will be highly interactive.
Outline
Day 1
I. Introduction to ATLAS.ti 1.
Conceptual introduction a.
The universals of qualitative methodology b.
ATLAS.ti as a tool of data transformation c.
Integration of data description, analysis, and interpretation d.
The role of software in qualitative data analysis 2.
The hermeneutic unit ATLAS.ti 7 Windows Seminars 1 a.
b.
What is the hermeneutic unit? The objects of the hermeneutic unit II. Setting up the Hermeneutic Unit 1.
Creating the hermeneutic unit a.
Saving the hermeneutic unit file in the right folder in Windows. b.
Naming the hermeneutic unit. 2.
Adding and loading primary documents a.
Adding source documents to the individual library (individual work) or the team library (team work). Implications of accessing source documents in this way. b.
Accessing primary documents in the Primary Document Manager c.
Commenting on primary documents. d.
Accessing primary documents through the side panels. e.
Loading up to four primary documents at a time. Applications. 3.
Organizing primary documents into families a.
Thinking about the study attributes that allow to compare findings across cases (e.g., demographics, data collection sites, data collection waves). b.
Creating primary document families. c.
Commenting on primary document families. d.
Examining primary document families in a network view. e.
Applications of primary document families. 4.
Creating memos a.
Definition b.
Types III. Segmenting the Text a. Reading a document and selecting segments of the text b. Reading the resulting quotations c. Commenting quotations d. Renaming quotations if necessary e. Integrating memo writing into data segmentation IV. Coding 1. Creating a deductive coding structure (codebook) from research objectives or systems of hypotheses a.
Incorporating codes into the HU: •
One code at a time. •
All codes at once using the Memo Manager. b.
Writing operational definitions on each code. 2.
Organizing the system of codes a.
Using prefixes to group codes according to shared characteristics. b.
Using colors to distinguish codes across categories. c.
Grouping codes into code families. 3.
Coding by list a.
Coding by list using the right-‐click strategy. b. Coding by list using the Code Manager strategy. c.
Coding by list using the short-‐cut menu strategy. d.
Coding using the Code Forest and the Code Tree tool (used once code-‐to-‐code semantic networks have been created). 4.
Creating inductive or emergent codes a.
Creating emergent codes through Open Coding. ATLAS.ti 7 Windows Seminars 2 b.
Creating emergent codes through In-‐Vivo Coding. c.
Writing operational definitions for each emergent code. 5.
Auto-‐coding a.
Reasons for auto-‐coding. b.
Strategies for auto-‐coding. i. Initial exploration. ii. Focused exploration. c.
Checking for the quality of each new quotation: filtering quotations by selected code. Day 2 IV.
Data Exploration, Analysis and Outputs 1.
Memos (back to memos) a.
Linking memos to quotations and codes b.
Graphical representation of linked memos c.
Organizing memos into memo families 2.
Word Cruncher (also an output tool) a. Application: feedback and output b. Excel c. Word cloud d. Use of filters 3.
Exploring the Data through Keywords in Context
a.
The Search tool
b.
The Object Crawler
4.
Exploring the Data Through Filters
a.
Reasons to use filters
b.
Creating and applying primary document filters
c.
Creating and applying quotation filters
d.
Creating and applying code filters
5. Co-‐occurrences a.
Definition: tools that allow to explore spatial associations between codes. They tell you something about the context. b.
Approaches to identify co-‐occurrences: •
The network tool. •
Code co-‐occurrence outputs. •
The Co-‐Occurrence Tree. •
The Co-‐Occurrence Table: qualitative and quantitative data. c.
What to do with the information gathered through the exploration of co-‐occurrences? 6.
Qualitative outputs: The Query Tool: •
Boolean operators •
Semantic operators •
Proximity operators 7.
Quantitative outputs: The Codes-‐Primary Documents Table. VI.
Team Work 1.
Scenarios
2.
Creating IDs for team members
3.
Merging strategies: adding, unifying, and ignoring
ATLAS.ti 7 Windows Seminars 3 VII. Importing survey data •
The Excel spreadsheet structure: symbols and format. •
Importing the Excel spreadsheet. •
Examining the imported survey data: •
Each survey response as a primary document. •
Each variable as a primary document family. •
Each open-‐ended question as a code. •
Each answer given to the open-‐ended questions as a quotation. • Interrogating the survey responses using the Query Tool: •
Answers given to each open-‐ended question. •
Answers given to each open-‐ended question by subsets of participants (Query Tool/Scope of Query). VIII. Conclusion ATLAS.ti 7 Windows Seminars 4