Content and AI Integrated Learning in Language Teaching for Enhanced AI Literacy

Abstract

The rapid advancement of artificial intelligence (AI) has created an urgent demand for widespread AI literacy, empowering individuals to navigate an increasingly AI-driven world with ethical awareness and critical thinking. However, existing AI curricula often emphasize technical understanding and coding skills, neglecting the integration of AI literacy into broader educational contexts. This study introduces Content and AI Integrated Learning (CAIIL), a novel pedagogical framework that adapts principles from Content and Language Integrated Learning (CLIL) and content-based education to modern AI education. CAIIL enables students to acquire AI knowledge and skills while learning traditional academic subjects such as mathematics, science, and the humanities.Using language teaching as a case study, the research demonstrates how integrating AI concepts into subject-specific learning fosters interdisciplinary knowledge, enhancing students’ understanding of both core disciplines and AI fundamentals. Through this approach, learners develop critical competencies such as data analysis, critical thinking, and ethical AI application, preparing them for success in a technology-driven future. By promoting a holistic understanding of AI within diverse academic contexts, CAIIL equips students to apply AI effectively and responsibly across a wide range of fields to achieve immersive learning.