STR402A Methodology for Master Thesis (E/N)

• Topics

  The purpose of the course is to develop the methodological skills required to write a master’s thesis. The course consists of several assignments designed to introduce students to the different stages of the research process. A core component of each session is the exploration of how Artificial Intelligence can be used effectively and ethically within these specific stages. Topics include:

  • Choosing a research topic
  • Formulating research questions
  • Collecting and critically reviewing literature
  • Selecting a research design
  • Collecting and analyzing qualitative and quantitative data
  • Research quality
  • Research ethics
  • Academic writing
  • Presenting research

• Learning outcome

  Knowledge

  • Formulate a viable research question for a master's thesis.
  • Explain the connection between philosophical traditions and research design.
  • Describe various qualitative and quantitative research methods.
  • Discuss the strengths and weaknesses of Artificial Intelligence within research workflows.

  Skills

  • Evaluate academic sources relevant to a specific research topic.
  • Design a methodological plan for a master's thesis project.
  • Justify methodological choices in relation to a specific research question and philosophical tradition.

  General Competence

  • Assess ethical dilemmas at each stage of the research process.
  • Reflect on how AI tools impact academic integrity and research quality.
  • Communicate the methodological choices for a proposed research project.

• Teaching

  The course consists of on-campus lectures combining teaching and assignments on key topics in the research process.

  Throughout the course, students work in groups of 2-3 to develop a project proposal for a planned or hypothetical master’s thesis. The proposal follows the progress of the course, and supervision is provided along the way.

• Compulsory Activity

  The groups (2-3 students) must submit a final project proposal and present it orally. Both the written submission and the oral presentation are compulsory activities (pass/fail) and must be approved in order to sit the exam.

  Spring: The project proposal may be submitted and presented in either Norwegian or English.

  Autumn: The project proposal must be submitted and presented in English.

• Assessment

  Digital school exam (6 hours), weight 100 %.

  Spring: The school exam is given in Norwegian, and the exam answer may be written in either Norwegian or English.

  Autumn: The school exam is given in English, and the exam answer must be written in English.

  The course requirements and assessment scheme have been changed starting spring 2026. Previously approved course requirements are no longer valid.

• Grading Scale

  A - F

• Literature

  Saunders M., Lewis, P., & Thornhill, A. (2023). Research methods for business students (9th ed.). Pearson Education.

  In addition, the teaching will also draw on academic articles that can be downloaded via Leganto from the course page on Canvas.

• Permitted Support Material

  One bilingual dictionary (category 1) is permitted during the exam.

  All in accordance with Supplementary provisions to the Regulations for Full-time Study Programmes at the Norwegian School of Economics Ch.4 Permitted support materialhttps://www.nhh.no/en/for-students/regulations/https://www.nhh.no/en/for-students/regulations/ and https://www.nhh.no/en/for-students/examinations/examination-support-materials/https://www.nhh.no/en/for-students/examinations/examination-support-materials/

  Regarding the use of artificial intelligence, the same guidelines apply as for the master’s thesis: https://www.nhh.no/en/for-students/masters-thesis/guidelines-for-use-of-ai-tools-in-the-work-on-master-theses/https://www.nhh.no/en/for-students/masters-thesis/guidelines-for-use-of-ai-tools-in-the-work-on-master-theses/