Vol. 2 No. 1 (2027): Volume 2, Issue 1 (2027)
Articles

From Digital Literacy to AI Literacy: A Systematic Review and Integrative Framework for Education

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  • Bahar Memarian,
  • Tenzin Doleck
Bahar Memarian
Simon Fraser University
Tenzin Doleck
Simon Fraser University
DOI: https://doi.org/10.46787/ijaipil.v2i1.7287

Published 2026-05-05

Keywords

  • artificial intelligence literacy,
  • AI literacy,
  • Artifical Intelligence (AI),
  • Education,
  • Review

How to Cite

Memarian, B., & Doleck, T. (2026). From Digital Literacy to AI Literacy: A Systematic Review and Integrative Framework for Education. International Journal of AI in Pedagogy, Innovation, and Learning Futures, 2(1). https://doi.org/10.46787/ijaipil.v2i1.7287

Copyright (c) 2026 Bahar Memarian, Tenzin Doleck

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Digital technology and associated literacies have expanded rapidly, with artificial intelligence (AI) literacy emerging as a critical area of focus. This shift underscores the need to understand AI and its role in supporting learning. While prior research has proposed various AI literacy frameworks and scales, existing reviews remain fragmented, and connections to foundational digital literacy models are often limited (D. R. Long et al., 2020). This study conducts a systematic literature review and applies a well-established digital literacy framework (Ng, 2012), which identifies cognitive, technical, and social-emotional dimensions, to examine how AI literacy has been conceptualized. A thematic analysis of selected studies is then used to identify gaps in existing frameworks and inform a more integrated conceptualization of AI literacy. A total of 516 studies were identified across Web of Science (292), Scopus (201), and Google Scholar (23), and following PRISMA screening, 72 studies were retained for analysis. The primary focus of AI literacy in each study was examined through thematic analysis and independent coding, followed by iterative consensus-building among the authors. Using this process, axial coding was conducted (Johnny Saldaña, 2016), which, in combination with the digital literacy framework, informed the development of a refined conceptualization of AI literacy. This study contributes by explicitly bridging AI literacy and digital literacy frameworks and reframing AI literacy as an extension of core literacy constructs.

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