Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 1 |
| Since 2016 (last 10 years) | 3 |
| Since 2006 (last 20 years) | 3 |
Descriptor
Author
| Dascalu, Mihai | 3 |
| McNamara, Danielle S. | 2 |
| Allen, Laura K. | 1 |
| Botarleanu, Robert-Mihai | 1 |
| Crossley, Scott A. | 1 |
| Crossley, Scott Andrew | 1 |
| Nicula, Bogdan | 1 |
| Perret, Cecile A. | 1 |
| Skalicky, Stephen | 1 |
Publication Type
| Reports - Research | 3 |
| Speeches/Meeting Papers | 2 |
| Journal Articles | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full text
Direct linkBotarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2021
Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. This study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale.…
Descriptors: Computer Assisted Testing, Scoring, Natural Language Processing, Computer Software
Crossley, Scott A.; Skalicky, Stephen; Dascalu, Mihai – Journal of Research in Reading, 2019
Background: Advances in natural language processing (NLP) and computational linguistics have facilitated major improvements on traditional readability formulas that aim at predicting the overall difficulty of a text. Recent studies have identified several types of linguistic features that are theoretically motivated and predictive of human…
Descriptors: Natural Language Processing, Readability, Reading Comprehension, Reading Rate
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Open-ended comprehension questions are a common type of assessment used to evaluate how well students understand one of multiple documents. Our aim is to use natural language processing (NLP) to infer the level and type of inferencing within readers' answers to comprehension questions using linguistic and semantic features within their responses.…
Descriptors: Natural Language Processing, Taxonomy, Responses, Semantics
