Language and Artificial Intelligence Literacy (LAIL): Emerging Competencies for Language Learners in the 21st Century
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Abstract
This Article aimed to establish and propose a comprehensive, integrative conceptual model called the Language and Artificial Intelligence Literacy (LAIL) Framework to address the rapidly evolving technological demands in modern language classrooms. As generative artificial intelligence (GenAI) and large language models (LLMs) act as active epistemic and meditational agents in education, traditional functional language learning models focusing strictly on communicative skills are no longer sufficient to preserve learner agency. This conceptual paper synthesizes contemporary scholarship at the intersection of critical language awareness, AI literacy, and associated digital competencies.
Within this proposed triadic framework, Language Literacy—reconceptualized through critical language awareness as advocated by McKinnon (2025)—and AI Literacy, drawing on the dimensions established by Ng et al. (2021) and Long and Magerko (2020), function as the core dual backbones. Other crucial 21st-century capabilities—namely Digital Literacy (Vuorikari et al., 2022), Media Literacy (Tuxanbayeva et al., 2026), and Information Literacy (Association of College and Research Libraries, 2015)—serve as vital supporting competencies. These domains are regulated by the central cognitive-ethical filters of critical thinking and critical literacy, preventing the risk of cognitive offloading (Iskandar et al., 2025).
By illustrating the essential boundaries between deterministic digital navigation and stochastic AI-mediated interaction, this paper outlines actionable techno-pedagogical strategies for educators, including scaffolded prompt engineering and process-focused verification pedagogy as described by Harsch et al. (2025). This paradigm shift counters the limitations of biased automated AI-plagiarism detectors and reframes communicative competence on a posthumanist spectrum where meaning-making is co-constructed with non-human digital agents. Ultimately, this framework contributes to the academic community by establishing a human-centered, ethically grounded model where technology serves to enhance, rather than erode, human intelligence and student autonomy in language acquisition.
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