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2022/2023  KAN-CINTO2821U  Researching Technologies: Explanatory and Design Strategies

English Title
Researching Technologies: Explanatory and Design Strategies

Course information
Language English
Course ECTS 7.5 ECTS
Type Mandatory
Level Full Degree Master
Duration One Semester
Start time of the course Spring
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for BSc/MSc in Business Administration and Information Systems, MSc
Course coordinator
  • Torkil Clemmensen - Department of Digitalisation
Main academic disciplines
  • Information technology
Teaching methods
  • Face-to-face teaching
Last updated on 21-06-2022

Relevant links
Learning objectives
To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors:
  • Demonstrate an ability to identify and formulate technological problems central to businesses
  • Conduct research and reflect on approaches for solving formulated technological problems
  • Develop plausible solutions for addressing formulated technological problems (i.e., research question)
  • Assess, explain, and communicate developed solutions to key stakeholders
Course prerequisites
Completion of first semester at cand. merc.(it.)
Prerequisites for registering for the exam (activities during the teaching period)
Number of compulsory activities which must be approved (see section 13 of the Programme Regulations): 3
Compulsory home assignments
There are four assignments in the course, each covering a major stage in research technologies (for example, identifying technological problem, explanation/solution from prior literature, data collection strategy, gain solution from analysing data). The purpose with the assignments is to systematically provide students with opportunities for feedback on their work from fellow students and from their teacher(s), see the description of feedback in this course.

The students must have 3 out of 4 assignments approved in order to go to the exam.

Each assignment will be max 4 pages long. It is a group assignment with group size from 1-3.

There will not be any extra attempts provided to the students before the ordinary exam.
If a student cannot hand in due to documented illness, or if a student does not get the activity approved in spite of making a real attempt, then the student will be given one extra attempt before the re-exam. Before the re-exam, there will be one home assignment (max.10 pages) which will cover 3 mandatory assignments.
Examination
Researching Technologies: Explanatory and Design Strategies:
Exam ECTS 7,5
Examination form Oral exam based on written product

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance, see also the rules about examination forms in the programme regulations.
Individual or group exam Oral group exam based on written group product
Number of people in the group 2-3
Size of written product Max. 15 pages
The report needs to be within 15 standard pages, plus appendix.
Assignment type Project
Duration
Written product to be submitted on specified date and time.
15 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Grading scale 7-point grading scale
Examiner(s) Internal examiner and second internal examiner
Exam period Summer
Make-up exam/re-exam
Same examination form as the ordinary exam
Students can submit the same project or they can choose to submit a revised project.
Description of the exam procedure

The oral exam is a dialogue based on the project written by the students.

 

2 students are examined in 30 minutes.

3 students are examined in 40 minutes.

 

The examination time includes time for the examinator to inform the students about the grade.
Course content, structure and pedagogical approach

By taking this course, you will develop the capability to identify the challenges and topics in information technology industry from both global connections and local community. You will also master the knowledge to systematically and scientifically assess the identified technological problem from sociotechnical perspective, for example technology, humanity, and ethics. In addition, you will learn data-driven solution to the technological problem. You will also have opportunity to cultivate your communication and cooperation capability.

 

The objective is to help you engage in learning activities that matter and where you are setting the scene for the learning journey fulfilling the academic, domain, and operational learning objectives of the study program's  competence profile.

 

Besides aligning you and the study program's other learning activities, we also want to stimulate you in problem solving that matters and where the solutions are not trivial. The course introduces a business case and course participants are expected to progressively, over the course, design a research study based on the case.

 

The project is organized as a number of seminars where students meet with supervisors and discuss the status of their projects. At each seminar, the key texts will be introduced by the supervisor in a lecture. 

 

The project is pointing forward to study relevant activities in the third semester and while writing the master thesis.  

  

The project needs to be anchored in subjects and themes central to the study program, and where relevant, incorporate theory and/or models and methodologies and / or tools. 

 

The project report needs, for each key part, to provide both an illustrative example and a plan for further research. The example may include  mini-literature review, some data collected, example analysis of the data, two-three sketches, a single hypothesis testing prototype, and more.  The plan will give a reasonably detailed view of how to scale the example up to master thesis level.
Description of the teaching methods
The students will receive supervision for the project.
There are 5 hours for two students, 7 hours for three students.
Feedback during the teaching period
Systematic peer-review of each of four mandatory assignments provided the students with excellent feedback from three (number may vary) other student groups, plus review by the track teacher(s), all of which is done in a CBS endorsed peer review system (e.g., Peergrade.io). This is followed up systematically by the teachers during group supervision, based on the completed mandatory assignments and the reviews of those. Additional, per request feedback is provided by emails and F2F (when possible) from teachers.
Student workload
Workshops 8 hours
Supervision 5 hours
Preparation for workshops 35 hours
Individual study 148 hours
Preparation for exam and the exam 10 hours
Total hours 206 hours
Further Information

No later than three weeks after the project starts, the detailed project description including name of supervisor and all group members must be mailed to the project coordinator. 

 

Instructions on the project description will be available at Canvas prior to the course start.

 

There can be adjustments to the project description, but these will have to be justified and approved by the supervisor.

 

Supervisors for the projects will be approved and, if necessary, assigned by the course coordinator.
Expected literature

The literature can be changed before the semester starts. Students are advised to find the final literature on Canvas before buying any books.

 

 

Mandatory literature

Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard business review, 96(1), 108-116.

 

Felin, T., & Lakhani, K. (2018). What problems will you solve with blockchain?. MIT Sloan Management Review, 60(1), 32-38.

 

Pistrui, J. (2018). The future of human work is imagination, creativity, and strategy. Harvard Business Review, 1(18), 2018.

 

Hevner, A. R., March, S. T., Park, J., & Ram, S. (2008). Design science in information systems research. Management Information Systems Quarterly, 28(1), 6, 75-105.

 

Dorst, K. (2011). The core of ‘design thinking’ and its application. Design studies, 32(6), 521-532.

 

Djamasbi, S., Strong, D., Wilson, E. V., & Ruiz, C. (2016). Designing and testing user-centric systems with both user experience and design science research principles. Emergent research, AMCIS2016

 

Rai, A. (2017). Editor's comments: diversity of Design Science Research. MIS Quarterly, 41(1), iii-xviii.

 

Mandatory literature for the Explanatory track

Gregor, S. (2006). “The Nature of Theory in Information Systems,” MIS Quarterly (30:3), 2006, pp. 611-642.

32

Ellis, T., & Levy, Y. (2008, January). Framework of problem-based research: A guide for novice researchers on the development of a research-worthy problem. Informing Science: The International Journal of an Emerging Transdiscipline, 11, 17-33

17

Weber, R. (2012). Evaluating and developing theories in the information systems discipline. Journal of the Association for Information systems, 13(1), pp.1-30.

30

Paré, G., Trudel, M. C., Jaana, M., & Kitsiou, S. (2015). Synthesizing information systems knowledge: A typology of literature reviews. Information & Management, 52(2), 183-199.

17

Webster, J. and Watson, R. “Analyzing the Past to Prepare for the Future: Writing a Literature Review,” MIS Quarterly (26:2), 2002, pp. xiii-xxiii.

10

Sarker, S., Xiao, X., Beaulieu, T., & Lee, A. S. (2018). Learning from First-Generation Qualitative Approaches in the IS Discipline: An Evolutionary View and Some Implications for Authors and Evaluators (PART 1/2). Journal of the Association for Information Systems, 19(8), 752-774.

24

Fusch, P. I., & Ness, L. R. (2015). Are We There Yet? Data Saturation in Qualitative Research.The Qualitative Report, 20(9), 1408-1416. Retrieved from https:/​/​nsuworks.nova.edu/​tqr/​vol20/​iss9/​3

8

Urquhart, C., & Fernandez, W. (2016). Using grounded theory method in information systems: the researcher as blank slate and other myths. In Enacting Research Methods in Information Systems: Volume 1 (pp. 129-156). Palgrave Macmillan, Cham.

28

Van de Ven, A. H., and Poole, M. S. (1995). Explaining development and change in organizations. Academy of management review, 20(3), 510-541.

32

Gefen, D., Straub, D. and Boudreau, M. C. “Structural Equation Modeling and Regression: Guidelines for Research Practice,” Communications of the Association for Information Systems (4:7), 2000.

70

Mandatory literature

268

Reference papers (3 papers addressing similar topic as project)

60

Project relevant literature

200

TOTAL LITTERATURE

528

 

 

Mandatory literature for the Action design track

Gregor, S. (2006). The Nature of Theory in Information Systems. MIS Quarterly (30:3), 2006, pp. 611-642.

30

Hevner, A. R., March, S. T., Park, J., & Ram, S. (2008). Design science in information systems research. Management Information Systems Quarterly, 28(1), 6, 75-105.

32

Djamasbi, S., Strong, D., Wilson, E. V., & Ruiz, C. (2016). Designing and testing user-centric systems with both user experience and design science research principles. Emergent research, AMCIS2016

5

Dorst, K. (2011). The core of ‘design thinking’ and its application. Design studies, 32(6), 521-532.

12

Bellamy, R., Desmond, M., Martino, J., Matchen, P., Ossher, H., Richards, J., & Swart, C. (2011, May). Sketching tools for ideation (NIER track). In Proceedings of the 33rd International Conference on Software Engineering (pp. 808-811). ACM.

 

Mandviwalla, M. (2015). Generating and justifying design theory. Journal of the Association for Information Systems, 16(5), 314-344

32

Buchenau, M., & Suri, J. F. (2000, August). Experience prototyping. In Proceedings of the 3rd conference on Designing Interactive Systems: processes, practices, methods, and techniques, DIS2000, (pp. 424-433). ACM.

10

Rai, A. (2017). Editor's comments: diversity of Design Science Research. MIS Quarterly, 41(1), iii-xviii.

17

Joshi, S. G., & Bratteteig, T. (2016). Designing for prolonged mastery. On involving old people in participatory design. Scandinavian Journal of Information Systems, 28(1), 3-36.

35

Reinecke, K., & Bernstein, A. (2013). Knowing What a User Likes: A Design Science Approach to Interfaces that Automatically Adapt to Culture. Mis Quarterly, 37(2), 427-454.

39

Mandatory literature

212

Reference papers (3 papers addressing similar topic as project)

60

Project relevant literature

200

TOTAL LITTERATURE

462

 

 

 

 
Last updated on 21-06-2022