Course content

This PhD course will teach you about the most important areas within empirical research methods in digitalization. Aspects of empirical research, research design, data generation and analysis, evaluation, and dissemination will be covered. The course gives insight into the most used empirical research methods: Case studies, design science, surveys, and experiments. The course provides an introduction to research ethics and managing user data, writing and reviewing research articles, and doing peer reviews. The course is offered every spring. The course is built on and taught in parallel to IT3010.

Learning outcome

Knowledge: The candidate will acquire knowledge of:

• Empirical research in digitalization.
• The main principles for designing empirical research studies.
• The main principles for selecting and applying data generation and analysis methods.
• Ethical issues related to empirical research in digitalization, and how to address them.
• Best practices for reporting research results.

Skills: The candidate will acquire skilled on:

• Planning empirical research projects.
• Ethically conducting empirical research projects.
• Evaluating empirical research.
• Reporting, presenting, and otherwise disseminating research results.

General competence: The candidate will get competence on:

• Critically evaluate the quality of research studies in digitalization.
• Conduct empirical research studies.

Learning methods and activities

Lectures, self-study, individual assignments. Students will conduct a complete cycle of research, including planning, data generation and analysis, paper writing, peer review, paper revision, and presentation in conference.

Compulsory assignments

• Presentation

Recommended previous knowledge

MSc in computer science, information systems or software engineering.

Required previous knowledge

None. You cannot take this course if you already have taken IT3010 or equivalence.

Course materials

Relevant papers and book chapters.

Credit reductions