At least a passing grade on the courses:

• Professional Interpersonal Communication in Computer Science and Media Technology
• Designing and Evaluating Innovation

Alternative, at least a passing grade on the courses:

• Professional Interpersonal Communication in Computer Science and Media Technology
• Theorizing Media Technology
• Innovation and Strategic Thinking

The course is part of the main field of computer science and may be included in the degree requirements for a master’s degree in computer science.

The course is alternatively part of the main field of media technology and may be included in the degree requirements for a master's degree in media technology.

The course has three primary objectives:

• The student will develop and deepen their knowledge and skills in research methodology relevant to their subject area, as well as information search and formulation of research problems and hypotheses.
• The student will develop and deepen their knowledge and skills in methods for analysing and visualising empirical data.
• The student will develop their knowledge regarding the choice of methodology in relation to research problems, taking into account research ethics.

**Knowledge and understanding
**After completing the course, the student should be able to:

1. demonstrate in-depth methodological knowledge in the subject area, including choice of research focus, strategies for data collection, and choice of methodology and approach
2. collect, analyse and visualise data in practice, in a scientific context
3. apply in-depth knowledge of the challenges and opportunities of different types of data, collection techniques and data quality, especially in a digital context.

**Skills and abilities
**To pass the course, the student must be able to:

4. link concepts and insights from theory to applied analytical problems
5. identify and formulate research questions and choose adequate methodology to address these questions
6. identify and plan quantitative, qualitative and mixed methods based on well-defined scientific and strategic objectives
7. carry out collection, analysis and visualisation of data, taking into account the application of different validity and reliability principles and tools
8. critically reflect on the consequences of the choice of research methodology as well as data analysis/data visualisation method.

Judgement and approach
After completing the course, the student should demonstrate the ability to:

10. understand the possibilities and limitations of science, its role in society and people's responsibility for how it is used
11. argue how different methods of data collection and analysis can be used to achieve a deeper and more complex understanding of phenomena
12. identify their need for further knowledge and to take responsibility for their knowledge development.

The course consists of lectures, workshops, seminars and laboratory work, as well as self-study, project work and supervision.

Grading is based on oral and written examination, including active participation, throughout the following
components:

• Seminars (2,5 credits) – UG – examines learning outcomes 1, 4, 5, 8
• Laboratory work (2,5 credits) – UG – examines learning outcomes 2, 3, 7, 11
• Home assignments (5 credits) – UA – examines learning outcomes 2, 8, 9, 11,12
• Project work (5 credits) – UA – examines learning outcomes 1-12

Requirement for a passing final grade (A-E): a passing grade on every course component.

The final grade is weighted in accordance with:

• Project work: 1
• Home assignments: 2

• Björk, L., Räisänen, C. & Björk C. M. (2003). Academic writing: A University Writing course. 3 ed. Lund: Studentlitteratur.
• Cresswell, J. W. & Cresswell, J. D. (2018). Research Design: Qualitative, quantitative and mixed methods approaches (5 ed.). London: Sage.
• Kirk, A. (2016). Data Visualization. Los Angeles: Sage Publications.
• O’Reilly, K. (2012). Ethnographic Methods. 2nd edition. London & New York: Routledge.
• Ridley, D. (2008). The literature review: A step-by-step guide for students. London: Sage.
• Rogers, R. (2019). Doing Digital Methods. Los Angeles: Sage Publications.
• Salganik, M. J. (2017). Bit by Bit: Social Research in the Digital Age. Princeton: Princeton University Press.
• Wilke, Claus O. (2018). Fundamentals of Data Visualization, O'Reilly Media, USA, [Elektronisk resurs].

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.