Education Directory
PÅ SVENSKA
Malmö University
Course syllabus autumn 2023
Course syllabus autumn 2023
Title
Research Methods, Data Analysis, and Communication
Swedish title
Forskningsmetodik, dataanalys och kommunikation
Course code
DA625E
Credits
15 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
Syllabus approval date
2021-05-19
Syllabus valid from
2021-08-30
Entry requirements
  1. Bachelor's degree or equivalent of at least 180 credits in the subject of computer science or related and relevant subjects. Examples of such subjects include informatics, computer and information science, information systems, interaction design, human-computer interaction and media technology.
  2. At least 15 credits in programming, system development or equivalent.
  3. Knowledge equivalent to English 6 at the Swedish upper secondary level
  4. At least a passing grade in the course Designing and Evaluating Innovation
Level
Advanced level
Main field
Computer Science
Progression level
A1F
Progression level in relation to degree requirements
The course is part of the programme Computer Science: Innovation for change in a digital society and can be included in a Master's degree in Computer Science (120 credits).
Course objectives
The course has three primary purposes:
  • The student develops and deepens his or her knowledge of research methods relevant to the subject area.
  • The student develops knowledge of analysing, visualising and using empirical data, both in research and in other applications.
  • The student develops knowledge about the effective communication of results to different target groups in different contexts and forms.
Course contents
The course includes advanced qualitative and quantitative research design, methodological approaches and considerations, analysis and visualisation of data and studies into effective communication.
The course includes:
  • Information searching and retrieval
  • Goal formulation
  • Formulation of scientific problems and hypotheses
  • Choice of method to solve a scientific problem
  • Qualitative and quantitative research methods
  • Data analysis and statistical analysis
  • Visualisation of data
  • Communication tailored to target group
  • Research ethics
Learning outcomes
Knowledge and understanding
Once the course is completed, the student shall be able to demonstrate:
  • detailed methodological knowledge in the subject of computer science, including the choice of research orientation and strategies for acquiring information as a choice of methodology and approach,
  • in-depth knowledge and understanding of how to collect, analyse and visualise data, and
  • knowledge and understanding of communication tailored to the target group and situation.
Competence and abilities
Once the course is completed, the student shall be able to demonstrate:
  • competence and ability to identify and formulate questions and to choose adequate methods to address these questions,
  • competence and ability to collect, analyse, interpret and evaluate data and to visualise such data appropriately,
  • competence and ability to adapt a message for different situations and target groups both orally and in writing, and
  • competence and ability to acquire information, relate to concepts and with, a critical approach, translate theory into practice.
Evaluation abilities and approach
Once the course is completed, the student shall:
  • demonstrate the ability within the subject of computer science to make assessments in relation to relevant scientific, social and ethical aspects, as well as demonstrating awareness of ethical issues in research and development work,
  • demonstrate insight into the opportunities and limitations of the science, the role these play in society and the human responsibility for how this is used, and
  • demonstrate the ability to identify his or her own need for further knowledge and to take responsibility for his or her own knowledge development.
  • demonstrate the ability to critically review information from different sources (e.g. research publications, books, the internet).
Learning activities
During the course a number of lectures, seminars, workshops and laboratory sessions are conducted. Large parts of the course are carried out in the form of independent study and project work.
Assessment
Grading is based on oral and written examination, including active participation. The course is divided as follows:
  • Research methodology (7 credits)
Assignments - 6 credits - UA
Examination - 1 credit - UA
  • Data analysis, statistics and visualisation (4 credits)
Laboratory work - 1.5 credits - UA
Assignments - 1.5 credits - UA
Examination - 1 credit - UA
  • Communication (4 credits)
Assignments - 4 credits - UA
For a passing grade (A-E), all elements must be completed with least the grade E. The final grade is based on an assessment of all the individual elements with the grade of each element weighted according to its credits.
Course literature and other study material
  • Berndtsson, M., Hansson, J., Olsson, B., & Lundell, B. (2008). Thesis projects: A Guide for Students in Computer Science and Information Systems. London: Springer
  • Björk, L., Räisänen, C. & Björk C. M. (2003). Academic writing: A University Writing course. 3 ed. Lund: Studentlitteratur.
  • Dawson, Christian W. (2015). Projects in Computing and Information Systems: a Student's Guide. Third edition. Harlow, England: Pearson
  • McKinney, W., 2012. Python for data analysis: Data wrangling with Pandas, NumPy, and IPython. " O'Reilly Media, Inc.".
  • Oates, B.J., (2005). Researching Information Systems and Computing. Sage Publications, UK.
  • Runeson, P., Host, M., Rainer, A. and Regnell, B., 2012. Case study research in software engineering: Guidelines and examples. John Wiley & Sons
  • Wohlin, C., Runeson, P., Höst, M., Ohlsson, M.C., Regnell, B. and Wesslén, A., 2012. Experimentation in software engineering. Springer Science & Business Media.
  • Zobel, J. (2004). Writing for Computer Science - The Art of Effective Communication
Besides the above mentioned literature a collection of scientific articles will be added.
Course evaluation
The University provides students who are taking or have completed a course with the opportunity to share their experiences of and opinions about the course in the form of a course evaluation that is arranged by the University. The University compiles the course evaluations and notifies the results and any decisions regarding actions brought about by the course evaluations. The results shall be kept available for the students. (HF 1:14).
Interim rules
When a course is no longer given, or the contents have been radically changed, the student has the right to re-take the examination, which will be given twice during a one year period, according to the syllabus which was valid at the time of registration.
Additional information
The syllabus is a translation of a Swedish source text.