Publication Date
| In 2025 | 0 |
| Since 2024 | 1 |
| Since 2021 (last 5 years) | 1 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 1 |
Descriptor
| Accuracy | 1 |
| Artificial Intelligence | 1 |
| College Students | 1 |
| Comparative Analysis | 1 |
| Computational Linguistics | 1 |
| Computer Software | 1 |
| Cues | 1 |
| English (Second Language) | 1 |
| Error Patterns | 1 |
| Essays | 1 |
| Foreign Countries | 1 |
| More ▼ | |
Source
| International Journal of… | 1 |
Author
| Christopher Saarna | 1 |
Publication Type
| Journal Articles | 1 |
| Reports - Research | 1 |
| Tests/Questionnaires | 1 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
| Japan | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textChristopher Saarna – International Journal of Technology in Education, 2024
This study seeks to clarify whether teachers are able to distinguish between essays written by English L2 students or generated by ChatGPT. 47 instructors who hold experience teaching English to native speakers of Japanese in universities or other higher education institutions were tested on whether they could identify between human written essays…
Descriptors: Identification, Artificial Intelligence, Computer Software, Grammar
