Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 1 |
Descriptor
| Accuracy | 1 |
| Computer Assisted Instruction | 1 |
| Cues | 1 |
| Elementary School Students | 1 |
| English | 1 |
| Error Patterns | 1 |
| Intervention | 1 |
| Learner Engagement | 1 |
| Middle School Students | 1 |
| Predictor Variables | 1 |
| Reading Tests | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 1 |
| Reports - Research | 1 |
Education Level
| Middle Schools | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
| Gates MacGinitie Reading Tests | 1 |
What Works Clearinghouse Rating
Peer reviewed
Direct linkNam, SungJin; Frishkoff, Gwen; Collins-Thompson, Kevyn – IEEE Transactions on Learning Technologies, 2018
In an intelligent tutoring system (ITS), it can be useful to know when a student has disengaged from a task and might benefit from a particular intervention. However, predicting disengagement on a trial-by-trial basis is a challenging problem, particularly in complex cognitive domains. In the present work, data-driven methods were used to address…
Descriptors: Intervention, Learner Engagement, Middle School Students, Vocabulary Development
