Multifunctional learning environments: How Gen-AI and Immersive Worlds Transform Engagement, Collaboration, and Learning in EU Studies

This paper introduces and critically reflects on a pedagogically grounded simulation design that integrates advanced web-based tools and AI applications into the teaching of European Union politics. Building on insights from political science education and simulation pedagogy, the model incorporates virtual worlds, generative AI, and AI-powered avatars into a semester-long simulation of the EU legislative process. Students assume roles as Members of the European Parliament, Council representatives, or interest group lobbyists and engage in authentic legislative negotiations that mirror real-world political dynamics. The paper therefore situates the course design within a broader pedagogical framework that distinguishes between teaching political processes and teaching substantive policy content, highlighting how simulation structures can be calibrated to advance both dimensions. Developed through two higher education innovation projects since 2022 and implemented across four BA and two MA programme at UAS BFI Vienna as well as at the University of Vienna, Volda University and HTW Berlin under an Erasmus+ Jean Monnet Module, the course demonstrates how AI-enhanced immersive simulations can deepen students’ understanding of EU governance through self-experience, self-commitment, and self-empowerment. This design expands the scope and realism of assignments, supports asynchronous and decentralised learning pathways, and enables students from different cohorts, programmes, and disciplines to participate simultaneously in one coherent simulation, thereby promoting cross-programme collaboration, peer teaching, and internationalisation at home. The didactic model follows a student-centred, blended learning approach that combines problem-based tasks, flipped-classroom elements, and collaborative negotiation formats. As students’ progress through interdependent tasks, they develop analytical, negotiation, and judgment competences while taking increasing ownership of their learning processes. Learning materials are introduced progressively and aligned with students’ evolving needs, allowing AI to complement rather than replace in-class instruction. The integration of Gen-AI and AI-avatars substantially enhances the pedagogical value of the virtual simulation environment by increasing both its realism and instructional flexibility. AI-assisted tasks enable students to conduct more complex analyses, such as drafting negotiation briefs, opening speeches or evaluating policy alternatives, while reinforcing essential academic skills and strategic decision-making. AI-avatars embedded throughout the virtual environment function as contextualized on-demand tutors and information hubs, that store interim negotiation outcomes, represent the positions of parallel groups, and ensure continuity within an asymmetric, multi-actor legislative setting. Together, these AI components stabilise the simulation flow, lower barriers to participation, personalise learning trajectories, and maintain a high level of immersion. The paper concludes by discussing the implications of AI-supported simulation environments for innovative teaching and by offering recommendations for educators seeking to adopt similar approaches. Drawing on findings from focus group interviews, course evaluations, and a dedicated post-simulation survey, it examines how students assess the value of AI-assisted learning, how AI-supported performance of students can be evaluated fairly and transparently, and to what extent the didactic model fosters measurable competence gains. By linking pedagogical design choices to empirically observed learning outcomes, the paper identifies the conditions under which AI-enhanced simulations can meaningfully enrich EU Studies teaching—and where further refinement, safeguards, or critical scrutiny are required.