Research on Recommendation of Personalized Exercises in English Learning Based on Data Mining

Abstract

Aiming at the problems of traditional method of exercise recommendation precision, recall rate, long recommendation time, and poor recommendation comprehensiveness, this study proposes a personalized exercise recommendation method for English learning based on data mining. Firstly, a personalized recommendation model is designed, based on the model to preprocess the data in the Web access log, and cleaning the noise data to avoid its impact on the accuracy of the recommendation results is focused; secondly, the DINA model to diagnose the degree of mastery of students’ knowledge points is used and the students’ browsing patterns through fuzzy similar relationships are clustered; and finally, according to the clustering results, the similarity between students and the similarity between exercises are measured, and the collaborative filtering recommendation of personalized exercises for English learning is realized. The experimental results show that the exercise recommendation precision and recall rate of this method are higher, the recommendation time is shorter, and the recommendation results are comprehensive.

A study of innovative strategies for teaching English to college students based on tiered probit

“…With the goal of "gender" as the guide, "three strengths" as the guide, "diversified view of talent cultivation" as the goal, "diversified teacher development" as the guarantee, and "diversified academic evaluation" as the means, we actively build the EGP+ESP+EIC trinity diversified curriculum system of college English. The EGP+ESP+EIC curriculum is mainly composed of EGP General English to build the foundation, ESP Special English to improve, and EIC English for Intercultural Communication to broaden the horizon [18]. The EGP+ESP+EIC trinity curriculum system is shown in Figure 1.…”