Fostering Metacognitive Skills Through AI-Human Dialogues: A New Paradigm for Language Learning

Abstract

This conceptual paper proposes a novel framework for fostering metacognitive skills in language learners through AI-human dialogues, presenting a new paradigm for language education in the 21st century. As generative AI technologies advance, their potential to revolutionise language learning remains largely untapped, particularly in developing higher-order thinking skills. This study addresses the critical question: How can AI-human dialogues be leveraged to foster metacognitive skills in language learners? Through a comprehensive literature review and conceptual analysis, we develop a framework that integrates AI capabilities with established metacognitive strategies. The proposed framework comprises five key components: Reflective Questioning, Strategy Awareness, Progress Monitoring, Error Analysis, and Adaptive Challenges. Each component is designed to engage learners in deep, personalised metacognitive processes, facilitated by AI's ability to model strategies, provide immediate feedback, and adapt to individual learning patterns. This paper discusses the potential benefits of the framework, including enhanced self-regulated learning, improved language acquisition efficiency, and increased learner autonomy. It also addresses challenges and ethical considerations, such as balancing AI guidance and learner independence and ensuring privacy in AI-human interactions. By presenting this innovative approach, we aim to stimulate further research and practical applications in the field, ultimately contributing to more effective and personalised language learning experiences in the AI era.