Entry requirements

• CD163A Independent Project for Master's Degree in Computer Science and Engineering (15 credits)
• CM152A Mathematical Statistics (7.5 credits)

Progression level in relation to degree requirements

The course is part of the degree requirements for a Master of Science in Engineering in Computer Science and Engineering (specialisation Applied Data Science)

Course contents

The aim of the course is for the student to acquire knowledge of research methodology in computer science and engineering. It also aims to enable the student to develop their ability to select and critically reflect on different research designs in this field.

The course includes the following elements:

• Formulation of scientific problems and hypotheses
• The theoretical foundations of computer science, including Turing machines, the Church-Turing hypothesis, the halting problem and complexity theory
• Selection and review of relevant literature
• Research methods relevant to computer science
• Approaches to data selection and collection
• Data analysis, including statistical methods
• Oral and written presentation of research studies
• Research ethics

Learning outcomes

Knowledge and understanding

Upon completion of the course, the student shall be able to:

1. describe and demonstrate understanding of the theoretical foundation and different scientific methods in computer science,

2. describe and demonstrate an understanding of different approaches to the selection and collection of relevant data,

3. describe and demonstrate understanding of different approaches to analysing data, and

4. describe and demonstrate understanding of ethical aspects related to computer science research.

Competence and skills

Upon completion of the course, the student shall be able to:

5. formulate scientific problems and hypotheses,

6. given a scientific problem, select and review literature relevant to the problem and present this literature,

7. design a research study, including the choice of scientific method and data, as well as data collection and data analysis, and

8.present a research study in a scientific manner, both orally and in writing.

Judgement and approach

Upon completion of the course, the student shall be able to:

9. critically reflect on the choice of research methods, data, data collection and data analysis, in relation to alternative choices and taking ethical aspects into account.

Learning activities

Lectures, seminars and self-study.

Assessment

The following are required to pass the course

• Passing grades on written and oral assignments (4 credits, Pass/Fail) (Intended learning outcomes 5–9)
• Written examination (3.5 credits, UA) (Intended learning outcomes 1–4, 7, 9)

For all assessments, the materials must be presented in a manner that makes it possible to discern individual performance.

The final grade corresponds to the grade of the written examination.

Course literature

Reference literature:

• 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.
• Sipser, M. (2013) Introduction to the Theory of Computation. Cengage.
• 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.

Scientific articles provided by the teacher during the course.

Course evaluation

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).

Interim rules

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. The syllabus is a translation of a Swedish source text.

Additional information

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.