Bibliometric analysis of gamification in teacher education during the generative AI era: historical trends, present status, and future trajectories.

Gamification has become a relevant pedagogical approach in teacher education, yet its evolution and relationship with generative artificial intelligence remain fragmented. This study maps the development, intellectual structure, and emerging trajectories of research on gamification in pre-service and in-service teacher education between 2016 and 2025. A bibliometric analysis was conducted on an integrated Scopus and Web of Science dataset. After merging records, removing duplicates, and applying predefined eligibility criteria, 1,223 documents were retained. Performance analysis, co-citation analysis, keyword co-occurrence analysis, and thematic evolution mapping were conducted in Biblioshiny/Bibliometrix, with study identification and selection documented through the PRISMA framework. Scientific output increased markedly over the study period, especially from 2020 onward, and was led mainly by institutions and countries with strong educational innovation capacity. The co-citation network revealed three intellectual foundations: motivational theories of gamification, technology adoption and educational innovation models, and empirical work on game-based learning and serious games. Keyword co-occurrence analysis identified seven thematic clusters organized around gamification, education, artificial intelligence, teacher training, and digital learning. By 2025, the field shows a clear thematic shift toward generative artificial intelligence, adaptive systems, and automated personalization. Research on gamification in teacher education has moved from a focus on motivational design and digital engagement toward more intelligent, data-driven, and adaptive ecosystems. The findings highlight a rapidly expanding field and provide an evidence-based agenda for teacher education, institutional policy, and future studies on the pedagogical and ethical integration of GenAI.