Research Traditions and Paradigms in IS and Organisations
This information is for the 2021/22 session.
Prof Chrisanthi Avgerou NAB 3.22
This course is compulsory on the MPhil/PhD in Management - Information Systems and Innovation. This course is available with permission as an outside option to students on other programmes where regulations permit.
Students from related PhD programmes who are interested in epistemological paradigms may be able to join the course with the teacher's permission.
The course introduces the foundations of social research and the key issues concerning the status of knowledge and the forms by which it is acquired. The course deals with the principal paradigms/traditions in the philosophy of science and epistemology and the answers they have provided to the basic questions concerning the status of knowledge claims and the forms by which valid knowledge claims can be made. The main focus of the course concerns the ways by which these key epistemological paradigms have been applied in the study of information systems and digital innovation.
There are three parts to the course: Part one (lectures1-5) confronts the main traditions within the philosophy of science (positivism, realism, constructivism) and relates these traditions to the development of types of knowledge claims and their relationship to reality. There are references to IS and examples of different stances adopted by major contributions in the IS field. Part two (lectures 5-10) deals with research design for theory building, with emphasis on case study research and ethnography. Key ideas are exemplified with reference to IS research articles. Part three (lectures 11-20) entails a more substantial encounter with the IS field through engagement by key texts in the history of the IS field and the epistemological positions, research designs and data collection methods and analysis such texts illustrate. This last part of the course involves several professors and associate professors of the ISI Group.
This course is delivered through seminars across Michaelmas Term and Lent Term. Teaching hours will be commensurate with a usual full unit taught masters course but note that teaching may take a different format and/or structure in 2021/22.’
This course includes a reading week in Week 6 of Michaelmas Term
• Abbot, A. (2004). Methods of Discovery: Heuristics for the Social Sciences. New York: Norton, pp. 3-40.
• Barley, S. (1990). “The Alignment of Technology and Structure Through Roles and Networks” Administrative Science Quarterly (35:1): 61-103.
• Bowker, G. C. and Star, S. L. (1999). Sorting Things Out: Classification and its Consequences. Cambridge, MA: The MIT Press.
• Burton-Jones, A. (2014). “What Have we Learned from the Smart Machine?” Information and Organization (24:2): 71-105.
• Eisenhardt, K. M. (1989). “Building theories from Case Study Research,” Academy of Management Review (14:4), pp. 532-550.
• Faulkner, P., and Runde, J. (2019). "Theorizing the Digital Object," MIS Quarterly (43:4): 1279-1302.Morgan, G. (1981). “Paradigms, Metaphors and Puzzle Solving in Organization Theory”, Administrative Science Quarterly (25:4): 605–622.
• Sayer, A. (2001). Realism and the Social Sciences. London: Sage.
• Zuboff, S. (1988). In the Age of the Smart Machine. New York: Basic Books.
Essay (100%, 7000 words) in the ST.
Course selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Important information in response to COVID-19
Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Total students 2020/21: 2
Average class size 2020/21: 2
Value: One Unit
Personal development skills
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