Teacher(s)
Language
French
Content
| This course aims to introduce students to the research process in the social sciences. Following a brief review of epistemological principles, the course will outline the various stages of social science research using a hypothetical-deductive approach: Formulating a research question Exploring the research topic Writing a literature review Defining the research problem Developing an analytical model Data collection techniques Data analysis techniques Discussion of the results |
Teaching methods
The module combines lectures and practical sessions. The lectures provide the theoretical foundations essential for carrying out an individual research project, which is undertaken throughout the year. Practical sessions offer personalised support: they enable students to apply the concepts covered in lectures, make tangible progress on their projects and benefit from the guidance of a teaching assistant.
Evaluation methods
Assessment is continuous and comprises two components:
The submission of each piece of work, attendance at the corresponding oral defence, and the submission—within the specified deadlines and in accordance with the procedures provided—of the audio file of the interview and its full transcript are essential requirements for passing the module.
Failure to submit an assignment, unauthorised absence from the corresponding defence, failure to submit the interview or its transcript, or submission of material that does not comply with the requirements and prevents assessment will result in a mark of 0/20 for the component concerned. This result is decisive: in each of these cases, the final mark for the module is set at 0/20, regardless of the result obtained for the other component.
In particular, the following are considered non-compliant submissions that prevent assessment: a submission made after the specified deadline; the absence of the required file; the submission of a file that is empty, illegible, corrupted or does not contain the expected work; submission via a channel other than that expressly provided for; the absence of a sworn declaration regarding the use of artificial intelligence and compliance with intellectual property rules; and, in the event of the use of a generative artificial intelligence tool, the absence of time-stamped transcripts of the prompts and exchanges with the tool, retained and archived in such a way as to enable the examiner to carry out the necessary checks.
Pursuant to Article 78 of the RGEE, these assessments are held only once during the academic year. No further submission of work or oral defence is organised in the third term. The marks obtained are attributed to the June and September examination sessions.
- The submission and oral defence of a group research project in the first term, accounting for 5 marks of the final mark. The written work and oral defence are combined to form an overall mark.
- The submission and oral defence of an individual research project in the second term, accounting for 15 marks of the final mark. The written work and the oral defence are combined to form an overall mark.
The submission of each piece of work, attendance at the corresponding oral defence, and the submission—within the specified deadlines and in accordance with the procedures provided—of the audio file of the interview and its full transcript are essential requirements for passing the module.
Failure to submit an assignment, unauthorised absence from the corresponding defence, failure to submit the interview or its transcript, or submission of material that does not comply with the requirements and prevents assessment will result in a mark of 0/20 for the component concerned. This result is decisive: in each of these cases, the final mark for the module is set at 0/20, regardless of the result obtained for the other component.
In particular, the following are considered non-compliant submissions that prevent assessment: a submission made after the specified deadline; the absence of the required file; the submission of a file that is empty, illegible, corrupted or does not contain the expected work; submission via a channel other than that expressly provided for; the absence of a sworn declaration regarding the use of artificial intelligence and compliance with intellectual property rules; and, in the event of the use of a generative artificial intelligence tool, the absence of time-stamped transcripts of the prompts and exchanges with the tool, retained and archived in such a way as to enable the examiner to carry out the necessary checks.
Pursuant to Article 78 of the RGEE, these assessments are held only once during the academic year. No further submission of work or oral defence is organised in the third term. The marks obtained are attributed to the June and September examination sessions.
Other information
The use of artificial intelligence in the assessment tasks for this course is governed by the rules set out in the faculty notice on this subject, which is available on the faculty’s intranet under ‘Information for students’.
Bibliography
Coman, R., Crespy, A., Louault, F., Morin, J.-F., & Collectif. (2016). Méthodes de la science politique : De la question de départ à l’analyse des données. De Boeck Supérieur.
Miles, M. B., Huberman, A. M., & Saldana, J. (2014). Qualitative Data Analysis. SAGE.
Marquet, J., Van Campenhoudt, L., Quivy, R. (2022). Manuel de recherche en sciences sociales. Armand Colin.
Miles, M. B., Huberman, A. M., & Saldana, J. (2014). Qualitative Data Analysis. SAGE.
Marquet, J., Van Campenhoudt, L., Quivy, R. (2022). Manuel de recherche en sciences sociales. Armand Colin.
Faculty or entity
