Learning Analytics and Adaptive Learning Systems for Supporting Problem-Solving Skills: A Systematic Review toward Sustainable Education - Qurrota A'yun; Rahmatta Thoriq Lintangesukmanjaya; Dwikoranto Dwikoranto; Neisya Azaria Adinda Putri; Noval Maleakhi Hulu (Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto, 2026)
Objective: This study aims to systematically examine publication trends, dominant technologies, implementation strategies, educational impacts, challenges, and future directions in learning analytics and adaptive learning systems to improve students’ problem-solving skills in sustainable education contexts. Method: Research employed a Systematic Literature Review (SLR) approach following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Articles were collected from Scopus, Web of Science, ScienceDirect, Springer, IEEE Xplore, and Google Scholar using predefined inclusion and exclusion criteria. From 1,487 initial records, 20 articles published between 2022 and 2026 in Scopus-indexed Q1–Q3 journals were selected for in-depth thematic analysis. Results: The findings reveal a growing research trend toward intelligent and personalized learning systems. Intelligent tutoring systems, adaptive learning platforms, predictive analytics, augmented reality, and gamification emerged as the most frequently used technologies. These technologies were found to improve self-regulated learning, collaboration, higher-order thinking, and students’ problem-solving performance across various educational contexts. Novelty: This review offers a comprehensive analytical framework that integrates learning analytics, adaptive learning systems, problem-solving skills, and sustainable education, which have largely been examined separately in prior reviews.