6 ECTS credits
152 h study time

Offer 1 with catalog number 1023729CNR for all students in the 1st semester at a (C) Bachelor - specialised level.

Semester
1st semester
Enrollment based on exam contract
Impossible
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Yes
Enrollment Requirements
Studenten in de bachelor communicatiewetenschappen moeten 'Kwantitatieve methoden' en 'Kwalitatieve methoden' gevolgd hebben, alvorens dit opleidingsonderdeel op te nemen. Studenten in het schakelprogramma of voorbereidingsprogramma communicatiewetenschappen en de master criminologische wetenschappen kunnen dit opleidingsonderdeel opnemen.
Taught in
English
Faculty
Faculty of Social Sciences & SolvayBusinessSchool
Department
Communication Sciences
Educational team
Daniël Hans Marinus Jurg
Laurence Claeys (course titular)
Activities and contact hours
26 contact hours Lecture
26 contact hours Seminar, Exercises or Practicals
100 contact hours Independent or External Form of Study
Course Content

Students will gain basic knowledge of social science research methods that are used to research new types of data (e.g. hyperlinks, social media networks, algorithmes, …), learn to use these new types of data to answer existing research questions and learn to formulate new research questions (e.g. on social surveillance, algorithmic trading,... ), that arise as a consequence of the digitalization and interconnectedness of data. Students will learn the basics of data science, but also critically reflect upon the methodological implications of these changes for the social sciences methodology. 

Additional info

The course exists out of weekly lectures and practical exercises (during 13 weeks)

  • a two-hour theoretical session: each session consist out of a lecture, followed by student discussion and discussion of a scientific paper on digital methods or innovation methods.
  • a two-hour practical session: each practical session consists out of assignments to teach students to use digital methods tools (data gathering, analysis and visualisation tools) with the goal for students to independently execute digital methods research by the end of the course.

 

Learning Outcomes

General competences

After taking the classes students should be able to:

  • Recognize and understand the new data types that arise as a consequence of the Internet and related technologies;
  • Select, apply on a basic level, and understand a range of digital/data science methods and tools that can be applied to a wide array of social science research issues.
  • Understand the practices of the software development methodology in the ICT innovation process as well as the role of the different disciplines within this practices.

Critically engage with the ethical, legal and social issues related to digital social research and more generally, the use of social research methods to study ICTs and their social implications.

Grading

The final grade is composed based on the following categories:
Practical Exam determines 100% of the final mark.

Within the Practical Exam category, the following assignments need to be completed:

  • Task 1_Online ID with a relative weight of 20 which comprises 20% of the final mark.
  • Task 2_Description with a relative weight of 30 which comprises 30% of the final mark.
  • Task 3_Analysis with a relative weight of 50 which comprises 50% of the final mark.

Additional info regarding evaluation

Not applicable.

Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Bachelor of Communication Studies: Standaard traject (only offered in Dutch)