ADAPTIVE LEARNING SYSTEMS FOR PERSONALIZED INSTRUCTION AND ACHIEVEMENT GAP REDUCTION IN DIVERSE CLASSROOM ENVIRONMENTS

Abstract

Adaptive Learning Systems (ALS) have emerged as intelligent educational technologies for supporting personalized instruction, learner engagement, and educational equity; however, empirical evidence regarding their effectiveness across diverse classroom environments remains limited. This study evaluated the effectiveness of ALS in improving academic achievement, learner engagement, educational equity, and teacher-supported instructional adaptability. A mixed-methods research design incorporating a quasi-experimental pre-test–post-test control-group approach was employed with 720 students from six educational institutions across a 14-week intervention period. Quantitative data were obtained from curriculum-aligned pre-test and post-test assessments and system-generated learning analytics, while qualitative data were collected through classroom observations and teacher interviews. The experimental group recorded a mean learning gain of 28.6%, compared with 14.3% for the control group. Subject-specific improvements were highest in Mathematics (32.4%), followed by Science (29.1%), English Language (24.7%), and Social Studies (22.9%). Learners in the lowest achievement quartile recorded a 35.8% improvement, while the achievement gap between high- and low-performing learners decreased by 17.6%. Learning analytics indicated increased engagement, with average daily active engagement reaching 32.5 minutes and task completion reaching 87.3%. Teachers also reported improved instructional decision-making through real-time learner analytics. Overall, the findings indicate that ALS can support personalized, inclusive, and data-informed instruction while enhancing learner engagement and pedagogical adaptability across diverse classroom environments.