A Comparative Study of Different Information Entropy Index in Personalized Exercise Recommendation

Zheng, Qiulei, Gao, Huifan, Yang, Fan, Pan, Yinghui and Zeng, Yifeng (2021) A Comparative Study of Different Information Entropy Index in Personalized Exercise Recommendation. In: ICCSE 2021: The 16th International Conference on Computer Science and Education. IEEE, Piscataway. (In Press)

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Abstract

It is meaningful to recommend exercises to students in an online education system with a large amount of learning resource. Many recommendation methods usually rely on strategy in the recommendation system in order to predict an exercise score. In this paper, we compare different information entropy index in the exercise recommendation. These index consider how well exercise matches the student’s knowledge ability. In order to compare different methods, we introduce an interactive platform for dynamic exercise recommendation. We conduct a set of exercise recommendation experiments, compare the effect of different index and find the optimal index in the experiment.

Item Type: Book Section
Uncontrolled Keywords: exercise recommendation, information entropy index, online education system
Subjects: G400 Computer Science
X900 Others in Education
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Related URLs:
Depositing User: John Coen
Date Deposited: 02 Jul 2021 12:40
Last Modified: 31 Jul 2021 10:30
URI: http://nrl.northumbria.ac.uk/id/eprint/46594

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