Abstract

This study investigates ChatGPT's potential for measuring linguistic accuracy in second language writing for research purposes. We processed 100 L2 essays across five proficiency levels with ChatGPT-4 and manually coded for precision and recall with regard to ChatGPT's identification of errors. Our findings indicate a strong correlation (ρ = 0.97 using one method and .94 using another method) between ChatGPT's error detection and human coding, although this correlation diminishes with lower proficiency levels. While ChatGPT infrequently misidentifies errors, it often underestimates the total error count. The study also highlights ChatGPT's limitations, such as the issue of consistency, and provides guidelines for future research applications.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.