We propose a simple but effective method to recommend exercises with high quality and diversity for students. Our method is made up of three key components: (1) candidate generation module; (2) diversity-promoting module; and (3) scope restriction module. The proposed method improves the overall recommendation performance in terms of recall, and increases the diversity of the recommended candidates by 0.81\% compared to the baselines.
@article{arxiv.2206.12291,
title = {A Design of A Simple Yet Effective Exercise Recommendation System in K-12 Online Learning},
author = {Shuyan Huang and Qiongqiong Liu and Jiahao Chen and Xiangen Hu and Zitao Liu and Weiqi Luo},
journal= {arXiv preprint arXiv:2206.12291},
year = {2022}
}
Comments
AIED 2022: The 23rd International Conference on Artificial Intelligence in Education (accepted)