COMMUNICATION ACCOMMODATION IN HUMAN–AI INTERACTION: A CORPUS-ASSISTED SOCIOLINGUISTIC STUDY OF PAKISTANI UNIVERSITY STUDENTS’ DISCOURSE WITH CHATGPT
DOI:
https://doi.org/10.63878/jalt1855Keywords:
Communication Accommodation Theory, human–AI interaction, corpus-assisted sociolinguistics, ChatGPT discourse, Pakistani university students, digital communication, linguistic convergence, AI-mediated academic writing.Abstract
The high pace of introducing artificial intelligence into the educational setting has altered the dynamics of human interaction patterns, establishing new rules of interaction between humans and the machine agents. Basing the research on the Communication Accommodation Theory (CAT), the focus of the study is to explore how the Pakistani university students linguistically accommodate ChatGPT during academic and problem-solving interactions. A more focused corpus-assisted sociolinguistic methodology was thus followed, during which a dedicated corpus of student-AI prompt-response sequences was aggregated of naturally occurring ChatGPT conversations between undergraduate and postgraduate students in a variety of disciplines. The analysis of the data has been conducted using a combination of the corpus tools to detect recurrent lexical bundles, use of pronouns, signs of politeness, constructions of modal, and formality indicating convergence, divergence, and maintenance strategies. The results suggest a strong inclination toward convergence, with students shifting their communicative preferences in order to conform to what they consider to be the AI communicative preference, i.e., greater explicitness, procedural clarity, mitigation, and task-related instructions. The conversation helps to further show that accommodation depends on academic competence, previous exposure to AI-based tools, and the communicative intent of the communication. Also, the paper reveals that human-AI discourse restructures the conventional power relations in which the AI is seen as both a source of authoritative knowledge and a collaborative interlocutor. Through its recording of the emergent patterns of interaction in Global South setting, the study will add to digital sociolinguistics, further applying CAT to human-machine interaction, and give pedagogic suggestions to AI-mediated academic literacy practices.
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