Artificial Intelligence as a Pedagogical Scaffold in K–12 Language and Literacy Education

Abstract

The artificial intelligence (AI) in language and literacy teaching at K-12 has expanded the opportunities of individualization in language learning. This systematic review, using the theory of sociocultural learning developed by Vygotsky and the Zone of Proximal Development (ZPD) in its explanations, describes the support of scaffolding learning provided by AI-powered education technologies in K12- language classroom settings. Drawing on the outcomes of empirical data gathered during the period of 2020-25, this review aims to synthesize the prior studies to understand how adaptive technologies, including ChatGPT, Grammarly, and Duolingo, can influence the needs of learners by providing real-time feedback, natural language processing, and content adaptation. The results confirm AI systems as similar to MKO dynamic mediators that fill in gaps in the capacity of learners to negotiate the ZPD. The implications of this research based on the AI-based tools is that the tooling should encourage equal, and non-discriminatory, language learning. It also requires cooperative consultation between educators, AI developers and policymakers in order to influence the moral integration within school curricula. Building on prior empirical work, this review is one of several contributors to current debate regarding the extent to which intelligent technology can be a pedagogic agent that supports individualized and scaffolded language learning at scale.