• Bachelor of Science in Engineering (at least 180 credits) or a bachelor’s degree in computer science or related fields such as computer engineering, computer and information science, software engineering, informatics, telecommunications or electrical engineering.
• At least 15 credits in programming.
• Equivalent of English 6 in secondary school.

This course is part of the Computer Science: Internet of Things, Masters Programme and the main field of study, computer science, and may be included in the degree requirements for the master’s degree (120 credits) in computer science.

The course includes the following:

• Formulation of scientific problems and hypotheses
• Selection and review of relevant literature
• Research methods in computer science
• Approach to the selection and collection of data
• Data analysis, including statistical methods
• Oral and written presentation of research studies
• Research ethics

Knowledge and understanding
To pass the course, the student must be able to:

1. Account for different scientific methods in computer science
2. Describe different approaches to the selection and collection of relevant data
3. Describe different approaches to data analysis
4. Account for ethical aspects related to research in computer science

Competence and skills
To pass the course, the student must be able to:

5. Formulate scientific problems and hypotheses
6. Given a scientific problem, review a selection of literature relevant to the problem and present this literature
7. Create a proposal for a research study, including the choice of scientific method and data, as well as the methods for data collection and analysis
8. Present the proposed research study in a scientific manner, both orally and in writing.

Judgement and approach
To pass the course, the student must be able to:

9. Critically reflect on the choice of research methods, data collection and analysis, in relation to various options, whilst considering ethical aspects.

Lectures, seminars and independent study.

Assessment of student performance is based on:

• Written and oral assignments (4 credits, assessed according to UG) - Learning outcomes 5, 6, 7, 8, 9
• Written examination (3.5 credits, assessed according to UA) - Learning outcomes 1, 2, 3, 4, 7, 9

For an overall passing grade, a pass must have been achieved in both the assignments and the exam.

The final grade is based on the exam.

Referenslitteratur:

• Berndtsson, M., Hansson, J., Olsson, B., & Lundell, B. (2008). Thesis projects: A Guide for Students in Computer Science and Information Systems. London: Springer.
• Oates, B.J., (2005). Researching Information Systems and Computing. London: Sage Publications.
• Wohlin, C., Runeson, P., Höst, M., Ohlsson, M.C., Regnell, B., & Wesslén, A. (2012). Experimentation in Software Engineering. Berlin: Springer.
• Zobel, J. (2015). Writing for Computer Science - The Art of Effective Communication. London: Springer

Ytterligare vetenskapliga artiklar tillhandahålls av läraren under kursen.

Malmö University provides students who participate in, or who have completed a course, with the opportunity to express their opinions and describe their experiences of the course by completing a course evaluation administered by the University. The University will compile and summarise the results of course evaluations. The University will also inform participants of the results and any decisions relating to measures taken in response to the course evaluations. The results will be made available to the students (HF 1:14).

If a course is no longer offered, or has undergone significant changes, the students must be offered two opportunities for re-examination based on the syllabus that applied at the time of registration, for a period of one year after the changes have been implemented.

If a student has a Learning support decision, the examiner has the right to provide the student with an adapted test, or to allow the student to take the exam in a different format.

The syllabus is a translation of a Swedish source text.