Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Accuracy | 1 |
| At Risk Students | 1 |
| Classification | 1 |
| Comparative Analysis | 1 |
| Elementary School Students | 1 |
| Grade 1 | 1 |
| Grade 2 | 1 |
| Identification | 1 |
| Models | 1 |
| Nonparametric Statistics | 1 |
| Prediction | 1 |
| More ▼ | |
Source
| Regional Educational… | 1 |
Publication Type
| Reports - Research | 1 |
Education Level
| Early Childhood Education | 1 |
| Elementary Education | 1 |
| Grade 1 | 1 |
| Grade 2 | 1 |
| Primary Education | 1 |
Audience
| Administrators | 1 |
| Parents | 1 |
| Policymakers | 1 |
| Teachers | 1 |
Location
| Florida | 1 |
Laws, Policies, & Programs
Assessments and Surveys
| Stanford Achievement Tests | 1 |
What Works Clearinghouse Rating
Peer reviewed
Download full textKoon, Sharon; Petscher, Yaacov; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
This study examines whether the classification and regression tree (CART) model improves the early identification of students at risk for reading comprehension difficulties compared with the more difficult to interpret logistic regression model. CART is a type of predictive modeling that relies on nonparametric techniques. It presents results in…
Descriptors: At Risk Students, Reading Difficulties, Identification, Reading Comprehension
