Research on Personalized Learning Recommendation Model Based on User Collaborative Filtering Algorithm

In the era of big data, the number of learning resources is increasing exponentially, and learners need to spend a lot of time and energy searching for target resources, leading to problems such as information overload and learning confusion. This project proposes to establish a personalized learning recommendation model based on learner collaborative filtering algorithm. Firstly, model online learners and online learning recommendation projects. Then, it extracted their main features. Finally, through user collaborative filtering algorithms, personalized learning resources or paths that match personalized parameters are recommended to online learners, thereby stimulating their learning motivation and enthusiasm, improving learning effectiveness, and achieving personalized learning.