Adaptive Gamification in Learning Management Systems: A Systematic Literature Review

Digital transformation has positioned the Learning Management System (LMS) as the centerpiece of the higher education learning ecosystem. However, current conventional gamification implementations are still dominated by a static, "one-size-fits-all" approach, which often triggers gamification fatigue and a long-term decline in student motivation. This study aims to synthesize literature regarding the convergence between Artificial Intelligence (AI) and the Felder-Silverman Learning Style Model (FSLSM) in developing adaptive gamification within LMS. The research methodology employed is a Systematic Literature Review (SLR) based on the PRISMA protocol, combined with bibliometric analysis using VOSviewer on 31 selected articles ranging from 2021 to 2026. The results indicate a significantly increasing global publication trend, peaking in 2025. The knowledge structure in this domain is divided into two primary pillars: a pedagogical cluster focusing on motivation theory and a technical cluster emphasizing personalization algorithms and system architecture. The main findings confirm that AI and FSLSM integration allows an LMS to transform into a dynamic ecosystem capable of adjusting game elements in real-time based on student psychological profiles, thereby increasing active engagement and learning effectiveness. This research provides a strategic roadmap for educational technology developers to create more inclusive and personalized digital learning environments.