Learning outcome

After successfully completing the course, the candidate will have achieved the following learning outcomes defined in terms of knowledge, skills and general competence.

The candidate:

- Has knowledge of the fundamental aspects of scientific work

- Has knowledge of key scientific and ethical requirements and can discuss key issues related to these requirements

- Can explain different research traditions and methods of social science research

- Understands key statistical concepts and statistical representation of data and can use this knowledge to read and interpret quantitative data

- Can apply knowledge of scientific theory, research ethics, research traditions and methodology in planning his/her own thesis

- Can use feedback on their Master’s thesis outline for further work on his/her own Master’s thesis

- Can apply knowledge of academic writing in working on his/her own thesis

Course Description

The course focuses on knowledge of science theory, scientific and ethical requirements, various research traditions and different methodological approaches. Students will acquire a theoretical, methodological and practical foundation for working on their Master’s theses. This requires insight into epistemological thinking, capacity for critical reflection and knowledge of social science methodology. Students will also be able to assess the quality, validity and relevance of research work. They will develop the ability to understand and interpret basic statistics and statistical representation of data; they will also become familiar with the application process for obtaining approval of a Master’s thesis.

The course covers the following topics:

- Science theory and research ethics

- Research methodology

- Statistics

Teaching and Learning Methods

The course includes different teaching and learning methods designed to enhance students’ learning and create an active learning environment. It includes lectures, discussions, seminars, discussion groups, feedback on assignments, student presentations and individual work. The workload corresponds to that of a full-time course of studies.

All the seminars are mandatory, as are the assignments outlined in the course plan. Students must meet the attendance requirement of at least 75% of the obligatory seminars and all assignments must be approved before students will be allowed to sit the final examination. The seminars and assignments have been made obligatory to ensure that students will be able to develop the foundation skills required for studying the Master’s degree courses and writing a Master’s thesis.

Assessment Methods

Course code: 981-E4: Scientific Theory, Research Methodology and Ethics

Students must submit a Master’s thesis outline that is awarded a passing grade in order to gain a passing grade for the course; students will then be assigned a supervisor and undertake course 5: Master’s thesis.

After completing the statistics course, the student will submit an individual assignment which will be assessed on a pass/fail basis. The assignment must be passed in order for the students to sit the examination.

Individual one-week take-home assignment assessed with a grade (A-F).

The grade will be entered separately on the diploma.

Students may not begin course 5 before courses 1-4 have been awarded passing grades.

Minor adjustments may occur during the academic year, subject to the decision of the Dean