Learners’ perceived AI presences in AI-supported language learning: a study of AI as a humanized agent from community of inquiry

Abstract

This study investigated the application of an artificial intelligence (AI) coach for second language (L2) learning in a primary school involving 327 participants. In line with Community of Inquiry, learners were expected to perceive social, cognitive, and teaching presences when interacting with the AI coach, which was considered a humanized agent. To examine how learners’ perceived AI presences were related to their language learning, this study drew on AI usage data, actual learning outcomes, and attitudinal data. Results from hierarchical regression analyses suggest that cognitive presence and learners’ affection for AI’s appearance were significant predictors of L2 enjoyment, which also positively predicted learning outcomes. The score of English shadowing (representing the quality of AI usage) positively predicted learning outcomes. Contrary to intuition, teaching presence was found to negatively predict learning outcomes. Based on cluster analysis and subsequent MANOVA results, this study indicates that the learners perceiving higher social and cognitive presences via interacting with AI and showing greater affection for AI’s appearance tended to use the AI coach more frequently, demonstrate higher L2 enjoyment, and achieve higher learning outcomes. The present study contributes to the limited but increasing knowledge of human-AI interaction in educational settings and carries implications for future efforts on the use of AI for L2 learning.

Keywords:

• Artificial intelligence
• language learning
• community of inquiry
• human-AI interaction

Notes on Contributors

Xinghua Wang is a professor in the Normal College at Qingdao University. He received his PhD in Learning Sciences and Technologies from Nanyang Technological University, Singapore. His research is related to technology-enhanced learning, human-computer interaction, and psychometrics.

Hui Pang is an associate professor in the Normal College at Qingdao University. Her research interest covers computer-assisted language learning, psycholinguistics, and teacher education.

Matthew P. Wallace is an assistant professor of applied linguistics in the Department of English, University of Macau, China. His research up to this point has focused on second language listening comprehension, language assessment fairness, and language learner motivation.

Qiyun Wang is a professor in Learning Sciences and Assessment Academic Group. He is also the Programme Leader of the Master of Education (Learning Sciences and Technologies), and the Chair of the Ethnic Clearance Committee of the Academic Group. He specialises in blended synchronous learning (using real-time video conferencing), technology-supported learning environment, and education design-based research.

Wenli Chen is a professor and the head of Learning Sciences and Assessment Academic Group at the National Institute of Education, Nanyang Technological University Singapore. Her research interests include Computer-Supported Collaborative Learning (CSCL), learning analytics, AI for Education, and mobile learning.

Disclosure statement

No potential conflict of interest was reported by the authors.