Pembelajaran Adaptif Berbasis Teknologi: Strategi Meningkatkan Keterlibatan Peserta Didik dan Hasil Belajar - Muharleni; Yeni Sulastri (Suria Academic Press, 2026)
Digital transformation has shifted educational practices toward more personalized, adaptive, and student-centered learning approaches. One of the most promising innovations is technology-based adaptive learning, which integrates Artificial Intelligence (AI), learning analytics, and digital learning platforms to tailor learning experiences according to learners' characteristics, needs, and learning progress. This study aims to analyze the contribution of technology-based adaptive learning to improving student engagement and learning outcomes using a Narrative Literature Review approach. The data were collected from peer-reviewed scholarly publications published between 2020 and 2025 and retrieved from Scopus, Web of Science, ScienceDirect, SpringerLink, ERIC, Taylor & Francis Online, and Google Scholar. The collected literature was analyzed through content analysis to identify major themes, compare research findings, and develop a comprehensive conceptual synthesis. The findings indicate that adaptive learning enhances behavioral, cognitive, and emotional engagement through personalized learning pathways, adaptive feedback, and learning analytics. Furthermore, adaptive learning contributes to improved learning outcomes, critical thinking skills, self-regulated learning, and data-driven instructional effectiveness. However, its implementation continues to face challenges related to digital infrastructure, teachers' digital competencies, data privacy, and the integration of technology with pedagogical practices. Therefore, the successful implementation of adaptive learning requires the synergy of advanced technologies, effective instructional design, institutional support, and responsible AI governance to create more effective, inclusive, and sustainable learning environments in the era of digital education.