AN AI-BASED ADAPTIVE LEARNING PLATFORM FOR PERSONALIZED STEM EDUCATION IN INDONESIAN HIGH SCHOOLS - Nong Chai; Shahinur Rahman; Tasnia Islam; Ruhul Amin (Scientechno: Journal of Science and Technology, 2026)
In recent years, the demand for personalized education has increased, particularly in Science, Technology, Engineering, and Mathematics (STEM) fields, where students’ learning needs vary significantly. In Indonesia, traditional classroom-based teaching methods struggle to accommodate the diverse learning styles and paces of students. With the rise of Artificial Intelligence (AI), there is a growing opportunity to design adaptive learning platforms that provide personalized learning experiences. However, such platforms are still underutilized in Indonesian high schools, especially in STEM education. This study aims to develop and evaluate an AI-based adaptive learning platform tailored to personalized STEM education for high school students in Indonesia. The platform’s primary goal is to enhance student engagement and academic performance by adapting learning materials and strategies based on individual student progress and preferences. The research utilized a design-based methodology, developing the platform using AI algorithms to monitor and adjust content delivery according to the student’s learning pace, strengths, and weaknesses. A quasi-experimental design was employed, with pre- and post-assessments conducted to evaluate the effectiveness of the platform in a sample of 200 high school students across four Indonesian schools. The platform significantly improved student engagement, with a 15% increase in STEM learning outcomes. Students demonstrated higher retention rates and improved problem-solving abilities, especially in mathematics and science. The AI-based adaptive learning platform proves to be a promising tool for personalized STEM education, enhancing both student learning experiences and academic performance in Indonesian high schools.