Publication Date
| In 2026 | 0 |
| Since 2025 | 6 |
Descriptor
| Classification | 6 |
| Student Behavior | 6 |
| Behavior Problems | 3 |
| Data Analysis | 3 |
| Data Use | 3 |
| Elementary School Students | 3 |
| Artificial Intelligence | 2 |
| Cutting Scores | 2 |
| Decision Making | 2 |
| Measures (Individuals) | 2 |
| Models | 2 |
| More ▼ | |
Source
| Behavioral Disorders | 2 |
| Education and Information… | 1 |
| Educational Technology &… | 1 |
| International Educational… | 1 |
| Psychology in the Schools | 1 |
Author
Publication Type
| Journal Articles | 5 |
| Reports - Research | 5 |
| Books | 1 |
| Collected Works - Proceedings | 1 |
Education Level
| Elementary Education | 3 |
| Higher Education | 3 |
| Postsecondary Education | 3 |
| Early Childhood Education | 1 |
| Grade 1 | 1 |
| High Schools | 1 |
| Junior High Schools | 1 |
| Middle Schools | 1 |
| Primary Education | 1 |
| Secondary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
| Child Behavior Checklist | 1 |
What Works Clearinghouse Rating
Caihong Feng; Jingyu Liu; Jianhua Wang; Yunhong Ding; Weidong Ji – Education and Information Technologies, 2025
Student academic performance prediction is a significant area of study in the realm of education that has drawn the interest and investigation of numerous scholars. The current approaches for student academic performance prediction mainly rely on the educational information provided by educational system, ignoring the information on students'…
Descriptors: Academic Achievement, Prediction, Models, Student Behavior
Chih-Yueh Chou; Wei-Han Chen – Educational Technology & Society, 2025
Studies have shown that students have different help-seeking behavior patterns and tendencies and furthermore, that students with certain help-seeking behavior patterns and tendencies may have poor performance (i.e., at-risk students). This study applied an educational data mining approach, including clustering and classification, to analyze…
Descriptors: Student Behavior, Help Seeking, Problem Solving, Information Retrieval
Kathleen Lynne Lane; Katie Scarlett Lane Pelton; Nathan Allen Lane; Mark Matthew Buckman; Wendy Peia Oakes; Kandace Fleming; Rebecca E. Swinburne Romine; Emily D. Cantwell – Behavioral Disorders, 2025
We report findings of this replication study, examining the internalizing subscale (SRSS-I4) of the revised version of the Student Risk Screening Scale for Internalizing and Externalizing behavior (SRSS-IE 9) and the internalizing subscale of the Teacher Report Form (TRF). Using the sample from 13 elementary schools across three U.S. states with…
Descriptors: Data Analysis, Decision Making, Data Use, Measures (Individuals)
Jessica R. Bagneris; Edward D. Scott Jr. – Psychology in the Schools, 2025
Bias influencing teachers' classroom management is increasingly clear, but the circumstances that influence the likelihood of relying on those biases are less understood. This study employed Classification and Regression Tree (CART) analysis, resulting in four models examining how teachers' appraisals of first-grade students' externalizing problem…
Descriptors: Predictor Variables, Behavior Problems, Classification, Regression (Statistics)
Kathleen Lynne Lane; Nathan Allen Lane; Mark Matthew Buckman; Katie Scarlett Lane Pelton; Kandace Fleming; Rebecca E. Swinburne Romine – Behavioral Disorders, 2025
We report the results of a convergent validity study examining the externalizing subscale (SRSS-E5, five items) of the adapted Student Risk Screening Scale for Internalizing and Externalizing (SRSS-IE 9) with the externalizing subscale of the Teacher Report Form (TRF) with two samples of K-12 students. Results of logistic regression and receiver…
Descriptors: Data Analysis, Decision Making, Data Use, Test Validity
Caitlin Mills, Editor; Giora Alexandron, Editor; Davide Taibi, Editor; Giosuè Lo Bosco, Editor; Luc Paquette, Editor – International Educational Data Mining Society, 2025
The University of Palermo is proud to host the 18th International Conference on Educational Data Mining (EDM) in Palermo, Italy, from July 20 to July 23, 2025. EDM is the annual flagship conference of the International Educational Data Mining Society. This year's theme is "New Goals, New Measurements, New Incentives to Learn." The theme…
Descriptors: Artificial Intelligence, Data Analysis, Computer Science Education, Technology Uses in Education

Peer reviewed
Direct link
