Master Thesis

Duration

Number of credits

Lecturer

Collégialité, Jean-Michel Lafleur, Jérémy Mandin, Marco Martiniello, Elsa Mescoli

Language(s) of instruction

English language

Organisation and examination

All year long

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

Cf. Rules available at this address: https://www.student.fass.uliege.be/cms/c_7151929/fr/studentfass-reglements-et-formulaires (General regulations and Master en Sociologie Finalité spécialisée en Migration and Ethnic Studies)

Learning outcomes of the learning unit

The master thesis aims to evaluate the student's capacity to carry out independent and rigorous research, resulting in a written document that presents the findings. Rather than simply reproducing knowledge taught by professors, the thesis requires the production of new insights on a specific topic. This involves formulating a research problem, including questions or hypotheses, within the field of migration and ethnic studies. The student must define a well-delineated subject, review the relevant literature, identify an appropriate empirical research field, select or design a suitable methodology, collect and analyze data, and compile a bibliography that adheres to formal academic standards.

Prerequisite knowledge and skills

Planned learning activities and teaching methods

The research and writing process is carried out autonomously by the student with regular exchanges with the promotor and the members of the jury. In addition, a thesis seminar is organized to support the student at every stages of the process.

For students in the EuMIGS double degree programme, a series of activities are organised throughout the year, including a kick-off meeting and/or a winter workshop at one of the network's partner universities. These events are, among other things, an opportunity for students to share the progress of their work with professors and students from across the network.

Mode of delivery (face to face, distance learning, hybrid learning)

Course materials and recommended or required readings

Exam(s) in session

Any session

- In-person

oral exam

Written work / report


Further information:

Data transparency

The supervisor(s) and members of the jury should have access to the empirical data produced throughout the thesis research to evaluate the methodological soundness of the final work. Therefore, students are asked to keep their empirical material (including fieldnotes, interview transcripts and audio recordings, database, etc.) organised in a secured place that can be shared with the thesis supervisor. 

During the collection of the empirical data, the use of an Information and Content Form and/or Procedure that conforms with the RGPD rules is required. A model of such form (in French) is available here: gdpr031-formulaire_dinformation_et_de_consentement_pour_tfe.docx 

 

AI transparency

Any use of AI tools should be done in coherence with the University Charter about AI: 

ULiège Charter for the use of generative artificial intelligence in academic work

The use of generative artificial intelligence during the thesis process, while not strictly forbidden, should be limited and will respect the following principles:

• Complete transparency: If students use AI at any stage of the thesis process, this use should be declared and described in the final thesis. The description should include the type of tasks AI was used for as well as the specific AI tools that were used for each task. 
• Methodological reflexivity: If AI tools are used during the research process, transparency is not enough. The use of AI - as any other research tools (coding software, statistical analysis software, etc.) - should be explained, justified and critically reflected upon in the thesis itself. 
• Research integrity: It is forbidden to present the production of AI as your own or as the production of any other person (research participant, author, fellow students, etc.). This means that the use of AI to produce false empirical data is strictly forbidden and will be judged as akin to fraud. The production of a personal and original work being at the center of the Master Thesis and of any academic work, the use of AI as a substitute to the student personal reflection, critical analysis, and command of academic literature, is forbidden. 

Work placement(s)

Organisational remarks and main changes to the course

The dates of the Master Thesis Seminar in the first semester are available on Celcat. The dates for the second semester will be decided at a later stage and communicated to the students. Participation to the seminar is mandatory. In case of difficulty, it is essential to contact the seminar coordinators.

Contacts

Jérémy Mandin jeremy.mandin@uliege.be

Elsa Mescoli E.Mescoli@uliege.be 

Association of one or more MOOCs