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Introduction to Qualitative Data Analysis with Atlas.ti V7

Johannes Starkbaum
johannes.starkbaum@univie.ac.at

University of Vienna

Johannes Starkbaum studied sociology at the Universities of Vienna (2003–2009) and Copenhagen (2005). From 2004 to 2007 he worked on different projects on knowledge- and learning technologies, and from 2008–2009 on the sociology of families and fatherhood.

Johannes has taught qualitative methods and computer-assisted analysis since 2009, and works on several international projects doing comparative, qualitative research using Atlas.ti.

His current research focuses on the governance of medical technologies.


Course Dates and Times

 
Friday 2 March
14:00–16:00 and 16:30–18:00

Saturday 3 March
09:00–10:30 / 11:00–12:00 and 13:00–14:30

Prerequisite Knowledge

You should be well grounded in Microsoft Windows and PCs in general, and have some familiarity with qualitative methods and analysis – ideally Qualitative Content Analysis.

If you do not, I strongly recommended reading the mandatory literature for the first unit, and the additional reading suggestions.

Atlas.ti experience not required.


Short Outline

The main purpose of this course is to teach you about computer assisted qualitative data analysis with Atlas.ti.

I will introduce Qualitative Content Analysis (QCA) to demonstrate practical ways of using Atlas.ti. We will focus mainly on textual data; however, I will include visual and audio data.

After reflecting on the assets and drawbacks of computer assisted analysis, I'll provide a brief introduction to QCA. Then we will retrace the process, from the decision to do computer assisted analysis, to producing output. You will build up your own project with a given data set.

Major steps are:

  • data management
  • creation and usage of quotes and codes
  • usage of comments and memos
  • splitting and comparing data
  • retrieving data pieces by different search functions
  • semantic networks.

Throughout them all, we will aply QCA to provide a practical example for using Atlas.ti.

The course alternates between lectures, plenary sessions and independent work. If there is time, we will discuss some of students' existing projects.


Long Course Outline

The main purpose of this course is to teach you about computer assisted qualitative data analysis with Atlas.ti.

I will introduce Qualitative Content Analysis (QCA) to demonstrate practical ways of using Atlas.ti. We will focus mainly on textual data; however, I will include visual and audio data. After reflecting on the assets and drawbacks of computer assisted analysis, I'll provide a brief introduction to QCA. Then we will retrace the process, from the decision to do computer assisted analysis, to producing output. 

The course alternates between lectures, plenary sessions and independent work.

First, we will discuss computer assisted data analysis on a general level, critically reflecting on the assets and drawbacks of these programs. Then we will discuss potential areas of application, and where such programs may be less effective or even problematic.

I will provide a brief introduction to QCA, pointing out the particularity of this approach. This overview will include general logics, as well as concrete techniques and application. I will give more information on a regular basis, according to the different stages of students' projects.

You will then build up your own project with a given data set. Data management and the up-building of an efficient project folder are essential for the further project, and we will discuss them in detail.

Next, we will practice the creation and usage of quotes and codes, while deconstructing the logic assembling of Atlas.ti. We will introduce and practice different logics of defining secluded patterns of meaning, and linking them with codes. We will also apply inductive and deductive coding. While coding and working with textual data lies at the heart of this course, I will include some images and audio/video material in the analysis, i.e. assembled with codes.

Parallel to that, we will discuss the usage and importance of comments and memos. I will pay specific attention to the importance of comments and memos for reflecting and bringing forward the project, developing concepts, teamwork, and for preparing the context for further dissemination of results.

I will then introduce different options for splitting and merging, and thereby comparing, the data. You will learn how to group your primary documents, as well as the codes and categories so far created. Constant comparison is one of the major logics of many methodologies, and important not only for quality management, but also for producing rich results. These functions may also be used for building categories within the coding system.

Code-and-retrieve is the immanent logic of most qualitative data analysis packages. Atlas.ti can retrieve coded data segments and output them, and it can operate complex inquiries using Boolean, proximity or semantic operators (query tools).

I will show different ways of retrieving already-coded data and we will discuss their practical usage for qualitative research. These functions will be amended by search operations based on the text documents that may also include GREP operators. The option of auto-coding these search results advances the areas of application and plays out its strength the most by further combination with the query tool. Then, almost any entity within the project may be defined as unit and compared or brought in context with other material.

Finally, networks have several functions in Atlas.ti. They are particularly helpful for structured content analyses in QCA. Throughout the semantic networks one can up-build, Atlas.ti helps researchers understand the larger logics within the field. Structured content analysis, comparison and contrasting is the major goal. Networks are also useful for building categories and hierarchies between codes.

By retracing a complete qualitative data analysis project, and the parallel documentation via memos, you will learn how knowledge is created in such a process and how this knowledge can then be extracted and transformed into a written paper. Here, the constant swapping between textual and conceptional levels are significant.

You will learn about the whole process of computer-assisted data analysis, and how to practice these technical steps with a common data set. The application of QCA will provide concrete examples of how an analysis may be performed using Atlas.ti. You will be able to practice all steps and techniques on your own, in consultation with me.

You will gain insight into theoretical and practical issues with computer assisted data analysis with Atlas.ti. Some students will be able to present their own data/projects to demonstrate the scope of possibilities of Atlas.ti, and to gain feedback.

Day Topic Details
Saturday morning Memos and comments - Data splitting and comparison: document- and code families - Retrieval: text search, auto-coding, query tool, co-occurrence

Lecture and plenary sessions as well as individual work.

Friday General discussion of computer assisted analysis - Brief introduction to Qualitative Content Analysis - Data management and project up-build - Quotes and coding

Lecture and plenary sessions as well as individual work.

Saturday afternoon Networks and linkage - Discussion of existing projects - Teamwork and data management

Lecture and plenary sessions as well as individual work.

Day Readings
Friday

Clive Seale (2013): Using Computers to Analyse Qualitative Data. In: Silvermann, David (Ed.) Doing Qualitative Research Sage: London, 264–278

Mayring P (2014) Qualitative Content Analysis. theoretical foundation, basic procedures and software solution. SSOAR Open Access

Friese S (2014) Qualitative Data Analysis with Atlas.ti. Thousand Oaks, Sage.

Konopásek, Z (2008) Making Things Visible With Atlas.ti: Computer Assisted Analysis as Textual Practice. Forum Qulitative Sozialforschung 9(2).

Software Requirements

Atlas.ti 7.x

Literature

To be confirmed


Additional Information

Disclaimer

This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc). Registered participants will be informed at the time of change.

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, please contact us before registering.