PENGGUNAAN TEKNOLOGI WEB UNTUK SISTEM E-LEARNING ADAPTIF DI PENDIDIKAN - Sardiansyah Sabir; Novita Kunia Wahyu; Nurhalima Nurhalima; Nurazizah Nurazizah; Abdillah Sirfanal Hak; Muh. Alfarizi Asbir (Plexi Digital Indonesia, 2025)
The development of web technology has accelerated the adoption of adaptive e-learning systems; however, existing literature indicates variations in approaches, limited integration of artificial intelligence, and a lack of comprehensive mapping of research trends in this field. This study conducts a Systematic Literature Review of 20 studies published between 2020 and 2025 to identify developments, challenges, and opportunities in web-based adaptive e-learning. The findings reveal that the integration of machine learning, learning analytics, and content personalization techniques is increasingly implemented and has been shown to improve learner engagement and learning outcomes. Nevertheless, many studies still focus primarily on higher education, have not fully optimized real-time analytics, and provide limited discussion on the need for ethical regulation of artificial intelligence. Specifically, this study identifies three major trends: (1) the integration of machine learning with real-time learning analytics, (2) more inclusive adaptive designs addressing diverse learner needs and learning styles, and (3) the growing urgency of ethical AI regulation in education. In addition, this review highlights research gaps in vocational and non-formal education, which remain underexplored. These findings provide directions for future research and recommendations for the development of more effective and sustainable web-based adaptive e-learning systems.