Antagna till forskarutbildning.
Applicants are required to be familiar with research within social sciences and have passed qualitative and/or mixed methods courses at basic levels.
The course is comprised of lectures, hands-on laboratory workshops, tutorials and seminars. The course is divided to the following thematic blocks. One or more session(s) may be devoted to each thematic block (see the program for details).
More about the course
Computer-Aided Qualitative Data Analysis Software (CAQDAS) is a term which refers to a category of computer software that have been developed specifically to assist researchers in completing a range of tasks associated with analysis and interpretation of qualitative data. Nowadays, Computer Aided Qualitative Data Analyses has advanced extensively and include a broad range of software, the general principle in all of them, however, is the use of qualitative methods and qualitative data. The title of the course with its emphasis on the data analysis might be misleading since the course aims to discuss pre-analysis stages including data preparation (organization and data import), analysis (theory-based as well as grounded theory) and post-analysis processes such as compatibility with statistical packages, model building and presentation of the findings.
The course will introduce the theoretical underpinnings of the computer aided qualitative analysis software, methodological foundations, research paradigms, essential terminology and approaches. The rationale behind different software designed for the qualitative data analysis, logics of data organization, coding and retrieval approaches and model building will be introduced throughout lectures and hands-on workshops.
Course participants are intended to become acquainted with the usage of computer with various types of qualitative data, approaches of data collection and choice of appropriate software for various types of data and analysis. The participants will be granted an opportunity to practice various ways of collecting data, organizing them in the software, run and conduct the analysis and use the outputs for building models or further analyses.