Academic internship (30 ECTS)
Course content
The purpose of the academic internship is to provide students with an opportunity to get hands-on-experience for research and/or commercial or social purpose. Through a formalized attachment to a company, public institution, research institute or similar the student will perform tasks and at the same time be able to apply academic skills in a practical context.
Students are only allowed to pass this course once in the course of
the Master’s degree programme.
Workload:
Extent of working hours 30 ECTS:
Working hours at the internship site: 650 hours
Social data scientific assignment, including preliminary
considerations: 175 hours
Total: 825 hours
The course is only open for students enrolled in the MSc programme in Social Data Science.
NOTE: This is the course description for Academic Internship 30 ECTS. The information in this course description is ONLY applicable to you if you are registered for 30 ECTS. If you are registered for 15 ECTS, please see the course description here: https://kurser.ku.dk/course/asdk20011u/2023-2024
Learning outcome
At the end of the academic internship, students are able to:
Knowledge
- Critically and independently reflect upon and discuss the applied social data science theories and methods to a chosen topic.
- Account for the validity, scope and usefulness of relevant data as part of the social data scientific assignment.
Skills
- Apply and discuss for relevant theories and methods in a practical context.
- Independently summarize and analyse a topic in a well-structured written assignment.
- Carry out and implement social data science-based analysis in a practical context
Competencies
- Independently identify and select relevant theories to examine a practical case
- Gauge and evaluate the relevance of methods for collecting and analysing data for practical cases.
- Formulate a comprehensive research design to investigate the chosen case
- Independently analyse and apply academic literature relevant to a specific problem statement
This course is conducted primarily as an independent study.
Internal supervisor
Students enter into supervision agreement 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. The supervisor is responsible for approving
and monitoring the academic internship, and for ensuring that the
learning outcome is achieved.
External supervisor
Students must be assigned an external supervisor employed at the
place of the academic internship. The external supervisor
continuously develops and evaluates the academic internship
together with the student in accordance with the expected learning
outcome.
In the course of the academic internship, the student will:
On one occasion, submit preliminary considerations regarding their
academic internship report and receive feedback from the
supervisor, as well as submit an academic internship report for the
exam.
Students will also:
On two occasions, submit preliminary considerations regarding their
social data scientific assignment and receive feedback from the
supervisor, as well as submit a social data scientific assignment
for the exam.
- ECTS
- 30 ECTS
- Type of assessment
-
Portfolio
- Type of assessment details
- Academic internship report.
Social data scientific assignment
Social data scientific assignment submitted individually, maximum 20 standard pages.
The exam is graded according to the Danish 7-point grading scale. The exam is graded by the internal supervisor. - Exam registration requirements
-
All students must on one occasion submit considerations regarding their academic internship report to the internal supervisor, and document that the number of working hours has been completed (e.g. academic internship contract).
Moreover, students must on two occasions submit considerations regarding their social data scientific assignment to the internal supervisor. - 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 assessment
The exam will be assessed on the basis of the learning outcome (knowledge, skills and competencies) for the course.
- Category
- Hours
- Practical Training
- 650
- Exam
- 175
- English
- 825
Kursusinformation
- Language
- English
- Course number
- ASDK20012U
- ECTS
- 30 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
- Friedolin Merhout (8-6b726a776d747a794578746833707a336970)
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