Publication - 田 锋
| 论文标题 | Identifying at-risk students based on Phased Prediction Model |
| 作者 | 陈妍，郑庆华，姬曙光，田锋（通讯作者）等 |
| 发表/完成日期 | 2019-06-06 |
| 期刊名称 | Knowledge and Information Systems |
| 期卷 | |
| 相关文章 | |
| 论文简介 | Identifying at-risk students is one of the most important issues in online education. During different stages of a semester, students display various online learning behaviors. Therefore, we propose a phased prediction model to predict at-risk students at different stages of a semester. We analyze students’ individual characteristics and online learning behaviors, extract features that are closely related to their learning performance, and propose combined feature sets based on a time window constraint strategy and a learning time threshold constraint strategy. The results of our experiments show that the precision of the proposed model in different phases is from 90.4 to 93.6%. DOI:10.1007/s10115-019-01374-x |
(创新港)
