AI literacy for teacher educators: a holistic curriculum for capacity-building in higher education

The emerge of Generative Artificial Intelligence (GenAI) sparked diverse reactions within the educational sector, from enthusiasm to prohibition. The core question is no longer whether educators should use GenAI, but rather what skills, knowledge, and mindset they need to use AI effectively and responsibly. Educational AI literacy focuses on the competencies educators must develop to understand, utilize, and critically evaluate AI in teaching, learning, and assessment. However, fostering educational AI literacy requires more than simply identifying and defining necessary competencies; existing literature does not adequately address providing a comprehensive curriculum for developing AI literacy in educational contexts. Drawing on an integration of conceptual theory, empirical research, and the author's extensive experience in faculty development across diverse international contexts, this conceptual paper introduces a holistic, participatory, and inquiry-driven curriculum framework for developing AI literacy among teacher educators in higher education. The synergy of these three sources of knowledge ensures a theoretically grounded and practically relevant foundation for the framework's design. Developed through an iterative process of design, implementation, and evaluation, the framework offers structured guidance for creating, embedding, and assessing AI literacy initiatives responsive to the unique needs and institutional contexts of higher education settings. Rather than prescribing a fixed hierarchical sequence, the framework is intentionally designed as a flexible blueprint—an open-ended roadmap, where the curriculum's depth and breadth can be adapted to an institution's AI-readiness and its broader mission regarding educators’ expected AI proficiency or mastery. Additionally, the analytical study addresses potential implementation challenges, strategies to mitigate them, and implications for stakeholders.

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Publication Details

Journal
Frontiers in Education
Published
2026-04-14
DOI
https://doi.org/10.3389/feduc.2026.1745768
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
35.94
Controls
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article

AI literacy for teacher educators: a holistic curriculum for capacity-building in higher education

Sima Caspari-Sadeghi
1 citations
Frontiers in Education
Online Learning and Analytics
35.94
article

AI literacy for teacher educators: a holistic curriculum for capacity-building in higher education

Sima Caspari-Sadeghi
article en
1 citations

Abstract

The emerge of Generative Artificial Intelligence (GenAI) sparked diverse reactions within the educational sector, from enthusiasm to prohibition. The core question is no longer whether educators should use GenAI, but rather what skills, knowledge, and mindset they need to use AI effectively and responsibly. Educational AI literacy focuses on the competencies educators must develop to understand, utilize, and critically evaluate AI in teaching, learning, and assessment. However, fostering educational AI literacy requires more than simply identifying and defining necessary competencies; existing literature does not adequately address providing a comprehensive curriculum for developing AI literacy in educational contexts. Drawing on an integration of conceptual theory, empirical research, and the author's extensive experience in faculty development across diverse international contexts, this conceptual paper introduces a holistic, participatory, and inquiry-driven curriculum framework for developing AI literacy among teacher educators in higher education. The synergy of these three sources of knowledge ensures a theoretically grounded and practically relevant foundation for the framework's design. Developed through an iterative process of design, implementation, and evaluation, the framework offers structured guidance for creating, embedding, and assessing AI literacy initiatives responsive to the unique needs and institutional contexts of higher education settings. Rather than prescribing a fixed hierarchical sequence, the framework is intentionally designed as a flexible blueprint—an open-ended roadmap, where the curriculum's depth and breadth can be adapted to an institution's AI-readiness and its broader mission regarding educators’ expected AI proficiency or mastery. Additionally, the analytical study addresses potential implementation challenges, strategies to mitigate them, and implications for stakeholders.

Frontiers in EducationVol. 11
Institute for Learning and Development (US)
Quality Education
Openalex Percentile: Top 0%
Online Learning and Analytics
35.94
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