Adaptive Learning dan Sistem Pembelajaran Berpersonalisasi: Tren dan Arah Penelitian

Abstract

This scoping review examines trends and research directions in adaptive learning and personalized learning systems published between 2019 and 2024. Following the PRISMA-ScR framework and guided by the Arksey & O'Malley methodology, a systematic search was conducted across multiple academic databases (Scopus, Web of Science, ERIC, IEEE Xplore, and MDPI). Of the 312 initially identified records, 28 studies met the inclusion criteria after screening. Findings reveal that: (1) research on adaptive learning grew significantly after 2020, particularly driven by the COVID-19 pandemic; (2) AI and machine learning are the dominant technologies used in adaptive learning systems; (3) the majority of studies focus on higher education contexts; (4) adaptive learning consistently shows positive effects on student learning outcomes; and (5) key challenges include data privacy, algorithmic bias, and limited teacher training. This review maps the current state of knowledge and identifies gaps for future research, particularly in K-12 settings and developing country contexts.