Generative Artificial Intelligence-CALL (GAI-CALL)

Abstract

<p>The integration of generative artificial intelligence (GAI) into language learning can reshape the existing paradigm of computer-assisted language learning (CALL), which will continue with the evolution of GAI technology. While Intelligent CALL (ICALL) has relied on rule-based methods and natural language processing (NLP) to model learner behavior and generate adaptive responses, the recent emergence of GAI in the AI landscape, especially large language models (LLMs) such as ChatGPT, Grok, Gemini, Claude, Copilot, DeepSeek, and Perplexity, has paved the way for new perspectives on the approaches to AI-integrated language learning. In this article, we propose an innovative framework that reflects the contemporality of modern civilization in the era of post-method pedagogy: Generative Artificial Intelligence-CALL (GAI-CALL), which is the next phase in the development of CALL. Compared to previous models, GAI-CALL creates more dynamic, contextual, and learner-engaged language input and interaction opportunities. We highlight the technical, pedagogical, and theoretical nuances of GAI-CALL through a comparative analysis of existing CALL methods. This article presents a conceptual framework that places GAI-CALL as the subsequent chapter in the progression of CALL. Our framework, GAI-CALL, affords great possibilities for transforming language learning into a more personalized, engaging, and interactive experience that may be suitable for developed and developing regions in the Global South. This article offers guidance to language teachers, learners, trainers, curriculum and material developers, and points to avenues for future research to promote the responsible and effective use of GAI in language education.</p>

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