Research and Practice of Individualized Intelligent Teaching Based on the Analysis of Individual and Group Learning Behavior: A Case Study of Mobile Communication System Course

Individualized intelligent teaching is the inevitable requirement of the development of higher education. With the gradual maturity of online and offline intelligent teaching platforms and online open courses, learning approaches and learning resources are becoming more and more diversified. The acquisition of learning behavior data is also more convenient, timely and accurate, which brings new opportunities for personalized teaching. Under this back-ground, in order to realize individualized intelligent teaching for specific courses, a teaching mode based on the analysis of individual and group learning behavior characteristics is proposed. Moreover, this paper takes the course “Mobile Communication System” as an example to explore and practice. Using the rain classroom and Blackboard (BB) teaching platform to obtain data, we make teaching adjustment and content recommendation according to students' learning behavior. The effectiveness of the proposed model was verified through a teaching implementation case.