Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 2 |
Descriptor
| Natural Language Processing | 2 |
| Artificial Intelligence | 1 |
| Automation | 1 |
| Documentation | 1 |
| Error Patterns | 1 |
| Essays | 1 |
| Language Acquisition | 1 |
| Language Proficiency | 1 |
| Learning Processes | 1 |
| Likert Scales | 1 |
| Linguistic Input | 1 |
| More ▼ | |
Author
| Botarleanu, Robert-Mihai | 2 |
| Dascalu, Mihai | 2 |
| Allen, Laura K. | 1 |
| Crossley, Scott | 1 |
| Crossley, Scott Andrew | 1 |
| McNamara, Danielle S. | 1 |
| Monteiro, Kátia | 1 |
Publication Type
| Reports - Research | 2 |
| Journal Articles | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Monteiro, Kátia; Crossley, Scott; Botarleanu, Robert-Mihai; Dascalu, Mihai – Language Testing, 2023
Lexical frequency benchmarks have been extensively used to investigate second language (L2) lexical sophistication, especially in language assessment studies. However, indices based on semantic co-occurrence, which may be a better representation of the experience language users have with lexical items, have not been sufficiently tested as…
Descriptors: Second Language Learning, Second Languages, Native Language, Semantics
Botarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2022
Automated scoring of student language is a complex task that requires systems to emulate complex and multi-faceted human evaluation criteria. Summary scoring brings an additional layer of complexity to automated scoring because it involves two texts of differing lengths that must be compared. In this study, we present our approach to automate…
Descriptors: Automation, Scoring, Documentation, Likert Scales

Peer reviewed
Direct link
