A Comparative Study in Using Rhetorical Hedging and the AI Trap of Thai and Native ELT Research
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Abstract
The purpose of this study was to investigate the rhetorical complexities of hedging within the Results and Discussion sections of English Language Teaching (ELT) research articles. Employing a qualitative comparative design, a corpus of 20 peer-reviewed articles (10 authored by Thai NNES and 10 native speakers) published between 2019 and 2024 was compiled. Data were extracted using AntConc software and manually coded according to Hyland’s (1998) typology of hedging, followed by a thematic analysis. The results revealed a significant pragmatic divide: Thai authors relied heavily on modal verbs (98 instances) for a reader-oriented approach, while native authors preferred limiting conditions (54 instances) to precisely bound their claims. Furthermore, the repetitive hedging patterns of Thai authors, characterized by lower lexical diversity, were observed to align with linguistic features known to trigger false positives in AI detection tools. These findings underscore the urgent need for pedagogical interventions to expand NNES scholars’ rhetorical repertoires and highlight the necessity for linguistically equitable AI detection methodologies.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
บทความนี้ยังไม่เคยลงตีพิมพ์ในวารสารใดมาก่อน และไม่อยู่ระหว่างการพิจารณาของวารสารอื่น
บทความที่ลงพิมพ์เป็นข้อคิดเห็น/แนวคิด/ทัศนคติของผู้เขียนเท่านั้น หากเกิดผลทางกฎหมายใดๆที่อาจ
เกิดขึ้นจากบทความนี้ ผู้เขียนจะเป็นผู้รับผิดชอบ และบทความนี้เป็นลิขสิทธิ์ของวารสารเท่านั้น
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