Between Theory and Practice: Integrating AI to Enhance Simulation-Based Learning in EU Politics

Active learning pedagogies, particularly simulations of EU legislative procedures and policy negotiations, have proven effective in fostering students' ability to translate theoretical knowledge into practical understanding of EU politics. However, traditional classroom simulations face inherent constraints: limited time for preparation and practice, fixed role assignments that cannot adapt to individual learning needs, difficulty in capturing the complexity and dynamism of real-world EU decision-making, and challenges in providing personalised feedback to all participants. This paper explores how artificial intelligence can transform simulation-based teaching in EU Studies, moving from static role-play exercises to adaptive, responsive learning environments that address these persistent pedagogical challenges. Drawing on experience teaching EU politics through negotiation simulations, I examine how AI tools can enhance three critical dimensions of simulation pedagogy. First, AI can provide students with real-time information and dynamic briefings during negotiations, mirroring the informational flows and uncertainties that characterize actual EU decision-making. Second, AI enables scaling of simulation complexity beyond what is feasible in traditional classrooms, allowing simulations to capture authentic multi-level governance dynamics, competing institutional logics, and temporal pressures without overwhelming instructors or simplifying the EU's political reality. Third, AI-enhanced simulations can more effectively bridge theory and practice by allowing students to test abstract concepts within realistic negotiation contexts and receive immediate, personalised feedback on their strategic choices, extending practice opportunities beyond limited class time. This paper provides preliminary recommendations for implementing AI tools in EU simulations while maintaining pedagogical rigour, active learning principles, and critical engagement. It concludes by posing questions for future research on measuring learning outcomes in AI-enhanced simulations and ensuring that technological innovation strengthens rather than diminishes students' capacity to navigate the increasingly complex European political landscape.