AI-Assisted Cyber Curricular Guideline Development: Enhancing Cognitive Rigor in Learning Outcomes

Abstract

As cybersecurity threats grow more sophisticated—often using Artificial Intelligence (AI)—academic programs must evolve just as quickly to ensure workforce readiness. In response, the US National Science Foundation (NSF) funded a project to create curricular guidelines to focus on Cybersecurity and Artificial Intelligence. A novel part of the project was accelerating Knowledge Unit (KU) development using a custom AI assistant to aide in creating and curating the content of the KUs. This paper presents an analysis of the learning outcomes produced through this process, comparing their cognitive levels to five frameworks: the National Security Agency (NSA) Cyber Defense and Cyber Operations KU sets, ACM Computing Curricula 2023, ACM Cyber2Y, and ACM Cybersecurity guidelines (CSEC) 2017. In addition to the cognitive classification, a textual analysis was conducted to assess the similarity between AI-generated KU suggestions and the final versions of each KU. Our findings reveal that the AI-assisted knowledge units demonstrate cognitive rigor that is on par with—or in some cases exceeds—that of established frameworks, particularly in their alignment with Bloom's taxonomy verb usage for learning outcomes. Additionally, many learning outcomes in the final KU closely mirror the AI-generated suggestions. These results suggest that AI can act as an effective collaborator in curricular guideline design, contributing not only to efficiency but also to consistency and academic rigor.

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