Experimental Methods

llsma2020  2026-2027  Louvain-la-Neuve

Experimental Methods
The version you’re consulting is not final. This course description may change. The final version will be published on 1st June.
5.00 credits
30.0 h
Q2

  This biannual learning unit is not being organized in 2026-2027 !

Language
English
Prerequisites
N/A
Main themes
This course provides students with the conceptual and practical foundations required to design, implement, and analyze experiments that produce valid, transparent and reproducible findings. Covering the entire experimental research process, the course guides students from the formulation of theory-driven hypotheses to the selection of appropriate designs, manipulation of variables, and application of advanced statistical techniques.
Students will learn to ensure internal and external validity, control for confounding variables, design robust manipulations, and adopt best practices for transparency, preregistration and reproducibility.
By the end of the course, participants will be equipped to design high-quality experiments, analyze complex data structures, and communicate results in line with international academic standards.
Learning outcomes

At the end of this learning unit, the student is able to :

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  • Explain the logic, principles and epistemological foundations of experimental research in management sciences.
  • Formulate clear research questions and hypotheses suitable for experimental testing (main effects, moderation, mediation).
  • Design robust experimental studies using between-subjects, within-subjects, and mixed designs, including factorial and complex multi-factor structures.
  • Implement manipulation checks, control conditions, and randomization procedures to ensure internal validity.
  • Conduct appropriate statistical analyses (ANOVA, regression, conditional process analysis) using SPSS.
  • Apply advanced techniques for moderation and mediation (PROCESS macro, bootstrap).
  • Prepare clear, transparent and publication-standard reports of experimental findings, including visuals, tables and narrative interpretation.
  • Critically evaluate the methodological quality of experimental research in management and the social sciences.
Contribution of the teaching unit to the LSM Learning Outcomes framework:
  • Knowledge and reasoning
  • Scientific and systematic approach
  • Personal and professional development.
 
Content
Introduction to Experimental Research
  • Experimental logic and causal inference
  • Types of validity (internal, external, construct, statistical)
  • Sample size and power
  • Ethical and transparency principles (pre-registration)
From Theory to Hypotheses
  • How to formulate research questions
  • Main effects, moderators, mediators
  • Illustrative examples from management and behavioral research
Experimental Design and Manipulation
  • Between vs. within-subjects designs
  • Mixed designs and factorial structures
  • Manipulation checks and control conditions
  • Practical exercise: designing an experiment
Data Analysis – ANOVA and Regression
  • ANOVA (univariate, repeated measures)
  • Regression for moderation and mediation
  • PROCESS macro
  • Hands-on SPSS session
Advanced Analyses and Visualization
  • Conditional process analysis (moderated mediation)
  • Bootstrap methods for indirect effects
  • Data visualization standards and best practices
  • Writing results sections (APA-style or journal-specific)
  • Reporting guidelines for top-tier journals
Integration and Application
  • Meta-analysis and replication strategies
  • Pitching an experimental study
  • Discussion and critique of student proposals
Teaching methods
A combination of teaching methods will be used, including lectures, interactive discussions, hands-on computer sessions, critical article reviews, and applied group exercises. Students actively engage with each step of the experimental research process.
Evaluation methods
Assessment is based on continuous evaluation, including:
  • Group activities: critique and discussion of experimental research articles.
  • Individual assignments: design an experimental study, conduct data analysis (ANOVA/regression), and prepare a research report.
  • Oral presentation: pitch an experimental project.
  • Class participation.
Important note: By submitting an assignment for evaluation, students affirm that (i) it accurately reflects verified facts—particularly when generative AI resources are used, in which case these tools must be explicitly acknowledged—and (ii) all specific requirements of the assignment have been respected, including those related to transparency and documentation of the process.
Failure to meet any of these commitments, whether through intent or negligence, constitutes a breach of academic integrity and is considered academic misconduct.
Online resources
The teaching materials available on Moodle includes:
  • PowerPoint slides and/or screencasts
  • Scientific articles
  • Case studies
  • Practical guides for SPSS and PROCESS
Bibliography
A reading list will be provided on Moodle and may include:
  • Foundational and advanced articles on experimental methods
  • Methodological chapters and selected book excerpts
  • Exemplary experimental research papers in management
Faculty or entity
> CLSM


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Management
GEST2M
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