Curriculum

Taught by Prof. Matthieu de Nanteuil, this course give access to a critical theory of knowledge applied to management and to all disciplines that belong to management studies. 
By mixing theoretical and practical methodology, the course aims to:

• help students understand how a "management science" has been progressively invented, what are the challenges and limitations of such a project;
• introduce the participants to the main debates in the epistemological field, mixing fundamental and applied epistemologies;
• give reflexive roots to fulfill their research in management studies.

Taught by Prof. Régis Coeurderoy, this courrse aims to develop students' ability to write critical papers based on existing literature. Students will:

• Read papers that provide a comprehensive perspective on an important research topic.
• Prepare a written and oral presentation and in-depth analysis of one of these papers to be presented 
• Participate to debate on the content, ask questions and discuss the issues raised during the different sessions.
• Produce a term paper with a summary of a paper, criticizing it (theoretical framework, methodology, results, contributions) and proposing a research plan for a follow-up study.

Prof. Valérie Swaen and Prof. Manuel Kolp teach this practical course focused on the following transversal competences:

• How to write a literature review, an academic paper; how to get published and how to present a research paper.
• Designing your literature review
• Developing your research design
• Writing your paper: what and how? 
• Publishing process
• Reviewing your paper
• Presenting your research in a research seminar
• Pitch your research to a non-expert audience

This course is split in three parts each taught by a different professors:

1. QUALITATIVE RESEARCH METHODS by Prof. Alain Decrop

This part will focus on different tools and approcahes:

• General characteristics of qualitative approaches
• Research design and data collection
• Interview guide and questioning
• Analyzing and making sense of data
• Data quality control
• Reflexivity and heterodox approaches
• Ethnographic and visual approaches

2. QUANTITATIIVE RESEARCH METHODS by Prof. Asaâd Elakremi

Here the main focus will be on:

• Defining Research Problems and background to quantitative research.
• Research designs & hypothesis testing (Conceptual)
• Type I and Type II Error
• Sampling, probability and sampling distributions.
• Statistical Power
• Description and Measurement: Levels of measurement, normal distribution, reliability, validity, and generalizability.

3. LOGIC AND ALGORTIHM by Prof. Philippe Chevalier

During this part students will talk about:

• Logic, automata and context-free languages
• Turing machines built on automata to make it possible to build more elaborate proofs
• Computability and complexity theory
• Does a problem have an answer? 
• Is the problem well formulated? 
• How can we determine a priori the level of difficulty of a problem?
• Analysis of algorithms