Co-curricular written assignment

Course content

Co-curricular written assignments are an option available to students who want to enhance their knowledge and competencies in a particular field within social data science.

Students are only allowed to pass this course once in the course of the Master’s degree programme.


Elective course offered by MSc programme in Social Data Science at University of Copenhagen.


The course is offered as 2,5 ECTS, 5 ECTS or 7,5 ECTS.


The course is only open for students enrolled in the MSc programme in Social Data Science.

Learning outcome

At the end of the course, students are able to:


  • Critically and independently reflect upon and discuss the applied social data science theories and methods within the chosen area of study.
  • Account for the validity, scope and usefulness of relevant data as part of the project.



  • Apply relevant theories and methods on a selected area of study.
  • Independently summarize and analyse a topic in a well-structured written report.



  • Independently identify and select relevant theories to examine a chosen area of study.
  • Independently select, analyse and apply academic literature relevant to a specific problem statement.

Students enter into supervision agreements with one of the full-time teachers who are involved in the Master’s degree programme in Social Data Science or an affiliated part-time lecturer, a PhD -student or a post doc. Supervision of co-curricular written assignments is limited to initial assistance with literature suggestions and/or the structuring and scope of the analysis and contents in the course of one meeting.

7,5 ECTS
Type of assessment
Written assignment
Type of assessment details
The assignment may be written individually or in groups. The length of the co-curricular written assignment follows the general length prescriptions for written exams, cf. section 5 in the programme curriculum.

See section 6.8.2 in the programme curriculum for the specific length prescribed to the number of ECTS you are taking.

ChatGPT and other large language model tools are permitted as a dedicated source, meaning text copied verbatim needs to be quoted, the tool cited, and generally the specific use made of them needs to be described in the submitted exam.

Marking scale
7-point grading scale
Censorship form
No external censorship

The second and third examination attempts are conducted in the same manner as the ordinary examination.

Criteria for exam assessment

The exam will be assessed on the basis of the learning outcome (knowledge, skills and competencies) for the course.

  • Category
  • Hours
  • Guidance
  • 3
  • Exam Preparation
  • 203
  • English
  • 206


Course number
7,5 ECTS
Programme level
Full Degree Master

1 semester

Autumn And Spring
Social Data Science
Contracting department
  • Social Data Science
Contracting faculty
  • Faculty of Social Sciences
Course Coordinator
  • Friedolin Merhout   (8-686f67746a71777642757165306d7730666d)
Saved on the 10-01-2024

Are you BA- or KA-student?

Are you bachelor- or kandidat-student, then find the course in the course catalog for students:

Courseinformation of students