Data Collection, Processing and Analysis (15 ECTS)
The purpose of this course is to provide students with an opportunity for collecting and working with data that is relevant in relation to the Master’s thesis. The course consists in participating in a data collection project such as running an experiment or scraping data from the internet. This includes preliminary processing and basic analysis.
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 only open for students enrolled in the MSc programme in Social Data Science.
NOTE: This is the course description for Data Collection 15 ECTS. The information in this course description is ONLY applicable to you if you are registered for 15 ECTS. If you are registered for 30 ECTS, please see the course description here: https://kurser.ku.dk/course/asdk20010u/2023-2024
Learning outcome 15 ECTS:
At the end of the course, students are able to:
- Describe the choice of method for doing research within social data science and the knowledge it produces.
- Define theoretical terms and research themes that can be used to understand relevant social data science problems within an empirical material.
- Carry out a smaller data collection, taking point of departure in an independent problem formulation.
- Organize the empirical material systematically, taking into consideration research ethics.
- Reflect critically on the methodological and analytical process of collecting data.
- Assess problem statement and research questions in relation to the empirical material.
This course is conducted primarily as an independent study. At
the beginning of the semester, the Head of Studies assigns students
into supervision clusters.
In the course of the semester students must participate in workshops, organised by the cluster supervisor, focusing on presenting their social data science material and analysis. The output from the workshops are portfolio items.
- 15 ECTS
- Type of assessment
- Type of assessment details
- Written exam (portfolio) submitted individually or in groups.
Students in the same group must be enrolled for the same number of
ECTS. The portfolio exam must contain all the portfolio assignments
handed in during the course and an overview of the collected data
The written portfolio assignment must be no longer than 10 pages when written by 1 student and 15 pages when written by two students, who write together.
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
Criteria for exam assessment
The exam will be assessed on the basis of the learning outcome (knowledge, skills and competencies) for the course.
- Exam Preparation
- Course number
- 15 ECTS
- Programme level
- Full Degree Master
- Social Data Science
- Social Data Science
- Faculty of Social Sciences
- Kristoffer Langkjær Albris
Department of Anthropology
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