Synergistic Integration of Artificial Intelligence and Gamification in University Finance Trading Simulation Labs

Background The integration of Artificial Intelligence (AI) and gamification in higher education has shown promise in enhancing engagement and learning outcomes, particularly in fields requiring experiential training like finance. However, university trading labs—critical for bridging financial theory and practice—often struggle to sustain student motivation and translate knowledge into real-world decision-making. Existing research predominantly examines AI or gamification in isolation, leaving a gap in understanding their synergistic potential to address these challenges. Objectives This systematic literature review investigates how the combined use of AI-driven adaptive systems and gamification strategies enhances learning experiences, motivation, and skill acquisition in university finance trading labs. Methods Following the systematic review protocol, 28 peer-reviewed studies were analyzed. Thematic coding and synthesis were employed to evaluate empirical findings, theoretical frameworks, and methodological approaches across AI-driven adaptivity (e.g., machine learning, NLP) and gamification elements (e.g., leaderboards, narrative scenarios). Results and Conclusions The integration of AI and gamification significantly improves engagement, knowledge retention, and decision-making agility in simulated trading environments. AI-driven personalization tailors challenges to individual proficiency, while gamification elements foster motivation and resilience. However, challenges such as algorithmic bias, resource disparities, and ethical concerns require interdisciplinary collaboration for equitable implementation. This review provides actionable insights for designing adaptive, game-informed learning ecosystems that prepare students for real-world financial markets, advocating for balanced innovation in pedagogy, technology, and policy.