VERIFICATION NORMS AND GENERATIVE AI USE: A SURVEY OF ENGLISH LANGUAGE UNDERGRADUATES
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Abstract
This cross-sectional survey examined generative AI use and views on output verification among English Language undergraduates at the University of Foreign Language Studies, the University of Danang. The analyses used closed-ended items and responses to four open-ended questions. Of 210 responses, 159 passed both attention checks. In the retained sample, 62.3% reported using ChatGPT daily and 89.3% at least weekly. AI use was most commonly reported for writing, grammar and vocabulary, and speaking. Among 158 cases with complete data, 41 (25.9%) endorsed a requirement for teachers to verify AI output and also reported using AI output themselves without checking it. Without attention-check exclusions, the corresponding proportion was 56/209 (26.8%). The two items had different referents, so their joint endorsement did not establish an inconsistency between students’ beliefs and behaviour. Epistemic asymmetry was therefore treated as a tentative interpretation. Scores for general readiness to use AI in teaching were higher than those for confidence in pedagogical prompt design. Self-reported confidence in identifying AI hallucinations and cultural bias was positively associated with confidence in prompt design. In addition, 93.7% reported no formal AI-related content in their programme. The findings described self-reported perceptions and practices at one institution, and the cross-sectional design did not permit causal inference.
Keywords
generative AI, English-language practice, verification norms, epistemic asymmetry, prompt design
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References
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