Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Classification | 1 |
| Help Seeking | 1 |
| Helping Relationship | 1 |
| Intelligent Tutoring Systems | 1 |
| Mathematics Instruction | 1 |
| Prediction | 1 |
| Problem Solving | 1 |
| Program Effectiveness | 1 |
| Student Behavior | 1 |
| Undergraduate Students | 1 |
Source
| Journal of Educational Data… | 1 |
Author
| Barnes, Tiffany | 1 |
| Chi, Min | 1 |
| Cody, Christa | 1 |
| Isvik, Amy | 1 |
| Lytle, Nicholas | 1 |
| Maniktala, Mehak | 1 |
Publication Type
| Journal Articles | 1 |
| Reports - Research | 1 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textManiktala, Mehak; Cody, Christa; Isvik, Amy; Lytle, Nicholas; Chi, Min; Barnes, Tiffany – Journal of Educational Data Mining, 2020
Determining "when" and "whether" to provide personalized support is a well-known challenge called the assistance dilemma. A core problem in solving the assistance dilemma is the need to discover when students are unproductive so that the tutor can intervene. Such a task is particularly challenging for open-ended domains, even…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Helping Relationship, Prediction
