Empirical Research Methods in Computer Science (ERMCS)
Course content
This course teaches students to design and evaluate empirical research in computer science. Students will acquire knowledge of central ideas about research quality and an understanding of how research is planned, conducted and analysed. On completion of the course, students will be prepared to select and use research methods in their projects (e.g. master's theses and dissertations) and to read and use the results of empirical research. Participants will also learn to critically evaluate results and sources of bias/error in the research of others. The course focuses on empirical research in all areas of computer science, including software engineering, human-computer interaction, natural language processing, graphics, and artificial intelligence.
MSc Programme in Computer Science
MSc Programme in Computer Science with a minor subject
Knowledge of
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Notions of research quality, including validity, credibility, reliability, transparency, ethics, and integrity
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Types of empirical research methods, including observation, experiments, field studies, interviews, surveys, archival research, crowdsourcing
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Tradeoffs in research, including between realism, precision, and generalizability
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Different research traditions and their underlying philosophies
Skills in
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Formulating research questions
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Planning and analyzing research of the types noted above
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Analysis and representation of qualitative and quantitative data
Competences in
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Analyzing research papers with respect to their quality and choice of method
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Interpreting and drawing conclusions from quantitative and qualitative data
The aim of the course is to give participants practical and theoretical insight into research methods. Practical insight is obtained through compulsory assignments on planning or analysis of empirical research. The theoretical insight is obtained through the reading and discussing selected papers and book chapters.
Selected papers. See Absalon when the course is set up.
Academic qualifications equivalent to a BSc degree are recommended.
Written and oral feedback on assignments, oral feedback on oral presentations.
As an exchange, guest and credit student - click here!
Continuing Education - click here!
PhD’s can register for MSc-course by following the same procedure as credit-students, see link above.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Continuous assessment
- Type of assessment details
- Continuous assessment of 5 written assignments. All assignments must pass. The final grade is based on an overall assessment of the assignments.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
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Oral examination, 20 minutes (including grading) without preparation.
Criteria for exam assessment
See Learning Outcome
Single subject courses (day)
- Category
- Hours
- Lectures
- 32
- Preparation
- 78
- Project work
- 96
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NDAK25001U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 1
- Schedulegroup
-
C
- Capacity
- No limitation – unless you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
- Studyboard
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Contracting faculty
- Faculty of Science
Course Coordinator
- Kasper Hornbæk (4-7a7082774f73783d7a843d737a)
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Kursusinformation for indskrevne studerende