Using GPT-3 as a More Knowledgeable Other to Provide Feedback on English Language Learners' Spoken Transcripts
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| Title: | Using GPT-3 as a More Knowledgeable Other to Provide Feedback on English Language Learners' Spoken Transcripts |
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| Language: | English |
| Authors: | Paul Raine (ORCID |
| Source: | TESL-EJ. 2025 29(2). |
| Availability: | TESL-EJ. e-mail: editor@tesl-ej.org; Web site: http://tesl-ej.org |
| Peer Reviewed: | Y |
| Page Count: | 15 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research Tests/Questionnaires |
| Education Level: | Adult Education |
| Descriptors: | Artificial Intelligence, English (Second Language), Second Language Learning, Transcripts (Written Records), Feedback (Response), Computer Uses in Education, Adult Students |
| ISSN: | 1072-4303 |
| Abstract: | Generative Pre-trained Transformers (GPT) have shown promise as More Knowledgeable Others(MKO) for English Language Learners (ELLs) by providing on-demand, contextualized feedback within the Zone of Proximal Development (ZPD). In this study, a web app collected spoken responses from 680 adult ELLs, automatically transcribed them and sent them to GPT3 for corrective and elaborative improvements. Of the 428 instances that participants rated, approximately 74% were judged "very helpful," and perceived helpfulness rose with learner proficiency. Semi-structured interviews with six users offered illustrative insights into how feedback was interpreted and applied, particularly by intermediate-level learners. Although this research shows promise for utilizing GPT-3 as an MKO for ELLs, the implementation needs to be further refined and developed, and we need to continue to bear in mind the limitations inherent in GPT-based systems. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1482976 |
| Database: | ERIC |
| Abstract: | Generative Pre-trained Transformers (GPT) have shown promise as More Knowledgeable Others(MKO) for English Language Learners (ELLs) by providing on-demand, contextualized feedback within the Zone of Proximal Development (ZPD). In this study, a web app collected spoken responses from 680 adult ELLs, automatically transcribed them and sent them to GPT3 for corrective and elaborative improvements. Of the 428 instances that participants rated, approximately 74% were judged "very helpful," and perceived helpfulness rose with learner proficiency. Semi-structured interviews with six users offered illustrative insights into how feedback was interpreted and applied, particularly by intermediate-level learners. Although this research shows promise for utilizing GPT-3 as an MKO for ELLs, the implementation needs to be further refined and developed, and we need to continue to bear in mind the limitations inherent in GPT-based systems. |
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| ISSN: | 1072-4303 |
