Duration
30h Th
Number of credits
| Master in labour sciences (60 ECTS) | 6 crédits |
Lecturer
Language(s) of instruction
French language
Organisation and examination
All year long, with partial in January
If a student fails an examination during the first term:
- They are permitted to resit the assessed subject during the second term (May-June);
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
This research method seminar aims to:
- familiarize students with the social science research process (learning the different stages through homework);
- provide students with the methodological tools needed to build a research approach in all its aspects;
- accompany students in the conduct of a first scientific research in the social sciences.
Learning outcomes of the learning unit
At the end of this seminar, the student will be able to:
- Identify a concrete object to be analysed;
- Formulate correctly (criteria seen during the seminar) a starting question and a research question;
- Choose a theoretical approach consistent with the concerned object;
- Research and use literature consistent with the theoretical approach;
- Collect relevant field data;
- Formulate hypotheses (criteria seen during the seminar);
- Analyse collected field data;
- Describe the results of the research carried out, in accordance with the instructions given by the teacher.
Prerequisite knowledge and skills
An introductory course in the humanities is highly recommended. If not, the student will be able to update himself/herself through various readings (see with the teachers).
Planned learning activities and teaching methods
The seminar is organized around:
- Ex cathedra sessions accompanied by video podcasts for theoretical input;
- Individual assignments with individual feedbacks (eCampus) and collective discussions (questions and answers sessions);
- Two moments of individual student coaching are also provided during the year (one mandatory and one optional).
Mode of delivery (face to face, distance learning, hybrid learning)
Blended learning
Further information:
The seminar is given in a hybrid way : video clips complement the sessions in class, in order to go deeper or to press on certain theoretical elements. The sessions will be recorder so that students can listen to the material again. However, recording is not guaranteed for sessions featuring guest speakers. Students will be notified of the sessions affected.
Course materials and recommended or required readings
Platform(s) used for course materials:
- eCampus
Further information:
Course materials :
- Slides of the different courses ;
- Vidéo clips;
- Recordings of the sessions;
- Documents and other resources (see Ecampus);
Exam(s) in session
Any session
- Remote
written exam
Written work / report
Further information:
The assessment will be based on the various assignments submitted throughout the year. Each assignment will be graded as follows:
- Assignment 1: /15
- Assignment 2: /15
- Final assignment: /70
The total of these marks will be converted to a mark out of 20, which will constitute the final mark for the seminar.
If the student does not wish to validate the seminar during the following session and obtain a pass mark (P) instead of a fail mark (A) for the assessment, they must submit a request to the teacher by email no later than the deadline for the final assignment.
A few points to note:
- Access to the final assignment in the first session is conditional on participation in the individual support sessions organised during the year. In the event of an unjustified absence from the individual support sessions, the student will receive an absence mark (A) for the final assignment and will have to resubmit it in the August session.
- If the final assignment is not submitted during the first sitting, the student will receive a mark for non-attendance and will therefore have to retake the seminar during the second sitting. The marks for Assignments 1 and 2 will be retained. If the final assignment is not submitted during the second session, the student will receive a mark for non-attendance and will have to re-enrol on the seminar, retake all assessments and comply with the requirements of the new academic year in order to pass the seminar.
- Absorbing grade principle: students must obtain at least 28/70 on the final assignment to pass the seminar. If the grade is lower, the final grade in the first session corresponds to the final assignment grade only. In other words, if the final assignment grade is too low, the grades for the other assignments cannot be used to make up for the final grade.
- Furthermore, an absorbing grade principle also applies to the final assignment: if a mark of less than 12/30 is obtained for the question relating to data analysis, the mark for the final assignment will be the mark for that question. As the analysis is the most important part of the assignment, if the analysis is too weak, the final assignment cannot be passed.
-If an assignment is submitted up to 24 hours late, a penalty of 10% of the mark will be applied. If it is submitted more than 24 hours late, the assignment will not be accepted.
-During their research process, students must conduct a minimum number of interviews (instructions given at the beginning of the year). If this number is not reached, 1 point will be deducted from the final grade for each missing interview. The teacher reserves the right to ask students for proof that the interviews were conducted if there is any doubt as to their veracity. In the event of data falsification, a fraud mark will be issued.
- In the event of suspected fraud (unauthorised use of generative AI, data manipulation, plagiarism, copying another student's work, etc.), the teacher reserves the right to request further details, evidence that the work was carried out, or even to organise an additional assessment in order to verify these suspicions.
See the University's Policy on Generative AI: https://www.student.uliege.be/cms/c_19230399/fr/faq-student-charte-uliege-d-utilisation-des-intelligences-artificielles-generatives-dans-les-travaux-universitaires
Organisation of the second session for students who obtained a mark lower than 10/20 for the seminar:
- If the student failed (or was unable to submit, due to non-participation in the AI) the final assignment, a new version of it must be submitted.
- If the student failed one or more assignments among Assignments 1 or 2, a reflective practice grade must be submitted for the assignment(s) concerned. Instructions for the reflective practice grade(s) will be given by the teacher via eCampus and by email.
The new mark for the assignment(s) submitted in the second session replaces the mark for the assignment(s) in the first session, and the same weighting as in the first session is applied with the other assignments and any internship. The principle of absorbing marks remains applicable.
In the event of a further failure in the second session, the student must re-enrol in the seminar the following year and retake all assessments.
Work placement(s)
No work placement
Organisational remarks and main changes to the course
The research methodology seminar takes place throughout the academic year. The precise dates, times and premises are provided via CELCAT.
The eCampus platform and the e-mail address @student.uliege.be will be the preferred means of communication with the course teachers.
The eCampus platform will also be used to submit assignments and various documents and teaching resources (PowerPoint presentations).
Students are advised to consult CELCAT, ECampus and their e-mail inbox regularly, as they may change location or timetable.
From year to year, the course and its organisational and assessment methods may change. Students who may have to retake the course after failing in a previous year must comply with the new rules in force in order to validate the course. It is therefore the responsibility of students in this situation to keep themselves informed of any changes and to comply with them.
Contacts
Manoée THIRY (Pedagogic assistant)
Mail : manoee.thiry@uliege.be
Bruno FRERE (Professor)
Mail : bfrere@uliege.be