Adaptive Recommender System for an Intelligent Classroom Teaching Model

Abstract

The development of information technology has facilitated the use of the intelligent classroom model supported by information technology to improve the college students’ comprehensive quality and ability. However, the existing models are too sophisticated to be applied to the actual teaching process, and ignore the individualized teaching characteristics of students. Therefore, an intelligent classroom model with adaptive learning resource recommendation was proposed. First, the entire teaching process was divided into three stages which were used to combine teachers’ teaching and students’ learning. Then the key problems of the learning resources recommendation system was studied and a learning resource recommendation based on TR-LDA (Teaching Resources-Latent Dirichlet Allocation) was proposed and how to be achieved. Finally, the proposed intelligent classroom model was verified in practical teaching. Results show that the intelligent classroom model with adaptive learning resources recommendation can help to improve students’ learning efficiency. The relevant conclusions can be used as a reference for exploring the use of information technology to improve the quality of undergraduate professional course teaching.