Exploring the Emergence of AI-Mediated Pragmatic Norms among Iranian EFL Learners in Virtual English Conversation Spaces
محورهای موضوعی : Journal of Teaching English Language Studies
Shahram Afraz
1
,
Azam Sodagar
2
1 - Department of English Language Teaching, Qe.C., Islamic Azad University, Qeshm, Iran
2 - Department of English Language Teaching, Qe.C., Islamic Azad University, Qeshm, Iran
کلید واژه: AI-mediated communication, Pragmatic competence, Iranian EFL learners,
چکیده مقاله :
This study investigates the emergence of pragmatic norms among Iranian EFL learners in AI-mediated virtual English conversation spaces. Drawing on sociocultural and interactionist frameworks, the research employed qualitative discourse analysis with 20 intermediate learners who participated in AI-based conversational sessions. Findings revealed that learners developed stable pragmatic patterns, including explicit politeness marking, template-driven requests, and regularized turn-taking, shaped by the predictable, feedback-oriented nature of AI partners. Adaptation strategies involved rapid uptake of feedback, calibration of directness, strategic hedging, and controlled code-switching, which reflect learners’ attempts to align with mediated interactional norms. While AI-mediated practices such as politeness, mitigation, and structured refusals partially mirror human communication, notable differences emerged, including reduced idiomaticity, limited small talk, and formulaic compliments. These divergences suggest that while AI partners facilitate pragmatic clarity and provide scaffolding for learners’ interactional routines, they may also constrain sociopragmatic richness. Overall, the results highlight both the educational potential and the limitations of AI as a tool for fostering pragmatic competence in EFL contexts. Implications call for integrating AI-based practice with reflective tasks and authentic communication opportunities to maximize pragmatic transfer.
This study investigates the emergence of pragmatic norms among Iranian EFL learners in AI-mediated virtual English conversation spaces. Drawing on sociocultural and interactionist frameworks, the research employed qualitative discourse analysis with 20 intermediate learners who participated in AI-based conversational sessions. Findings revealed that learners developed stable pragmatic patterns, including explicit politeness marking, template-driven requests, and regularized turn-taking, shaped by the predictable, feedback-oriented nature of AI partners. Adaptation strategies involved rapid uptake of feedback, calibration of directness, strategic hedging, and controlled code-switching, which reflect learners’ attempts to align with mediated interactional norms. While AI-mediated practices such as politeness, mitigation, and structured refusals partially mirror human communication, notable differences emerged, including reduced idiomaticity, limited small talk, and formulaic compliments. These divergences suggest that while AI partners facilitate pragmatic clarity and provide scaffolding for learners’ interactional routines, they may also constrain sociopragmatic richness. Overall, the results highlight both the educational potential and the limitations of AI as a tool for fostering pragmatic competence in EFL contexts. Implications call for integrating AI-based practice with reflective tasks and authentic communication opportunities to maximize pragmatic transfer.
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