Faculty
Associate Professor Torkil Clemmensen, and invited guest teachers

Course Coordinator
Associate Professor Torkil Clemmensen

This PhD course enables the participants to understand and apply digital tools to plan, carry out and report the qualitative parts of different research designs. The course offers participants experience with contemporary qualitative and mixed research designs, which often make use of both quantitative and qualitative data. Examples include experiments (verbal protocols), surveys (open questions), qualitative research interviews, literature reviews (qualitative content analysis), observational studies (video analysis) and more. The course raises participants’ awareness of the quality of qualitative data analysis, such as the transparency of the research design, and the adherence to established rules for presenting qualitative data.

The course offers participants practical experience in analysing and presenting qualitative data from a research project in a multidisciplinary context. Best cases and worst cases of digital qualitative analysis will be presented. Participants are expected to be willing to use data from their own research to analyze during the course. Each day we will have a “write notes for your method section” exercise.

The course will help facilitate the participant’s qualitative data analysis by presenting and discussing some of the questions that researchers ask other researchers when they look for help and advice in how to plan and execute their qualitative data analysis, including technical issues of how to format data for analysis and philosophical discussions of the meaning of reliability and validity in the context of qualitative data analysis.

Students are expected to master basic research design before enrolment and have been introduced to qualitative research methods. Depending on the level of experience with digital analysis of qualitative data among the participants, different kind of qualitative analysis software will be demonstrated (see below for more detail on this).

Completing the course, the participants will earn 3 ECTS points.

The course will run 2½ days, 24-09-2012 to 26-09-2012, from Monday 24 September at 1300 hours and until Wednesday 26 September at 1600 hours, followed by a virtual (by email) sharing of reflections on the course experiences in January.

The plan is to allow participants to during the course to work with digital analysis of their own data. The aim is that the course will enable the participant to go through with digital analysis of own data after the course has ended. Appropriate time for coffee breaks has been allocated. The tentative course program is:

 

READINGS (note: the literature list may change before course start. A compendium of readings is being planned, and participants will receive this ultimo August)

Central readings are marked with a *

Recommended books:

*Creswell, J. W. (2003). Research design - qualitative, quantitative and mixed method approaches. London: SAGE. (in particular chapter 1 and chapter 11)

*Dahler-Larsen, P. (2008). Displaying Qualitative Data. University Press of Southern Denmark, 2008. 170 pages.

Smith, J. A., Flowers, P., & Larkin, M. (2009). Interpretative phenomenological analysis: Theory, method and research: Sage Publications Ltd.

Papers in compendium:

*Alexa, M., & Zuell, C. (2000). Text analysis software: Commonalities, differences and limitations: The results of a review. Quality & Quantity, 34(3), 299-321.

*Barata, P. C., Gucciardi, E., Ahmad, F., & Stewart, D. E. (2006). Cross-cultural perspectives on research participation and informed consent. Social Science & Medicine, 62(2), 479-490.

*Barry, C. A. (1998). Choosing qualitative data analysis software: Atlas/ti and nudist compared. Sociological Research Online, 3(3), http://www.socresonline.org.uk/socresonline/3/3/4.html .

Brett, J. A., Heimendinger, J., Boender, C., Morin, C., & Marshall, J. A. (2002). Using ethnography to improve intervention design. American Journal Of Health Promotion, 16(6), 331-340.

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101.

Buston, K. (1997). Nud*ist in action: Its use and its usefulness in a study of chronic illness in young people. Sociological Research Online, 2(3), U77-U89.

Calloway, L. J., & Ariav, G. (1995). Designing with dialogue charts - a qualitative content-analysis of end-user designers experiences with a software engineering design tool. Information Systems Journal, 5(2), 75-103.

Carroll, J. M., & Swatman, P. A. (2000). Structured-case: A methodological framework for building theory in information systems research. European Journal of Information Systems, 9(4), 235-242.

Clemmensen, T. (2004). Four approaches to user modelling - a qualitative research interview study of HCI professionals' practice. Interacting With Computers, 16(4), 799-829.

Dainty, A. R. J., Bagihole, B. M., & Neale, R. H. (2000). Computer aided analysis of qualitative data in construction management research. Building Research And Information, 28(4), 226-233.

Friese, Susanne (2011). Using ATLAS.ti for Analyzing the Financial Crisis Data [67 paragraphs]. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 12(1), Art. 39, http://nbn-resolving.de/urn:nbn:de:0114-fqs1101397.

Gibson, W., Callery, P., Campbell, M., Hall, A., & Richards, D. (2005). The digital revolution in qualitative research: Working with digital audio data through atlas.Ti. Sociological Research Online, 10(1).

Hoshmand, L. (1989). Alternate research paradigms - a review and teaching proposal. Counseling Psychologist, 17(1), 3-79.

Järvinen, M. (2000). The biographical illusion: Constructing meaning in qualitative interviews. Qualitative inquiry, 6(3), 370.

Loxley, W. (2001). Drowning in words? Using nudist to assist in the analysis of long interview transcripts from young injecting drug users. Addiction Research & Theory, 9(6), 557-573.

MacMillan, K., & McLachlan, S. (1999). Theory-building with nud.Ist: Using computer assisted qualitative analysis in a media case study. Sociological Research Online, 4(2), U135-U151.

Marsh, E. (2001). Atlas.Ti, the knowledge workbench. Library & Information Science Research, 23(1), 93-95.

Olsen, H. (2002). An evaluation of Danish qualitative interview investigations. Nordisk Psykologi, 54(2), 145-172. (in Danish)

Patrizi, P. (2005). Deviant action and self-narration: A qualitative survey through atlas.Ti. Journal For The Theory Of Social Behaviour, 35(2), 171-+.

Richards, T., & Richards, L. (1992). Database organization for qualitative-analysis - the nudist(tm) system. Lecture Notes In Artificial Intelligence, 611, 116-133.

Scales, J., & Lindsay, E. B. (2005). Qualitative assessment of student attitudes toward information literacy. Portal-Libraries And The Academy, 5(4), 513-526.

Yerbury, H., & Parker, J. (1998). Novice searchers' use of familiar structures in searching bibliographic information retrieval systems. Journal of Information Science, 24(4), 207-214.

Zhang, Z., Lee, M. K. O., Huang, P., Zhang, L., & Huang, X. Y. (2005). A framework of ERP systems implementation success in China: An empirical study. International Journal Of Production Economics, 98(1), 56-80.

We will have a limited number of licences of the software Atlas.ti single user educational version running on machines at CBS DIT lab, and these will be available to course participant during the course to try out analysis of their own data. Both Atlas.ti and Nvivo have downloadable demo versions from the software websites. Also take a look at Maxqda and possible other software suitable for qualitative data analysis, including MS Excel, Word, Onenote, and more. Other qualitative analysis software will also be discussed when relevant. We encourage you to bring your own project with your own software, if relevant, and to do analysis work with this during the course.

There will be no traditional demonstrations of any software during the course, but there will be plenty of opportunities for hands-on experience connected with reflection in class. You are therefore required to familiarize yourself with different kind of software packages for qualitative analysis before the course, as good as you can.

There will be examples of complex setups of research projects, best cases as well as worst cases.

Disclaimer: This course is NOT a course in how to use the software (there are several of such courses available, look for them at the distributors of the software websites and their news and mail lists). Instead, this course is an opportunity to work on the intermediate level between theory and practice of digital qualitative analysis.