Language Learning Development in Human-AI Interaction: A Thematic Review

• In Event: Educator Perceptions and Uses of AI

Abstract

Interaction is essential for language learning. Artificial intelligence (AI) is increasingly applied in language learning to promote interaction. In response to the paradigmatic shifts in AI application design, this review maps the research landscape of language learning development in human-AI interaction. Based on 49 studies, this study investigates contextual characteristics by AI-supported interaction type, AI application, target language, etc. Moreover, three research paradigms are identified in this emerging field, i.e., Paradigm One (AI-directed, teacher-as-facilitator, learner-as-recipient), Paradigm Two (AI/teacher-codirected, learner-as-collaborator), and Paradigm Three (AI/teacher/learner-codirected). The paradigms are induced from eight constructs: human-AI relationship, learning objective, task type, level of pre-structuring, mode of engagement behavior, knowledge-change process, cognitive outcome, and research focus. This positioning study reveals their different philosophical and linguistic underpinnings.

Authors

• Feifei Wang, The Chinese University of Hong Kong

• Alan C. K. Cheung, The Chinese University of Hong Kong

• Ching Sing Chai, Chinese University of Hong Kong