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.
| Original language | English |
|---|---|
| Title of host publication | ICCSE 2021 - IEEE 16th International Conference on Computer Science and Education |
| Subtitle of host publication | IEEE: The 16th International Conference on Computer Science and Education |
| Place of Publication | Piscataway |
| Publisher | IEEE |
| Pages | 1030-1034 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781665414685, 9781665414678 |
| ISBN (Print) | 9781665447546 |
| DOIs | |
| Publication status | Published - 17 Aug 2021 |
| Event | ICCSE 2021: The 16th International Conference on Computer Science and Education - Lancaster University, Lancaster, United Kingdom Duration: 17 Aug 2021 → 21 Aug 2021 http://www.ieee-iccse.org/?_v=1625228873586 |
Publication series
| Name | Proceedings of the International Conference on Computer Science & Education (ICCSE) |
|---|---|
| Publisher | IEEE |
| ISSN (Print) | 2471-6146 |
| ISSN (Electronic) | 2473-9464 |
Conference
| Conference | ICCSE 2021 |
|---|---|
| Country/Territory | United Kingdom |
| City | Lancaster |
| Period | 17/08/21 → 21/08/21 |
| Internet address |
Keywords
- Exercise recommendation
- Information entropy index
- Online education system