Digital analysis of qualitative data (May 27-29) CANCELLED

Faculty
Associate professor Torkil Clemmesen and invited guest teachers

Course Coordinator
Associate professor Torkil Clemmensen

The PhD 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 details).

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 analyse 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 ability and validity in the context of qualitative data analysis.

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.

Lecture plan

Time/period	Faculty	Title
Wednesday
13:00	Torkil Clemmensen	Course introduction
13:30-14:00	Sudhanshu Rai & Annemette Leonhardt Kjærgaard	Examples of the use of digital analysis of qualitative data
14:00-16:00	Torkil Clemmensen	The quality of digital analysis of qualitative data
16:00-18:00	Torkil Clemmensen	Preparation of data for digital analysis
Thursday
09:00-10:30	Torkil Clemmensen	Case: HCI professional's user modelling
10:30-12:30	Torkil Clemmensen	Next steps in digital analysis
12:30-14:00		Lunch
14:00-18:00	Torkil Clemmensen	Analysis of participants own data
Friday
09:00-9:30	Torkil Clemmensen	"Write notes for your method section"
09:30-11:00	Torkil Clemmensen	Presenting results from digital analysis
11:00-12:30	Torkil Clemmensen	Participants work with presentation of their data
12:30-14:00		Lunch
14:00-15:00	Torkil Clemmensen	More analysis and presentations of own data
15:00-16:00	Torkil Clemmensen	Preparation for email session in July
July - date to agree on later	Facilitator: Torkil Clemmensen	Email circulation and discussion of experiences based on the question: "What did you write in your method section"?

The plan is to allow participants, 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.

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 participants during the course in order to try out analysis of their own data. Both Atlas.ti and Nvivo have downloadable demo versions from the software websites. 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 familiarise yourself with different kinds 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.

In July 2009 the course will be followed by a virtual (by email) sharing of reflections on the course experiences.

Course diploma will be issued after participation in the course.

Required readings are marked with a *

*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)

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

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

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

Dahler-Larsen, P. (2002). At fremstille kvalitative data: Odense Universitetsforlag

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

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)

Guerrier, Y. (1996). Atlas-ti. Management Learning, 27(2), 252-254

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

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

Murray, P. J., & Muhr, T. (2000). Atlas.Ti the knowledge workbench - software for visual qualitative data analysis, management and model building in education, research and business. Journal Of Advanced Nursing, 31(1), 245-245

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

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

Preece, J. (2001). Sociability and usability in online communities: Determining and measuring success. Behaviour & Information Technology, 20(5), 347

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

A few texts will be in Danish only. Replacements of these will be sought. (Dahler-Larsen, 2002; Olsen, 2002).

For more information about the course, please contact Torkil Clemmensen, associate professor at the Department of Informatics, Copenhagen Business School, phone +45 38152389, email: tc.inf@cbs.dk.

The deadline for enrolment is April 1, 2009. Regarding practical information and enrolment, please contact Anni Olesen, administrative officer at the Department of Informatics, Copenhagen Business School, Phone +45 38152282, e-mail: ao.inf@cbs.dk.