Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 0 |
| Since 2006 (last 20 years) | 1 |
Descriptor
| Affective Behavior | 1 |
| Classification | 1 |
| Classroom Environment | 1 |
| Data Collection | 1 |
| Data Use | 1 |
| Error Patterns | 1 |
| Evaluation | 1 |
| Feedback (Response) | 1 |
| Majors (Students) | 1 |
| Mathematics Instruction | 1 |
| Measurement Techniques | 1 |
| More ▼ | |
Source
| Grantee Submission | 1 |
Publication Type
| Reports - Research | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
| Higher Education | 1 |
| Junior High Schools | 1 |
| Middle Schools | 1 |
| Postsecondary Education | 1 |
| Secondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full text
Direct linkWang, Yutao; Heffernan, Neil T.; Heffernan, Cristina – Grantee Submission, 2015
The well-studied Baker et al., affect detectors on boredom, frustration, confusion and engagement concentration with ASSISTments dataset were used to predict state tests scores, college enrollment, and even whether a student majored in a STEM field. In this paper, we present three attempts to improve upon current affect detectors. The first…
Descriptors: Majors (Students), Affective Behavior, Psychological Patterns, Predictor Variables
