In terms of knowledge and understanding, after completed course the student should be able to:
- based on different knowledge-theoretical concepts and paradigms, present key issues within knowledge creation in information systems research
- explain different knowledge products that can form the result of a research process
- explain different scientific methods for data collection and analysis
- describe how a research process can be structured based upon problem formulation, research questions, knowledge contribution and products, choice of research approach, choice of data collection and analysis methods, implementation, and reporting of results
In terms of skills and abilities, after completed course the student should be able to:
- create a research plan, i.e., structure and plan a research or other knowledge development process within the area of information systems
- explain choice of research approach, e.g., qualitative, qualitative, or experimental approaches, in relation to the goals, knowledge contribution and knowledge products of the research process
In terms of judgment and approach, after completed course the student should be able to:
- reflect on own assumptions in connection with a research process
- critically review research plans based on general scientific criteria
- adhere to a critical approach to theories, literature and sources of knowledge
The course provides an introduction and in-depth understanding of key concepts and perspectives in the field of information systems research. The student is introduced to the basic concepts of knowledge theory, such as ontology, epistemology and paradigm. The knowledge products of research processes (new or improved IT artefact or IT-related practices, new or further developed theory, new or advanced development techniques / methodology, deep understanding based on case studies, explanations of phenomena, behavior and their relationships, knowledge of new phenomena, or knowledge based on critical analysis) are explained. Different research approaches (quantitative, experimental, design-oriented, qualitative), data collection methods (interviews, observations, questionnaires, document studies, focus groups), as well as methods of data analysis (qualitative data analysis, quantitative data analysis) are presented and discussed in detail.
Lectures, seminars, laboratory excercises, and supervision.
The course is examined through assignments, seminars, laboratory exercises, and compulsory attendance.
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator or a decision by the department's working group for study matters.
(applies from Spring 2019, version 2)