Customized Learning Paths: Machine Learning based Developing Intelligent Tutoring Systems for Elementary Students in India

In today’s rapidly evolving educational landscape, the integration of artificial intelligence (AI) into learning environments has become increasingly vital—particularly in regions where access to personalized instruction is limited. Existing literature supports the effectiveness of learner-centered approaches, especially through the development of Intelligent Tutoring Systems (ITS), with a growing emphasis on enhancing education for children in the Indian context. Primary education continues to face significant challenges: rote memorization is often emphasized over conceptual understanding, classroom sizes are large, and opportunities for experiential learning remain limited. To address these issues, this study proposes the development of an interactive and accessible ITS designed to teach primary-level mathematics and Tamil to children aged 5 to 10 years in a more engaging and individualized manner. The system is implemented using a Raspberry Pi module and was tested with a group of 34 children. It aims to offer personalized learning experiences, foster motivation, and support measurable improvements in learning outcomes. The ITS allows children to progress at their own pace and incorporates adaptive learning strategies. Learners are presented with basic questions aligned to previously taught content; correct responses receive positive reinforcement, while incorrect answers prompt context-sensitive hints. Future work will focus on further validating the system through detailed assessment of student learning progress and capability development.