Systematic review reveals five instructional approaches and key barriers for integrating AI into K-12 cybersecurity education, highlighting the need for explainable tools and teacher training.
This systematic review (2020–2025) examines the pedagogical integration of artificial intelligence (AI) into introductory cybersecurity education. As AI-powered cyber threats evolve, cybersecurity education faces pressure to re-examine its pedagogical assumptions and objectives. Focusing on K-12 contexts while drawing insights from undergraduate studies, the review addresses three questions: (1) how AI is reshaping cybersecurity learning objectives, (2) which AI-augmented instructional approaches support learning outcomes, and (3) what implementation barriers educators face. The review identifies five promising AI-augmented instructional approaches and three categories of implementation challenges. Implications for practice emphasize the need for explainable tools, sustained educator professional development, and context-sensitive strategies that account for resource disparities between K-12 and higher education settings.
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Yang et al. (2026) studied this question.
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