Development of Interactive English Teaching Online Platform Based on Collaborative Filtering Algorithm

Abstract

In order to better promote the development of Interactive English teaching, we develop the existing online teaching platform on the basis of an improved collaborative filtering recommendation algorithm and construct an online English teaching platform that can meet the needs of teaching interaction. With the help of the “hierarchical learning” mode, an interactive teaching model in the form of self-study is constructed to provide users with the most suitable English learning resources. A new method is used to search the nearest neighbor set intelligently for the target user as a supplement to its similarity. This algorithm can be used well in interactive English teaching mode. On this basis, the system module of this study mainly includes a communication page, course evaluation, collaborative editing, and resource sharing. This study also investigates the actual use of students. The results show that the interactive English online teaching platform can meet most of the students’ needs. In this study, the interactive English online teaching platform developed based on a collaborative filtering algorithm has a significant effect, which enhances the interactivity of teaching, improves the quality of English teaching, and increases the breadth of teaching.