Enhancing Personalized Learning Resource Retrieval with an Intelligent Network Teaching System Using Hybrid Filtering Algorithm

Thetraditional one-size-fits-all teaching approach is no longer effective in engineering education as students' needs evolve and technology becomes more integrated. This technique has some complications, including a lack of smart teaching, limited communication, weak guidance, insufficient monitoring, and theoretical shortcomings. To address these issues, an intelligent online teaching system has emerged, but the abundance of information available online makes it challenging to find valuable resources. Therefore, a modified approval scheme remained developed using a Hybrid filtering algorithm that considers user preferences and system reliability. User browsing and downloading history are tracked to improve the system's accuracy and robustness. The aim is to make teaching smarter and more tailored to individual needs using knowledge map technology.