A personalized learning system for mathematics utilizing artificial intelligence and machine learning for ordinary-level students in Sri Lanka

In the context of Sri Lanka, the use of technology in education has a radical change in the method of learning and has made it possible for even concepts in mathematics to be taught in a manner that is interesting and easy to understand. Mathematics is one of the main subjects that Sri Lankan ordinary-level (O/L) students find difficult to learn due to traditional teaching methods, limited resources, and language barriers. This study introduces an artificial intelligence (AI) and machine learning (ML)-powered personalized learning system to enhance existing education delivery to the intension level in mathematics for grade 10 and 11 students. Individual learning requirements are met by creating learning paths, implementing a chatbot to teach as the learner interacts with the material, and implementing a feedback mechanism to track progress. The agile methodology was adopted for this study. The MERN-Stack-based system and the integration of a linear regression model for individualized feedback are described. Student data, collected through surveys in both English and Sinhala languages, helped train the chatbot using the RASA framework. The system’s effectiveness in enhancing math comprehension has been demonstrated, with a higher rate of students improving mathematical performance. The iterative development approach, guided by Agile methodology, allowed for continuous improvements based on user feedback. Even though the system presents effective results, limitations such as scalability and broader testing are noted, with future efforts focused on refining the AI model and enhancing the feedback system. AI and ML-based personalized learning systems are recommended for schools to improve educational outcomes.