Utilizing knowledge graph and student testing behavior data for personalized exercise recommendation
Pin Lv, Xiaoxin Wang, Jia Wei Xu, Junbin Wang · 2018
Personalized exercise recommendation plays an important role in boosting the study performance of students. However, recent studies for personalized exercise recommendation only take the learning status of a student in recommendation and fail to take the prerequisite relationships among knowledge points into account which represent a reasonable learning sequence of these knowledge points during a study procedure. To the best of knowledge, in this paper, we make the first attempt employing both of the learning status of a student and the prerequisite dependencies among knowledge points to enhance the effectiveness in personalized exercise recommendation. A real-case evaluation confirms the effectiveness of our personalized exercise recommendation algorithm in terms of recommendation precision and diversity.