THE APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGY IN EARLY CHILDHOOD LANGUAGE DEVELOPMENT
Abstract
Artificial intelligence (AI) tools are becoming more and more prevalent in early childhood education, but their effects on language development and the pedagogical settings in which they work best have not yet been thoroughly examined. This review takes a sociocultural stance and uses the Zone of Proximal Development (ZPD) theory to analyze AI-assisted language learning. Sixteen peer-reviewed empirical papers representing study contexts from various nations and regions that were published since 2021 and indexed in Web of Science (WoS) and Scopus were combined. Three types of AI tools are the main focus of current research: speech-based systems, social robots, and conversational agents/chatbots.The results show that children's linguistic engagement and participation during learning activities, story comprehension, and vocabulary acquisition all consistently gain from AI. According to ZPD, AI works best when it serves as a kind of scaffolding, facilitating interactional processes like dialogic prompting, instant feedback, and cooperative attention, and when these interactions are coordinated with kids' developmental needs under the direction of educators or caregivers. Overall, AI technologies show great promise for improving early language development when they are developed and used to supplement rather than replace socially mediated education. To support theory-informed and evidence-based integration of AI in early childhood language education, future research should make more use of longitudinal designs, expand validation across cross-cultural and multilingual contexts, and more precisely define scaffolding mechanisms.
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