Optimizing Learning Through Artificial Intelligence: Evaluating the Impact of Adaptive Learning Technologies on Student Outcomes - SH, Ummi Aminah; Supriyono, Nanda Meg Ryan Puspitasari (Sinergi International Journal of Education, 2023)
The integration of Artificial Intelligence (AI) into adaptive learning environments presents a promising approach to transforming education by personalizing instruction and improving learner outcomes. This narrative review investigates how AI technologies have been applied in educational settings to support adaptive learning and examines the effectiveness, user readiness, technological infrastructure, and policy considerations surrounding implementation. A structured literature search was conducted using Scopus and Google Scholar, employing Boolean operators to identify recent peer-reviewed studies on AI, adaptive learning, and education. Selected articles were analyzed to extract themes related to pedagogical effectiveness, student engagement, real-time feedback mechanisms, and system-level enablers and constraints. The findings reveal that AI significantly enhances learning by enabling customized content delivery, real-time analytics, and automated instructional support. Evidence from multiple contexts confirms improvements in student achievement and engagement, while educators benefit from reduced administrative workload and more targeted interventions. However, systemic challenges remain, including digital infrastructure gaps, insufficient teacher training, data privacy concerns, and disparities in technology access, particularly in developing regions. This review underscores the need for comprehensive educational policies that promote equitable AI access, robust ethical frameworks, and sustained professional development. Future research should focus on measuring socio-emotional impacts and refining assessment models for AI-enhanced learning. Addressing these areas will be essential to fully realize the benefits of AI in creating inclusive and adaptive learning environments.