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 |
| Artificial Intelligence | 1 |
| Classification | 1 |
| Comparative Analysis | 1 |
| Expository Writing | 1 |
| Natural Language Processing | 1 |
| Prediction | 1 |
| Readability | 1 |
| Readability Formulas | 1 |
Source
| Grantee Submission | 1 |
Publication Type
| Reports - Research | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
| Flesch Kincaid Grade Level… | 1 |
What Works Clearinghouse Rating
Peer reviewed
Download full textBalyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 2018
While hierarchical machine learning approaches have been used to classify texts into different content areas, this approach has, to our knowledge, not been used in the automated assessment of text difficulty. This study compared the accuracy of four classification machine learning approaches (flat, one-vs-one, one-vs-all, and hierarchical) using…
Descriptors: Artificial Intelligence, Classification, Comparative Analysis, Prediction
