Code
MGFE RES 4401
Level
M1
Field
Recherche
Language
Anglais/English
ECTS Credits
2
Class hours
12
Total student load
40
Program Manager(s)
Department
- Data analytics, Économie et Finances
Educational team
Introduction to the module
This course teaches students to produce a rigorous, critical literature review --- moving from personal opinion on a topic toward evidence-based knowledge of what has already been published on it. Working in groups of 2--3, students search academic databases, select and evaluate a number of sources for their relevance and credibility, and learn to recognize the data and method behind a study well enough to judge whether its conclusions actually hold up. AI tools are used throughout as research assistants, always verified rather than trusted outright. The course closes with an individual exam applying these same critical-evaluation skills to a new article.
Learning goals
- 2. Produire et mobiliser des savoirs hautement spécialisés, issus d’une réflexion critique, et dans un champ d’expertise
Learning objectives
- 2.1 - Develop a critical awareness of highly specialised knowledge, some of which is at the forefront of knowledge, with a view to formulating innovative contributions to complex issues, in line with the strategic plan of organisations and with scientific
Course Learning objectives
By the end of this course, each student will be able to:
1. Identify the types of literature available (white/grey, peer-reviewed vs. non-peer-reviewed, professional/trade).
2. Describe what makes a literature review critical rather than descriptive, and the different forms it can take.
3. Formulate a research question that is clear, focused, complex, arguable, and analytical.
4. Conduct a literature search using academic databases, applying appropriate search parameters and terms.
5. Differentiate the type of data and research method used in a given study.
6. Distinguish correlation from causation in a research design.
7. Judge the relevance, credibility, and sufficiency of an academic source against established criteria.
8. Draft a critical literature review that synthesizes selected sources thematically around a research question.
9. Use AI tools to support literature search and drafting, verifying each suggested source independently.
10. Identify practices that constitute plagiarism, including undisclosed AI-generated content.
11. Assess whether a research question, its supporting literature, data, and method are coherent, when applied to a new article.
Content : structure and schedule
Session 1 — Choosing a topic; what makes a research question good, and what makes a literature review critical rather than descriptive. Group: find sources, identify a gap.
Session 2 — Using library databases; planning a search. Group: find more sources; each member drafts one research question.
Session 3 — Critically evaluating the data behind a source. Individual: classify data type and evaluate source credibility (CRAAP) for 3 sources tied to each member’s own research question.
Session 4 — Critically evaluating the method behind a source, including bias and causal claims. Individual: identify method and bias for the same sources.
Session 5 — Using AI as a research assistant, and academic integrity. Group: combine every member’s individual work into one critical literature review.
Session 6 — Individual final exam: applying the same critical-evaluation skills to a new article.
Sustainable Development Goals
ODD 4: Quality education
Ce cours permet le développement de l'esprit de recherche et critique et permet de penser le recours à la littérature économique et aux outils d'IA.
Number of SDG's addressed among the 17
1
Learning delivery
Mixte
Pedagogical methods
Over six sessions, students work in groups of 2–3 to build one research project progressively.
Each session’s task is a genuine building block of the group’s final report, not a stand-alone exercise — students are encouraged to reflect on their own progress at each stage, beginning with their initial opinion on the topic, then confronting it with the academic literature, with AI-assisted search, with their own critical evaluation of data and method, and finally with collective discussion within the group.
Evaluation and grading system and catch up exams
Continuous examination 60%: individual MCQ (2x10%) + class work and homework in group of 3 students (40%)
Final exam 40% (in class exam) individual
Textbook Required and Suggested Readings
Saunders, M., Lewis, P. & Thornhill, A. (2023). Research Methods for Business Students (9th ed.). Harlow: Pearson. — Chapter 3, “Critically Reviewing the Literature,”
Keywords
Research methods, critical literature review, research question, data and methods, causal inference, AI-assisted research, scientific mindset.