TJTS5001 Research Methods (5 cr)
Description
Content
Research methods form generally accepted practices to collect, process, and analyze empirical material for scientific or business purposes. Students learn how to collect, process, and analyze empirical material and how to use it in scientific research (e.g. a Master’s thesis).
Completion methods
Attending to the lectures is recommended. However, students can complete the course by using individual/remote learning by completing the exam and a written assignment. The workload of the course is 135 hours (5 credits), it is divided as follows: Lectures/Other sessions: 20 h, Individual assignment: 60 h, Exam and preparation for the exam: 55 h.
Assessment details
The grade is based on the course assignment report and the course exam, using the standard 0-5 scale.
Learning outcomes
Students are able to evaluate and select research method(s) for their MSc thesis project. Students are familiarized with qualitative and quantitative methods, as well as essential Information Systems field of research approaches, such as Design Science. Students know general aspects of research ethics. Students are able to utilize their research method knowledge both in doing research (for e.g. their thesis, or other research project work), and in interpreting scientific literature.
Description of prerequisites
Students should have completed their BSc studies, including a BSc thesis or corresponding work. In this course, the students will learn how to collect, process, and analyze empirical material that is needed for a MSc thesis study. This course is best taken together with the MSc Thesis Seminar, as both units are intended to support the MSc thesis work.
Study materials
Additional reading material:
- Bhattacherjee, A. (2012). Social science research: Principles, methods, and practices. University of South Florida, USA. Freely available at: http://scholarcommons.usf.edu/oa_textbooks/3/
- Miles, M.B. & Huberman, A.M. (1994). Qualitative Data Analysis: An Expanded Sourcebook. California: Sage Publications.
- Yin, R.K. (2009). Case study research: design and methods. Sage Publications.
- Ketokivi, M. (2015). Tilastollinen päättely ja tieteellinen argumentointi (2. laaj. laitos). Gaudeamus.
- Allison, P. D. (1999). Multiple Regression : A Primer. Thousand Oaks, Calif: SAGE Publications, Inc.
- Singleton, R. A. J., & Straits, B. C. (2009). Approaches to social research (5th ed.). New York, NY: Oxford University Press.
- DeVellis, R. F. (2017). Scale Development: Theory and Applications (4th ed.). SAGE Publications.
Literature
- Eisenhardt, K.M. 1989. Building theories from case study research. Academy of Management Review 14(4), 532-550.
- Peffers, J., Tuunanen, T., Rothenberger, M.A. & Chatterjee, S. 2007. A Design Science Research Methodology for Information Systems Research. Journal of Management Information Systems 24(3), 45-77.
- Benbasat, I., Goldstein, K.K. & Mead, M. 1987. The Case Research Strategy in Studies of Information Systems. MIS Quarterly 11(3), 369-386.
- Eisenhardt, K.M. & Graebner, M.E. 2007. Theory building from cases: Opportunities and challenges. Academy of Management Journal 50(1), 25-32.
- Myers, M.D. & Newman, M. 2007. The qualitative interview in IS research: Examining the craft. Information and Organization 17(1), 2-26.
- Singleton, R. A. J., & Straits, B. C. 2009. Approaches to social research (5th ed.). New York, NY: Oxford University Press. (Chapter 4: Research Design, Chapter 5: Measurement, Chapter 15: Data Processing and Elementary Data Analysis, Chapter 16: Multivariate Analysis)
- Venkatesh, V., Thong, J., Chan, F.K.Y. & Hu, P.J.H. 2016. Managing Citizens’ Uncertainty in E-Government Services: The Mediating and Moderating Roles of Transparency and Trust. Information Systems Research 27(1), 87-111.
- Darke, P., Shanks, G. & Broadbent, M. 1998. Successfully completing case study research: combining rigour, relevance and pragmatism. Information Systems Journal 8(4), 273-289.
- Allison, P. D. (1999). Multiple Regression : A Primer. Thousand Oaks, Calif: SAGE Publications, Inc (Chapter 1: What is Multiple Regression, Chapter 2: How Do I Interpret Multiple Regression Results)