African Institute for ATLAS.ti
Welcome to Stellenbosch University


​ATLAS.ti Trainer Accreditation: Introductory Level

The accreditation process for Introductory Level Trainers consists of three key components:

1) The candidate must provide at least one ATLAS.ti project for review. The project does not have to be large in scope but must show the candidate's ability to utilize the key functions of ATLAS.ti. The Hermeneutic Unit should be sent to

Dr. Ricardo Contreras


ATLAS.ti Americas

Training & Partnership Development


Dr. Lauren Wildschut


African Institute for ATLAS.ti (AIA)

This component will compromise half of the weighting of the assessment process.

2) The candidate must teach for 60 minutes from the competency checklist provided overleaf. The teaching must take place at an accreditation session of the AIA – usually run in January of each year at the AIA offices at Stellenbosch University, South Africa. This accreditation process may move to other locations if the need is sufficient. If the quality of the feed is good enough, then the candidate may also present a Skype session.

When teaching the candidate should keep the following principles in mind and integrate them where appropriate:

Methodological principles

  • The key contributions of ATLAS.ti to CAQDAS
  • Methodological flexibility (from deductive to inductive)
  • The researcher is always in control
  • The concept of triangulation in ATLAS.ti (multiple file formats, multiple methods of data collection)
  • The notion of integration in the analysis. In other words, the need to construct a holistic understanding of the research problem.

The observation of these sessions will be done by Dr Susanne Friese and/or Dr Lauren Wildschut.

3) All candidates must attend compulsory webinars before applying to do the teaching sessions. A list of compulsory webinars will be provided to candidates.

Checklist for ATLAS.ti Trainers (Introductory level)

1. The structure of ATLAS.ti

  • The hermeneutic unit (HU) or analysis project
  • The objects of the HU
  • The new features of the HU interface (e.g, side panels)

2. Data management

  • Backing-up HUs with external documents (copy bundle)
  • Backing up HUs with embedded documents exclusively

3. Accessing sources of information (when and why to use each one)

  • Adding external sources
  • Creating new text documents (embedded)

4. The "library" concept in version 7

  • Personal library
  • Team library

5. Importing survey data

  • Preparing the spreadsheet
  • The imported survey: primary documents, comments, authors, primary document families, codes, and quotations
  • What to do in case of different waves of data collection?
  • What to do if new survey items are added in subsequent waves of data collection?

6. Primary documents

  • The PD Manager
  • Comments
  • Primary document organization (i.e., PD families and super PD families)
  • Applications of PD families (e.g., exploration of data across cases)

7. Codes

  • The Code Manager: comments, groundedness, density
  • The concept of a "flat coding structure"
  • Inserting into the HU codes that derive from an external frame of reference (e.g., research objectives, hypotheses): inserting them one by one or several of them at once.
  • Creating codes that emerge from the text ("open coding")
  • Different strategies to code with existing list of codes
  • In vivo coding
  • Auto-coding: how, when, and why?
  • Being able to answer questions regarding how to structure a code list

8. Quotations

  • Definition
  • Free quotations
  • The quotation ID
  • The quotation comment space

9. Memos


Distinction between memos and comments

Types of memos

Linking memos to quotations: Why? How? When?

Linking memos to codes: Why? How? When?

10. Filters

Objects that can be filtered (i.e., primary documents, quotations, and codes)

Applications of filters

11. Search tools

Text search

Object Crawler

12. Networks

Weak link networks: applications

Strong link networks:

  • code-to-code networks: applications
  • hyperlinks: applications

Differences between a code-to-code network and code families


  • Types
  • Formal properties of relations
  • Applications of the transitive type of relation

Creating new relations

Exporting networks as graphic files

**Reasonable support will be provided by AIA to those candidates wishing to go through the accreditation process

**The services of accredited trainers will be advertised on the AIA website.

** Dates: Interested parties should indicate their interest by 15 September by emailing Project submission date: 30 November 2014. Teaching assessment: during the week 19-23 January 2015. Individual slots will be arranged.

​​Introduction to qualitative data analysis with ATLAS.ti

Course description
This is an introductory course on qualitative data analysis (QDA) using a software programme called ATLAS.ti. Participants will be introduced to the range of qualitative data analysis types and will be shown how this software programme can be utilised to assist with your literature review. The course is very practical and students may bring along any qualitative data they have already collected for their thesis. You should already be familiar with the basic concepts of social research and be computer literate in order to register for this course.

Specific course elements are the following:

  • Introduction to qualitative data analysis

  • Computer Assisted Qualitative Data Analysis Software (CAQDAS)

  • Coding :

    • Types of Coding

    • Classifying and connecting codes

    • Coding levels

    • Developing a code book

  • ATLAS.ti

    • General working procedure

    • Terminology

    • Outputting results- quotes, codes, Networks and memos

    • Hypertext linking

  • Using ATLAS.ti for your literature review

  • Data management and  team work

  • Presenting QDA

Advanced qualitative data analysis with ATLAS.ti

Course description
This course follows on from the introductory course, which is a PRE-REQUISITE for attending this course.

You should know the basic concepts and be familiar with the four main objects: primary documents, quotations, codes and memos and have coded some data in ATLAS.ti. The aim of this course is to teach you how the technical aspects of ATLAS.ti liaise with the methodological aspects of computer-assisted analysis. Knowing the technical aspects of coding is one thing, building a well-developed coding system that supports data analysis in an optimal way is another. If you already have some coded data, you are welcome to bring it to the course so we can take a look at it and see where and how to improve on it if necessary.

The text topic area is the data analysis tools: the Query Tool, the Cooccurence Explorers, the Codes-Primary-Documents-Table and some other miscellaneous tools. We will first take a look at the basic principles of each tool and then run some example queries either based on your own material or based on example material provided. Writing memos and comments is inherently related to the data analysis process. Therefore these will be discussed here as well.

The third topic area is the network view function. Here we look at some technical aspects and some methodological issues.

There will be room for individual project related questions, special issues to discuss like coding different types of data, importing survey data, mix-methods approaches or project management issues.