"Interpretable AI techniques unveil the factors and types of at-risk early ..."

Jui-Long Hung, Kerry Rice, Mingyan Zhang (2025)

> Home

Details and statistics

DOI: 10.1108/DTA-11-2023-0795

access: closed

type: Journal Article

metadata version: 2025-08-05

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - journals/program/HungRZ25
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/program/HungRZ25
Jui-Long Hung, Kerry Rice, Mingyan Zhang:
Interpretable AI techniques unveil the factors and types of at-risk early warning: a case study in K-12 online learning. Data Technol. Appl. 59(3): 516-538 (2025)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.