ASDK20008U Co-curricular written assignment
Volume 2021/2022
Education
Elective course offered by MSc programme in Social Data Science at University of Copenhagen.
The course is only open for students enrolled in the MSc programme in Social Data Science.
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.
Learning Outcome
At the end of the course, students are able to:
Knowledge
- 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.
Skills
- Apply relevant theories and methods on a selected area of study.
- Independently summarize and analyse a topic in a well-structured written report.
Competencies
- 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.
Teaching and learning methods
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.
Workload
- Category
- Hours
- Guidance
- 3
- Exam Preparation
- 203
- Total
- 206
Feedback form
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Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Written assignmentThe 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.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
- Re-exam
The second and third examination attempts are conducted in the same manner as the ordinary examination.
Criteria for exam assesment
The exam will be assessed on the basis of the learning outcome (knowledge, skills and competencies) for the course.
Course information
- Language
- English
- Course code
- ASDK20008U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 semester
- Placement
- Autumn
- Study board
- Social Data Science
Contracting department
- Social Data Science
Contracting faculty
- Faculty of Social Sciences
Course Coordinators
- Friedolin Merhout (8-6a7169766c73797844777367326f7932686f)
Saved on the
15-12-2022