Generative AI in Gamified Learning: A Systematic Literature Review on Student Motivation
This Systematic Literature Review (SLR) synthesizes how Generative Artificial Intelligence (Generative AI) is implemented in learning environments, with and without gamification, and what studies report about students’ motivation and engagement. Following the PRISMA 2020 guidelines, structured searches in Scopus, IEEE Xplore, and ScienceDirect identified 792 records, and 116 full-text reports were assessed. Sixty-nine peer-reviewed journal articles were included: 21 on AI-supported gamified or game-based learning and 48 on Generative AI and motivation or engagement without gamification. In the gamified subset, four implementation forms appear (AI characters and role-play partners, LLM feedback and adaptive difficulty, AI-generated assessment items, and Generative AI as a game design tool), and all eight comparison studies reported higher or favorable motivation, engagement, or related outcomes. Across the whole corpus, two meta-analyses and one systematic review report positive overall effects of ChatGPT and Generative AI on engagement or motivation, with moderators and mixed emotional evidence. Individual studies are not uniformly positive: one found that videos outperformed a Generative AI assistant on knowledge gains and curiosity, one found no significant effect on behavioral engagement, and one found that Generative AI use may reduce active learning and motivation. The evidence is concentrated in higher education (48 of 69 articles) and in 2025 (52 of 69); the most frequently stated limitations are small or single-context samples (20 articles) and short interventions with novelty effects (12), and the most frequent recommendations are longer studies (18) and larger and more diverse samples (17). Future research should isolate the AI component's contribution and test it over time.
Keywords: Generative AI, Gamification, Gamified learning, Student motivation, Systematic review of literature.
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