A Model for Artificial Intelligence (AI) Literacy Education: Reflections on Teaching Graduate-Level Teacher Education Courses

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Authors: Hyunjin Jinna Kim
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Abstract

This practice-oriented self-study examines the development of an artificial intelligence (AI) literacy education model grounded in my reflective teaching practices and journey in graduate-level teacher education courses. As AI tools become increasingly embedded in educational and everyday technologies, both teachers and learners often remain unaware of the algorithms, data ethics, and biases that shape AI-driven systems (Ghallab, 2019; Ng et al., 2022). Recognizing that many teachers and teacher candidates responsible for educating the next generation have a minimal understanding of AI tools’ limitations and the ethical risks involved in AI use, I drew on my own experiences and knowledge as a language teacher educator to design the proposed model. Informed by Ng et al.’s (2022) AI literacy framework and constructionist approach, this article provides a model that integrates intentional opportunities for students to know, apply, and evaluate AI. I further discuss ways to promote students’ critical interrogation of AI-generated output while fostering responsible AI use.

Fields of Study & Subjects

Artificial Intelligence in Education Digital literacy in education Digital Education and Society

Publication details

Journal / source
Academic Commons (Stony Brook University)
Publication date
12 January 2026