Publication Date
| In 2026 | 0 |
| Since 2025 | 1 |
| Since 2022 (last 5 years) | 2 |
| Since 2017 (last 10 years) | 4 |
| Since 2007 (last 20 years) | 4 |
Descriptor
| Artificial Intelligence | 4 |
| Intelligent Tutoring Systems | 4 |
| Readability Formulas | 4 |
| Reading Comprehension | 4 |
| Classification | 2 |
| Comparative Analysis | 2 |
| Computational Linguistics | 2 |
| Computer Software | 2 |
| Correlation | 2 |
| Course Content | 2 |
| Difficulty Level | 2 |
| More ▼ | |
Author
| April Murphy | 2 |
| Balyan, Renu | 2 |
| Husni Almoubayyed | 2 |
| Kole A. Norberg | 2 |
| Kyle Weldon | 2 |
| Logan De Ley | 2 |
| McCarthy, Kathryn S. | 2 |
| McNamara, Danielle S. | 2 |
| Steve Ritter | 2 |
Publication Type
| Reports - Research | 4 |
| Journal Articles | 3 |
| Information Analyses | 1 |
Education Level
| Elementary Secondary Education | 2 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
| Flesch Kincaid Grade Level… | 2 |
What Works Clearinghouse Rating
Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – International Journal of Artificial Intelligence in Education, 2025
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2020
For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…
Descriptors: Natural Language Processing, Artificial Intelligence, Man Machine Systems, Classification
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 2020
For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…
Descriptors: Natural Language Processing, Artificial Intelligence, Man Machine Systems, Classification
Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – Grantee Submission, 2024
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change

Peer reviewed
Direct link
