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 allowed to write a maximum of one assignment of this kind during their master’s programme. 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 allowed to write a maximum of one assignment of this kind during their master’s 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.
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.
Competences:
- 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 postdoc. 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, as well as one meeting mid-way in the process where the student will receive feedback on a draft of the assignment, or parts of it. All assignments must be submitted no later than in the end of the semester where the registration date is made. The exact date is given by the exam administration. The assignment must be submitted in Digital Exam.
When registered you will be signed up for exam.
- Full-degree students – sign up at Selfservice on KUnet
The dates for the exams are found here Exams – Faculty of Social Sciences - University of Copenhagen (ku.dk)
Please note that it is your own responsibility to check for overlapping exam dates.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Home assignment
- Type of assessment details
- The home assignment may be written individually or in groups.
The length of the written home assignments depends on the prescribed number of ECTS. The requirements for the number of pages for co-curricular written assignments are as follows:
2.5 ECTS = 5 standard pages + 1 standard page per extra student
5 ECTS = 10 standard pages + 2 standard pages per extra student
7.5 ECTS = 15 standard pages + 3 standard pages per extra student - Examination prerequisites
-
To be eligible for exam, the projects must be pre-approved by course responsible(s) at the start of the third semester
- Aid
- All aids allowed
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
- Exam period
-
Exam information:
The examination date can be found in the exam schedule here
The exact time and place will be available in Digital Exam from the middle of the semester.
- Re-exam
-
The second and third examination attempts are conducted in the same manner as the ordinary examination.
Reexam info:
The reexamination date/period can be found in the reexam schedule here
Criteria for exam assessment
Students are assessed on the extent to which they master the learning outcome for the course.
To obtain the top grade “12”, the student must with no or only a few minor weaknesses be able to demonstrate an excellent performance displaying a high level of command of all aspects of the relevant material and can make use of the knowledge, skills and competencies listed in the learning outcomes.
To obtain the passing grade “02”, the student must in a satisfactory way be able to demonstrate a minimal acceptable level of the knowledge, skills and competencies listed in the learning outcomes.
- Category
- Hours
- Guidance
- 3
- Exam Preparation
- 203
- English
- 206
Kursusinformation
- Language
- English
- Course number
- ASDK20008U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 semester
- Placement
- Autumn And Spring
- Studyboard
- Social Data Science
Contracting department
- Social Data Science
Contracting faculty
- Faculty of Social Sciences
Course Coordinator
- Kristoffer Langkjær Albris (17-70776e7879746b6b6a7733667167776e7845787469667833707a336970)
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