Collaborative Research: CyberAI Innovation: Building AI Auditing Competency through Learning Theory-Guided Adoptable Module Design

Artificial intelligence (AI) now shapes decisions in health care, finance, education, and national security. These systems can improve services, but they can also produce unsafe, opaque, or privacy-invasive outcomes. The United States needs professionals who can audit AI systems and judge whether they meet public expectations for trust, accountability, and security. Current AI and cybersecurity curricula rarely teach these practices. This project will address this gap by creating adoptable educational materials that help colleges prepare students for AI auditing roles. Students will learn to examine evidence, identify risks, document findings, and communicate judgments about AI systems. The work will strengthen the national workforce for AI assurance and cybersecurity. It will also help institutions teach responsible AI practices without requiring full curriculum redesign. The project will develop and validate a theory-guided education package for AI auditing in undergraduate and graduate computing programs. The team will create an AI audit competency framework aligned with federal guidance, standards, and established cybersecurity education structures. The package will include six modular curriculum units covering core areas such as AI auditing frameworks, model assessment, and continuous model auditing. Hands-on labs will use real-world datasets, auditing libraries, and audit documentation workflows. Students will practice evidence collection, risk assessment, mitigation implementation, and professional reporting. The project will also develop competency-based assessments, including scenario-based tasks, reports, rubrics, and tests. A multi-site evaluation will measure student learning, instructor usability, adoption, and sustainability. The project will produce reusable curricular materials, validated assessment instruments, and empirical evidence demonstrating how AI auditing competencies transfer across courses, instructional modalities, and learner populations. This project is supported by the CyberAICorps Scholarship for Service (CyberAI SFS) program which funds proposals to increase national capacity to educate and train professionals in Artificial Intelligence (AI) or Cybersecurity, and to support their placement and retention in the CyberAI mission of government organizations. The Scholarship Track funds academic institutions to award scholarships to students in exchange for their government service. The Innovation Track seeks transformative education proposals in the areas of AI, cybersecurity, or the integration of AI and cybersecurity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.