A personalized exercise recommendation method for teaching objectives
Zhizhuang Li, Fei Xu · 2022
It can improve the learning effect and reduce the learning burden to recommend exercises which are in accordance with the teaching objectives to students. How to accurately judge the needs of students and recommend exercises that are consistent with the teaching objectives is an urgent problem to be solved in the field of personalized education. This paper proposes a personalized exercise recommendation method for teaching objectives. This method can recommend exercises that are highly compatible with the syllabus for students according to their selected knowledge points and expected score range. According to the experimental test, the average prediction success rate of this method is 72.5%, 57.2% higher than the exercise recommendation method based on collaborative filtering and KNN, and 10.6% higher than the exercise recommendation method based on cognitive diagnosis and probability matrix decomposition.