Published in the INTED2026 Proceedings (IATED), Valencia, Spain, March 2026.
Abstract
The rapid evolution of Artificial Intelligence (AI) and its dual-use implications for cybersecurity requires higher education institutions to prepare students with integrated technical, analytical, and ethical competencies. In response, this paper presents the pedagogical design, curriculum structure, and early educational outcomes of an undergraduate CyberAI program developed at a National Security Agency (NSA) Center of Academic Excellence in Cyber Operations (CAE-CO) designated institution. As one of the first six NSA-validated CyberAI programs in the United States, the curriculum is intentionally aligned with the NSA CyberAI Knowledge Units (KUs) to bridge traditional cyber operations education with AI-enabled analysis, automation, and decision-making.
The CyberAI program is grounded in outcomes-based education and employs a scaffolded instructional model that integrates theory, applied laboratories, and project-based learning. AI concepts are introduced progressively, moving from foundational machine learning principles to advanced adversarial and defensive AI applications within realistic cyber threat scenarios. Core courses include AI Governance, Law, and Ethics; AI and Machine Learning Fundamentals; AI for Security Assessment; and Defensive/Offensive Applications of AI. Each course incorporates hands-on laboratories, team-based exercises, and authentic assessments aligned to the required Knowledge, Skills, and Abilities outlined in the NIST/NICE Framework and Department of Defense Cyber Workforce Framework (DCWF) work roles and competencies. Experiential learning opportunities, including undergraduate research and industry-informed projects, further reinforce workforce relevance and applied skill development.
The paper also discusses faculty development, curriculum mapping processes, and institutional considerations required to align emerging AI content with established NSA CAE-CO and CyberAI standards. Preliminary educational outcomes demonstrate increased student enrollment, improved student engagement, expanded industry partnerships, and growth in undergraduate research focused on trustworthy AI and autonomous cyber defense systems.
This work contributes (1) a replicable, pedagogy-centered model for integrating CyberAI competencies into CAE-aligned undergraduate programs, and (2) evidence-based insights into how cybersecurity and AI education can co-evolve to address evolving workforce, educational, and national security demands.
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Citation
@inproceedings{straight2026,
author = {Straight, Ryan and Wagner, Robert Honomichl, Shengjie Xu,
Ryan Straight, and Li Xu, Paul},
publisher = {IATED},
title = {Integrating {AI} into {Cyber} {Operations} {Education}},
booktitle = {INTED2026 Proceedings (18th International Technology,
Education and Development Conference)},
date = {2026},
url = {https://ryanstraight.com/research/2026-03-01-cyberai-undergraduate-program/},
langid = {en}
}