Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 0 |
| Since 2006 (last 20 years) | 1 |
Descriptor
| Automation | 1 |
| Classification | 1 |
| College Entrance Examinations | 1 |
| Graduate Study | 1 |
| Maximum Likelihood Statistics | 1 |
| Models | 1 |
| Natural Language Processing | 1 |
| Prediction | 1 |
| Probability | 1 |
| Reading Comprehension | 1 |
| Regression (Statistics) | 1 |
| More ▼ | |
Source
| ETS Research Report Series | 1 |
Publication Type
| Journal Articles | 1 |
| Numerical/Quantitative Data | 1 |
| Reports - Research | 1 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
| Graduate Record Examinations | 1 |
What Works Clearinghouse Rating
Peer reviewed
Download full textSheehan, Kathleen M.; Kostin, Irene; Futagi, Yoko; Hemat, Ramin; Zuckerman, Daniel – ETS Research Report Series, 2006
This paper describes the development, implementation, and evaluation of an automated system for predicting the acceptability status of candidate reading-comprehension stimuli extracted from a database of journal and magazine articles. The system uses a combination of classification and regression techniques to predict the probability that a given…
Descriptors: Automation, Prediction, Reading Comprehension, Classification
