Microcredential ekomex: Qualitative Data Analysis – Concepts and Techniques

This five-day online course covers foundational topics of qualitative data analysis and trains participants, hands-on, to perform two popular data analytic techniques: thematic analysis and qualitative content analysis.

What Is This Course About?
The course introduces key concepts, strategies, and techniques for qualitative data analysis by grouping them as solutions to four sets of challenges which, if not properly addressed, can threaten confidence in qualitative research. These sets of issues are: first, decontextualized collection and analysis of data; second, data overload vs. overly tight or sketchy application of one’s own conceptual lenses; third, doubts about the quality of conclusions; and fourth, opaque documenting and reporting. The course treats each of these four issues by training participants, hands-on, to perform two popular data analytic techniques: thematic analysis and qualitative content analysis.

Learning Goals
After this course you will be able to:

• Choose the most suitable method for thoughtful documentation and your approach for effective and transparent methodological reporting.
• Choose the most appropriate strategy for ensuring the reliability and validity of your qualitative findings.
• Apply (in NVivo or other QDA software) techniques and tools offered by two popular qualitative data analytic methods: thematic analysis and qualitative content analysis.
• Reflect critically on the assumptions, research goals and designs design you favour, and align data collection and analysis with the design most suitable for your research context.

Assignments for the Course

• 4 ECTS points can be obtained by actively taking part in all course activities (80%), by delivering four daily assignments (short reflections or small tasks with sample data provided by instructor) and by submitting a take-home paper. In the take-home paper, participants will be invited to tackle challenges and solutions in own qualitative data work. While take-home paper will receive qualitative feedback, no grades are provided other than pass of fail.
• The course involves exercises with sample data (provided by the instructor) with the NVivo software. While these exercises will foster the use of NVivo basic functionalities, there is no need for prior familiarisation with NVivo nor for purchasing the software as we will be able to use a 14-day free trial version. Also, participants already using other QDAS (such are ATLAS.ti and MAXQDA) will also be able to follow and perform exercises with their own software package.

Schedule

• 09:00-10:30h: Asynchronous materials (lecture video, fun follow up quiz and/or task)
• 10:30-11:00h: Time for break
• 11:00-12:30h: Course: lab (hands on work in NVivo or other QDA software)
• 12:30-13:30h: Time for lunch break
• 13:30-14:30h: Course - independent small group work
• 14:45-15:45h: Office hours

Note: students should plan for sufficient time to do the assigned daily assignment (short reflections or small tasks with sample data provided by instructor) and read the assigned literature in advance.

Recommended Readings for the Course

• Kekez, A. (2019). “Qualitative data analysis in implementation and street - level bureaucracy research”. In: P. Hupe (Ed.) Research Handbook on Street-Level Bureaucracy: The Ground Floor of Government in Context (pp. 317-336). Cheltenham, UK and Northampton, MA, USA: Edward Elgar Publishing.                                                   
• Braun, V., Clarke, V., Hayfield, N.& Terry, G. (2019). Thematic analysis. In P. Liamputtong (Ed.), Handbook of Research Methods in Health Social Sciences (pp. 843-860). Singapore: Springer.
• Schreier, M. (2014). Qualitative content analysis. In U. Flick (Ed.), Qualitative data analysis (pp. 170–509). London: Sage.

Who is Your Instructor?
Anka Kekez is an assistant professor at the Faculty of Political Science at the University of Zagreb, Croatia, where she teaches public policy, public management, and qualitative methodology. She has extensive experience teaching and tutoring qualitative methods and qualitative data analysis (particularly including Nvivo) in a variety of settings. Recently, Anka received MethodsNET Pedagogical Excellence Award as the instructor of the Qualitative Data Analysis course delivered in 2022 at the 1st Summer School in Social Research Methods held in Nijmegen, the Netherlands. Using variety of qualitative data analytic methods, Anka has published papers at the Policy and Society, the Policy Sciences, the Policy Design and Practice or the Journal of Comparative Policy Analysis (among other journals).
Website https://www.fpzg.unizg.hr/staff/anka.kekez_kostro
LinkedIn https://www.linkedin.com/in/anka-kekez-06416843