MAXQDA in qualitative research

elective courses

Basic knowledge and skills in qualitative data analysis, good command of English

Classroom

The goal of the course is to learn how to use MAXQDA for qualitative data analysis. Participants will learn how to work with the program during qualitative analysis of content from different sources: interviews, visual materials, press materials, web content (Twitter, websites, etc.). Students will learn how to apply key program features to conduct step-by-step analyses. The skills gained in the course will be applicable to both academic and commercial research contexts.

The goal of the course will be to learn how to use MAXQDA for qualitative analysis of content and visual material. Participants will get to know the most important functions of the program, helpful in the analysis itself, as well as the possibilities of using these functions to analyze different types of materials, including interviews, visual materials, press materials, Internet content (Twitter, websites, etc.). Ways for combining analyses of diverse materials will be presented, as well as limitations in the use of MAXQDA and potential methodological issues, including those related to teamwork. Students will learn the application of key program features to perform step-by-step analyses. Participants will also become familiar with the quantitative analysis and data visualization tools offered by the program (e.g., code relationships, code clouds, etc.). The skills gained will be transferable to both academic and commercial research contexts.

As part of the course, students will both work in class, and at home. Take-home assignments (e.g., coding a text fragment, preparing a visualization of materials) will be part of the course evaluation. There will be at least 5 such assignments per semester.

The students will be required to prepare presentations summarizing their research projects and findings, given during final class.

Kuckartz, U., & Rädiker, S. (2019). Analyzing qualitative data with MAXQDA: Text, audio, and video. Springer.

Niedbalski, J. (2014). Komputerowe wspomaganie analizy danych jakościowych. Zastosowanie oprogramowania NVivo i Atlas.ti w projektach badawczych opartych na metodologii teorii ugruntowanej. Wydawnictwo Uniwersytetu Łódzkiego. https://doi.org/10.18778/7969-060-2

K_W07 Has in-depth knowledge of selected methods and techniques of social research, their limitations, specificity and areas of application

K_W08 Is aware of the importance of a reflective and critical approach to the results of social research, analyses and research procedures

K_W09 Knows how to plan and carry out complex qualitative and quantitative empirical research; is aware of the consequences of methodological choices

K_U04 Can use theoretical categories and research methods in the description and analysis of social and cultural changes in modern societies, as well as their consequences

K_U05 Can plan and carry out a social study using advanced quantitative and qualitative methods and techniques of social research

K_U06 Can use a selected computer program for data analysis, including its advanced functions

K_U10 Can prepare a presentation of a selected problem or study in Polish and in a foreign language

K_K03 Can gather, find, synthesize and critically assess information about social sciences

K_K04Can argue a thesis using scientific evidence

K_K10Takes responsibility for planned and performed tasks

Activity during class, preparation of take-home assignments (min. 5), which will require using the knowledge and skills acquired during the course, for instance coding of segments, data visualization, etc. (Maxqda files or export files). Preparation of presentations summarizing the research projects.

Maximum number of absences allowed: 2

Resit: take-home assignments