Course content

This PhD course is similar to the MSc course IT3010 but has more advanced requirements for PhD students. The course is run every spring. The course will give insight into the most important areas within empirical research methods in IT and digitalization. Challenges of empirical research, research design, data generation and analysis 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.

Learning outcome

• Knowledge: The candidate will acquire knowledge of:

• Basics of design of scientific studies.
• Principles for selection of data generation and analysis methods.
• Basic definitions of empirical research in IT and digitalization.

Skills: The candidate will acquire skills on:

• Planning and conducting research projects.
• Collecting and analyzing research data.
• Foreseeing and reducing threats to validity of research designs.
• Ethical issues related to empirical research in IT and digitalization, and how to address them.

General competence: The candidate will acquire competence on:

• Critically evaluating the quality of empirical studies in IT and digitalization.
• Conduct empirical 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 and revision, and presentation in conference.

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.