Research on Personalized Learning Recommendation System based on Machine Learning Algorithm

Abstract

The educational system has started to implement more individualized material from conventional functions in recent years due to the ongoing advancements and developments in science and technology, particularly the continuing growth of artificial intelligence, machine algorithms, and other technologies. The standardized approach to teaching used by conventional educational institutions frequently ignores the individual requirements and learning preferences of every student. To improve learning outcomes, a system of education that is personalized and enhanced by algorithms using machine learning can offer individualized learning materials and suggestions that reflect every student’s educational background, interests, and skills. Additionally, machine learning methods may offer immediate feedback on student achievement and modify instructional strategies in response to that feedback. Making sure AI is employed to promote higher education’s overarching objectives, like encouraging creativity and critical thinking, as opposed to merely eliminating chores and boosting effectiveness, is another difficulty. This paper examines over the several ways that artificial intelligence (AI) and the Optimized Collaborative Filtering Algorithm are being used in higher education. It also proposes an approach for increasing students’ cognitive abilities and compares it with different methods that are currently in use. It has been demonstrated that, in comparison to other models, the suggested model performs better by achieving 95% recall and 99% testing accuracy.