Speaker
Description
Grounded in Constructivist Learning Theory and Vygotsky’s Sociocultural Theory—particularly the Zone of Proximal Development (ZPD)—this study explores how English-majored students perceive the role of artificial intelligence (AI) tools in their academic learning. A survey of 186 students was analyzed using exploratory factor analysis (EFA), revealing two distinct but correlated factors: Metacognitive and Collaborative AI Use and Instrumental and Performance-Oriented Use. The former reflects students’ use of AI for idea generation, drafting, and self-directed learning, aligning with active cognitive engagement and guided learning within the ZPD. The latter emphasizes grade improvement, efficiency, and confidence building—highlighting a performance-focused orientation. The two-factor model explained 50% of the total variance and demonstrated good fit (RMSEA = 0.073; TLI = 0.869; RMSR = 0.05), with a moderate inter-factor correlation (r = 0.63).
To deepen the interpretation of these student perspectives, a parallel survey of 30 TESOL instructors is underway. This instructor survey is structured around the TPACK framework and Borg’s (2003) Teacher Belief and Practice Theory, focusing on how teachers with varying levels of experience (early-career, mid-career, and veteran) perceive and integrate AI into their teaching. Triangulating student and teacher data provides a more comprehensive understanding of the opportunities and challenges of using AI for formative feedback, learner support, and instructional planning in TESOL contexts. This study contributes practical insights into AI-enhanced pedagogy and its implications for supporting both learners and non-native English-speaking educators.
