AI-Powered Personalized Learning in Indonesian Senior High School Chemistry Education: Evidence from a Quasi-Experimental Study - Reza Firmansyah; Novia Kurniawati; Bagas Dwi Prasetyo (Journal of Science and Mathematics Education, 2026)
This study investigated the effectiveness of an AI-powered AI-powered adaptive learning platform in improving students’ academic achievement in chemistry and explored their overall learning experience. The research was conducted at SMA Negeri 3 Surabaya, involving 72 students of class XI MIPA in the 2023/2024 academic year. A quasi-experimental pretest-posttest control group design was employed. The experimental group (XI MIPA 2, n = 36) used an AI-powered adaptive learning platform incorporating artificial intelligence algorithms to personalize learning pathways, whereas the control group (XI MIPA 1, n = 36) received conventional instruction. Academic achievement was measured using a validated chemistry knowledge test covering reaction rates, chemical equilibrium, and thermochemistry, while learning experience was assessed through a structured questionnaire. The results showed that the experimental group achieved significantly higher posttest scores (mean = 83.7) than the control group (mean = 72.4), with a statistically significant difference (t = 6.43, p < 0.001) and a large effect size (d = 1.02). The experimental group also obtained a higher N-Gain score (0.61, moderate) than the control group (0.35, low). In addition, students in the experimental group reported highly positive learning experiences across all measured dimensions. These findings suggest that AI-powered personalized learning has strong potential to enhance chemistry achievement and student engagement in Indonesian senior high school settings.