Identifying at-risk students based on Phased Prediction Model

• Date:2025-04-30
• Title of Paper:Identifying at-risk students based on Phased Prediction Model
• Journal:Knowledge and Information Systems
• Summary: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
• Co-author:陈妍，郑庆华，姬曙光，田锋（通讯作者）等
• Translation or Not:No
• Date of Publication:2019-06-06