Course syllabus spring 2025
Course syllabus spring 2025
Title
Master’s thesis in IoT (two year)
Swedish title
Examensarbete i IoT (master, två år)
Course code
DA647E
Credits
30 credits
Grading scale
UA / Excellent (A), Very Good (B), Good (C), Satisfactory (D), Pass (E) or Fail (U)
Language of instruction
English
Decision-making body
Faculty of Technology and Society
Establishment date
2022-05-03
Syllabus approval date
2022-05-03
Syllabus valid from
2025-01-20
Entry requirements
- Bachelor's degree in engineering (at least 180 credits) in computer science or related fields such as computer science, computer and information science, software engineering, informatics, telecommunications or electrical engineering.
- At least 15 credits in programming, system development or equivalent.
- English 6 or equivalent.
- At least 75 passed credits in the Computer Science: Internet of Things, Master's Programme including Research Methodology DA645E, 7.5 credits
Level
Advanced level
Main field
Computer Science
Progression level
A2E
Progression level in relation to degree requirements
The course is part of the Computer Science: Internet of Things, Master's Programme and the main field of study, computer science, and may be included in the degree requirements for a master's degree (120 credits) in computer science.
Course objectives
The students will further develop their critical thinking, argumentation and problem-solving skills by carrying out an independent scientific project in the field of computer science. The project will have a particular focus on the Internet of Things, including societal aspects such as accessibility and equality
Course contents
The course consists of three parts:
- problem definition and project plan,
- essay project and
- opposition of another Master's thesis.
The thesis project has two stages:
- conducting the project and documenting it in writing (Master's thesis), and
- presenting and defending the thesis orally.
Learning outcomes
Knowledge and understanding
To pass the course, the student should be able to:
1. Account for and explain different aspects in at least one area within computer science with a special focus on the Internet of Things.
2. Account for the research process and its planning
Skills and abilities
To pass the course, the student should be able to:
3. Independently identify, formulate and handle complex problems within the scope of the individual project
4. Plan and carry out research and development projects within given time frames
5. Describe a research project's contribution to a field of knowledge
6. Actively search for and analyse relevant information about a given research problem
7. Select a research method for a scientific problem
8. Apply research methods to a scientific problem
9. Present the results of their own research project in a scientific manner, both orally and in writing
10. Communicate the results of research projects to different target groups.
Judgement and approach
To pass the course, the student should be able to:
11. Assess and analyse relevant research questions of importance to computer science
12. Critically analyse a scientific report and identify its main strengths and weaknesses, based on both technical and societal aspects, whilst including ethics, sustainability and gender equality
13. Argue about the suitability of a particular research method for a scientific problem.
Learning activities
The teaching is project-based and adapted to the student's previous knowledge, abilities and experiences. The main learning activities are independent projects, supervision and seminars. The student will also present orally and act as opponent for another Master's thesis.
Assessment
To achieve a passing grade, all three parts of the course must be completed and passed.
- project plan (3 credits, UG) – intended learning outcomes 2, 3, 4, 5, 6, 7, 11
- thesis (25 credits, UA) – intended learning outcomes 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13
- oral presentation (1 credit, UG) – intended learning outcome 12
- written and oral opposition (1 credit, UG) – intended learning outcome 12
Grades for each part are determined by the examiner through the use of criteria in an assessment matrix that covers the different learning outcomes for the course.
The final grade for the course is based on the grade for the thesis and oral presentation.
Course literature
- Dawson, C. (2015). Projects in computing and information systems. A student’s guide (3rd edition), Pearson
- Oates, B.J. (2005). Researching Information Systems and Computing. Sage Publications, UK.
- Zobel, J. (2004). Writing for Computer Science – The art of effective communication. 2nd ed., Springer, UK.
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.
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.