AI-enhanced gamification in education: an integrative review of trends, impacts, and corrective role potential

Abstract While educational gamification successfully drives student engagement, it faces persistent criticism for fostering extrinsic reward dependency, superficial achievement (“fast leveling”), and inequitable learning experiences. This study posits Artificial Intelligence (AI) as a critical corrective mechanism to these structural limitations, repositioning static game mechanics within dynamic, adaptive learning ecosystems. Adopting an Integrative Review methodology based on Whittemore and Knafl’s framework, this study synthesizes 61 empirical and theoretical studies (2003–2025) identified through systematic two-way snowballing. Complementary bibliometric data from Scopus and ScienceDirect reveals an exponential “J-curve” growth in the field, marking a decisive disciplinary shift from computer science architectures to pedagogical applications in Social Sciences. The findings indicate that AI integration mitigates traditional gamification pitfalls by (1) personalizing difficulty through adaptive algorithms, (2) replacing superficial rewards with intelligent, real-time feedback, and (3) enhancing inclusivity for diverse learner profiles. Crucially, this review proposes the “AI Corrective Role Framework,” a conceptual model grounded in convergent evidence that operationalizes how AI acts as a learner-centered function to deepen cognitive retention and as a decision-making instrument for institutional strategy. These insights offer researchers and policymakers a robust roadmap for implementing sustainable, evidence-based, and equitable gamified learning environments in the era of Generative AI.