Data mining-based personalized learning manual customization for smart classrooms

With the development of intelligent education, personalized learning has become an important way to improve students' learning efficiency and effectiveness. In this paper, a method for customizing personalized learning manuals for smart classrooms is proposed based on data mining technology. First, students' learning behavior data are collected through the smart classroom and preprocessed and feature extracted. Then, data mining technology is used to analyze and classify students' learning behaviors, so as to achieve accurate identification of personalized learning needs. Based on the analysis results, this paper designs a personalized learning manual generation system, which can dynamically adjust the learning content and path according to students' individual characteristics and learning progress. Finally, the effectiveness of the method is verified through practical application cases, and the results show that the customized personalized learning manual significantly improves students' learning experience and learning outcomes. The research in this paper provides new ideas and practical references for personalized teaching in smart classrooms.