TASK BASED LEARNING AND STUDENTS INTERACTING STANCE USING AI CHATBOOTS IN ESL CLASSROOM AT UNIVERSITY LEVEL

Abstract

The integration of artificial intelligence (AI) chatbots into English as Second Language (ESL) classrooms is reshaping the ways university students participate in task-bsed language learning and negotiate meaning during interaction. This qualitative study explores how university-level ESL learners develop and express interactional stances while engaging in task-based activities mediated by AI chatbots. Drawing on Task-Based Language Teaching (TBLT) and interactional perspectives on language learning, the study examines how learners use AI-mediated dialogue to express agreement, disagreement, uncertainty, evaluation, clarification, and personal positioning during collaborative and individual language tasks. Data are collected through classroom observations, students’ task interactions with AI chatbots, reflective journals, and semi-structured interviews. The qualitative data are analyzed thematically to identify recurring patterns in learners’ stance-taking, interactional strategies, engagement, and perceptions of AI-mediated communication. The anticipated findings indicate that AI chatbots can provide learners with accessible opportunities to initiate dialogue, experiment with linguistic forms, seek clarification, and negotiate meaning without the immediate pressure associated with human interaction. At the same time, learners’ interactional stances may be shaped by the perceived authority, responsiveness, and limitations of AI-generated responses, potentially encouraging both critical engagement and passive acceptance of machine-generated language. The study contributes to contemporary research on AI-assisted language education by demonstrating how task-based activities can create spaces for meaningful stance-taking and learner agency. It also highlights pedagogical considerations for integrating AI chatbots into university ESL classrooms while maintaining purposeful human interaction and critical engagement with AI-generated language.