Academic Journal
'AI is like fire': a discourse analysis of language teachers' attitudes towards artificial intelligence.
| Τίτλος: | 'AI is like fire': a discourse analysis of language teachers' attitudes towards artificial intelligence. |
|---|---|
| Συγγραφείς: | Paz-López, Alba1 (AUTHOR) albapazlopez@uma.es, Shafirova, Liudmila2 (AUTHOR), Vazquez-Calvo, Boris3 (AUTHOR) |
| Πηγή: | Journal of Education for Teaching. Sep2026, Vol. 52 Issue 4, p749-767. 19p. |
| Θεματικοί όροι: | *Artificial intelligence, *Language teachers, *Literacy, *Metaphor, *Technology Acceptance Model, *Discourse analysis, *Social attitudes, *Educational technology |
| Περίληψη: | This study examines how language teachers talk about artificial intelligence (AI) and how that talk relates to uptake. We analysed 17 semi-structured interviews from international teachers using utterance-level appraisal, metaphor and keyword analysis and interpreted findings through TAM3 (usefulness, ease, intention, social influence) and AI-literacy domains (informed, practical, critical, ethical). Teachers' metaphors and stance-marking language clustered into three frames: AI as terminator (integrity/assessment risks), enigma (inevitability/opacity; knowledge gaps) and sidekick (teacher-facing workflow support with human-in-the-loop boundaries). Mapping tagged utterances to a two-axis space (AI acceptance/AI literacy) yielded four attitudinal archetypes: sceptic, enthusiast, purist and early explorer. Implications are actionable: teach AI as literacies (and assess them), redesign assessment towards process evidence (draft trails, provenance checks), and stage adoption from planning to classroom implementation with explicit guardrails. Limitations include cross-sectional, self-reported data and raw-surplus profiling; future longitudinal, multilingual studies should normalise by utterance density and triangulate with classroom artefacts and traces. [ABSTRACT FROM AUTHOR] |
| Βάση Δεδομένων: | Academic Search Index |
καταχωρήστε σχόλιο πρώτοι!