Examination arrangement

Course content

The course will give insight in the most important challenges for research and innovation methods in computer science, as well as theories of science. Challenges of research design and presentation of results will be covered. The course gives insight in the most used empirical research methods: Case studies, design science and surveys, with emphasis on qualitative methods. The course will also teach students to conduct methodological hypothesis testing in a given market.

Learning outcome

Knowledge: The candidate will get knowledge of: - Basics of design of scientific studies. - Principles for selection of data collection and analysis methods. – Basic definitions of research-based innovation.

Skills: The candidate will acquire skilled on: -Planning and conducting research projects. - Collecting and analyzing research data. - Foreseeing and reducing threats to validity of research designs.

General competence: The candidate will get competence on: - Critically evaluate the quality of qualitative studies in computer science. - Conduct empirical studies.

Learning methods and activities

Lectures, self-study, group-based individual assignments.

Further on evaluation

Retake of the course will require new participation/deliverables in all activities.

Specific conditions

Recommended previous knowledge

This course is designed for students that require fundamental understanding and skills on research-based innovation approaches and methods in order to conduct research for their master thesis. A Bachelor degree in informatics or a similar background is recommended.

Required previous knowledge

No other courses required in order to take this course.

Course materials

Articles and book which will be presented at the start of the semester.