Developing Chatbot Pragmatics Through Prompting Instruction in AI‐Assisted Communicative Practice
Bibliographic Data
| ID | 22416375 |
|---|---|
| Authors | Alexey Tymbay (0000-0003-2061-0263, Department of the English Language, Faculty of Sciences, Humanities, and Education Technical University of Liberec, Czech Republic, corresponding author) |
| Year | 2026 |
| Publication date | 2026-07-17 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Applied Linguistics (JOURNAL) |
| Journal identifiers | ISSN: 0802-6106 • E-ISSN: 1473-4192 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/ijal.70310 |
| OpenAlex | W7169595671 |
| Language | EN |
| References cited | 25 |
This quasi‐experimental study examines the impact of short‐term prompting instruction on the communicative performance of Czech learners of English in human–chatbot interaction, conceptualizing their prompting behavior as a context‐specific manifestation of pragmatic competence. The study was conducted in two phases (September 2024 and May 2026) and included four groups of participants with varying chatbot experience. Participants with (experimental groups) and without (control groups) prior prompting instruction completed 20 communicative tasks of increasing complexity, during which four indicators of communication effectiveness were recorded: task completion rate, number of conversational turns, user satisfaction, and frequency of chatbot misunderstandings. The findings indicate that prompting instruction improves communication efficiency, particularly in higher‐complexity tasks, as reflected in fewer conversational turns and significantly reduced misunderstandings in human–chatbot interaction, alongside a modest, non‐significant advantage in task completion. More importantly, it facilitates a shift from the inference‐based pragmatic strategies typical of human–human communication toward more explicit forms of contextualization and communicative guidance. The inclusion of two data‐collection phases further enabled a comparison of interaction patterns across different stages of public familiarity with chatbot technology, suggesting that growing familiarity may encourage users to rely more heavily on established interaction routines while applying grammar and spelling rules less consistently. The study therefore contributes to the emerging discussion of chatbot pragmatics by demonstrating how Gricean communicative principles are adapted in AI‐mediated interaction and by highlighting the role of prompting instruction in facilitating this adaptation.
Assertion · Bulgarian · Chatbot · Communicative competence · Contextualization · Grammar · Pragmatics · AI in Service Interactions · Neurobiology of Language and Bilingualism · Social Robot Interaction and HRI
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| Citation velocity | historical |
|---|---|
| Highly cited | No |