Research and Application of Artificial Intelligence Based Integrated Teaching-Learning Modular Approach in Colleges and Universities

Nowadays, in various educational institutions, artificial intelligence technology is applied effectively and successfully. This artificial intelligence improves learning and student development in academic performance. Challenges of the conventional education approach, students' dependence on teachers in all resources for study, unavailability of professional instructors, and a greater focus on conditioning learning than practical usefulness lead to lower learning performance. In this paper integrated teaching-learning model approach has been proposed using artificial intelligence in student education. It involves speeding up fulfilling education targets by reducing barriers to entry, automating management processes, and maximizing learning performance. The proposed ITLMA method used the naive Bayes algorithm to evaluate the student ranking using a class score, task, project score, and final exam. The result of artificial intelligence-based ITLMA and naive Bayes algorithm hasa high accuracy ratio of 80.1% with less error ratio of 15.7%, high prediction 88.2%, precision 98.2%, and improves student and teacher interaction compared to other existing methods.