TJTJ7720 Theory in Information Systems (3 cr)

Study level:
Postgraduate studies
Grading scale:
Pass - fail
Responsible organisation:
Faculty of Information Technology
Curriculum periods:
2020-2021, 2021-2022, 2022-2023, 2023-2024

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This course describes scientific theory in information systems, and how it is discovered


0) Introduction

1) Philosophers' logical reconstructions for philosophical purposes and how they were confused with "real" theories in IS theory

2) The (once) received view of scientific theory and its impact on scientific theory in IS

2.1. Theories as laws in IS

2.2. Theories as inferential relationships in IS

2.3. Truth versus idealized accounts

3. Theoretical versus Empirical

3.1. Theoretical versus Empirical in Philosophy of Science

3.2. Theoretical versus Empirical in IS

3.3. Problems of Requiring "Theoretical contribution" and the value of "Empirical" contribution in IS

4. The deductive-nomological (D-N) model of explanations

4.1. Basics idea, including explanation versus prediction, and Critique

4.2. D-N confusions in IS and why IS model of explanation is not D-N

4.3. IS and Covering Theory Model of explanations (CTM)

4.3.1. inductive-qualitative CTM of explanations

4.3.2 probabilistic-statistical CTM of explanations

5. Mechanism-based explanations (MBEs)

5.1. History of mechanisms-based explanations

5.2. Modern mechanism accounts as alternative to laws-based explanations

5.3. Common misunderstandings of mechanisms in IS.

5.3.1 why and how explanations and mechanisms

5.3.2 laws and causal confusions regarding MBEs

5.4 the ontic conception of explanations

5.5 Deliberate misrepresentations in MBEs

5.6 Naturalism versus critical realism in MBEs

6. On theory characteristics preferences in IS

6.1. Should there be a premium on IS specific theories?

6.2. Theory scope: why a wider theory scope is not necessarily better than a narrow scope?

7. Merton's middle range theories reconsidered and implications for IS

8. Mohr's variance and process theories

8.1. basic ideas and critique

8.2. How "process" or "variance" is different from MBEs

9. Stage Theorizing

9.1 what makes a theory a stage theory?

9.2. Is stage an empirical or theoretical?

9.3. stage as idealization

9.4. Discovering and testing stage theories

10. Hypothetico-deductive method

10.1 "H-D" in IS

10.2. H-D in the philosophy of science

10.3. why H-D in IS is not a H-D method?

10.4. hypothetico-inductive-qualitative method

10.5. hypothetico-inductive-statistical method

11. Inductive methods

Learning outcomes

A basic understanding of different fundamental types of scientific theories and how they are discovered

Description of prerequisites

A basic course in the philosophy of science

Completion methods

Method 1

Evaluation criteria:
In person participation (80 %) of the lectures.
Select all marked parts
Parts of the completion methods

Participation in teaching (3 cr)

Participation in teaching
Grading scale:
Pass - fail
No published teaching