PersonalInfo - 田 锋
| Paper Name | Identifying at-risk students based on Phased Prediction Model |
| Author | 陈妍，郑庆华，姬曙光，田锋（通讯作者）等 |
| Publication/Completion Time | 2019-06-06 |
| Magazine Name | Knowledge and Information Systems |
| Vol | |
| Related articles | |
| Paper description | 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)
