Behavior-Based Computational Intelligence on the Web for Integrated Educational Systems

Abstract

Intelligent learning environments have been made possible by the rapid expansion of online technologies and the introduction of computational intelligence, which have completely changed traditional educational institutions. The use of behavior-based computational intelligence to improve educational systems on the web is examined in this research. Algorithms with intelligence may adjust feedback, evaluation, and content delivery to each student's unique needs by continuously observing how they learn. Personalised learning is made possible by the study's use of machine learning techniques, including reinforcement learning and neural networks, to model and predict student behaviour. High-quality education is now accessible to a wider audience because to the integration of these systems on web-based platforms, which offers scalability and accessibility. Our research shows that when instructional materials are customised to each learner's unique behavior, learner engagement, retention, and academic achievement significantly increase.