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Role-Play Simulations of Decision-Making and Student Learning: The Case of Political Science Teaching and Learning

Comparative Politics
European Politics
Higher Education
Dorothy Duchatelet
Universiteit Antwerpen
Dorothy Duchatelet
Universiteit Antwerpen

Abstract

Role-play simulations of decision-making are widely used within political science teaching. They simulate processes that underlie policymaking, such as agenda setting, policy formulation, policy adoption, implementation and evaluation, in contexts of international relations, European studies or comparative politics. They can be course-embedded, extracurricular or hybrid and as such strive for different learning objectives. Since decades, the use of these simulations has been increasing. However, to date, researchers have been struggling to grasp their effect on student learning outcomes. The current review study wants to systematically identify, synthesize and discuss characteristics of role-play simulations of decision-making as a learning environment and to evaluate their effect on student learning outcomes. The MISTER-model (Model for Investigating Simulation-based Teaching Environments and their Results) is presented as conceptual framework and is applied for answering the following research questions: 1. How do these role-play simulations of decision-making vary? 2. What is known about their effect on student learning? Material for the review was collected from the following databases: ERIC (Educational Resources Information Center; Ebsco) and Social Sciences Citation Index (SSCI), with the following search terms: ‘simulation’, ‘role-playing’, and ‘educational games’, each combined with ‘politics’, ‘political science’, ‘European studies’ or ‘international relations’. After removing doubles, 1772 articles were screened on 9 criteria. This resulted in 37 remaining articles. Results show a rich diversity in simulation environment (e.g. topic, size, duration, description) and specify struggles in capturing simulation effects (e.g. measures, design, analysis). Findings are discussed with regard to (the sharing of) future simulation practices and their related effect research.