Abstract
This paper studies the design and implementation of the learning management system of user behavior dynamic recommendation algorithm. With the rapid development of the Internet and the increasing number of information, the learning and thinking methods of college teachers and students have changed greatly, and the traditional education model has been unable to meet the requirements of teachers and students. In class, the teacher explains the knowledge step by step, and the teacher can’t get the feedback from the students in time, which may cause the students to not understand the knowledge and feel great pressure. The existing resources can not be effectively shared, nor can they provide interactive learning. At the same time, it is impossible to provide personalized recommendations based on users’ behavior. When more and more students join the classroom, their learning space is not only limited, but also can not meet the basic needs of personalized learning.
Learning management system is the product of the perfect combination of traditional education and the Internet. Through the existing classroom teaching means, teaching activities can transfer knowledge to students more conveniently and effectively. The system provides personalized services such as search, recommendation and resource reuse, which not only simplifies the workload of college teachers, but also provides the function of statistical analysis. Combined with the actual situation, the system uses a unique recommendation model to analyze the user’s behavior, and then provides users with personalized recommendation content.
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Xiao-hua, C. (2023). Design and Implementation of Learning Management System Based on User Behavior Dynamic Recommendation Algorithm. In: Jan, M.A., Khan, F. (eds) Application of Big Data, Blockchain, and Internet of Things for Education Informatization. BigIoT-EDU 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 465. Springer, Cham. https://doi.org/10.1007/978-3-031-23950-2_8
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DOI: https://doi.org/10.1007/978-3-031-23950-2_8
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