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Generative AI-Enhanced Intelligent Tutoring System for Graduate Cybersecurity Programs

Author

Listed:
  • Madhav Mukherjee

    (Institute of Cybersecurity and Cryptology, School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia)

  • John Le

    (Institute of Cybersecurity and Cryptology, School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia)

  • Yang-Wai Chow

    (Institute of Cybersecurity and Cryptology, School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia)

Abstract

Due to the widespread applicability of generative artificial intelligence, we have seen it adopted across many areas of education, providing universities with new opportunities, particularly in cybersecurity education. With the industry facing a skills shortage, this paper explores the use of generative artificial intelligence in higher cybersecurity education as an intelligent tutoring system to enhance factors leading to positive student outcomes. Despite its success in content generation and assessment within cybersecurity, the field’s multidisciplinary nature presents additional challenges to scalability and generalisability. We propose a solution using agents to orchestrate specialised large language models and to demonstrate its applicability in graduate level cybersecurity topics offered at a leading Australian university. We aim to show a generalisable and scalable solution to diversified educational paradigms, highlighting its relevant features, and a method to evaluate the quality of content as well as the general effectiveness of the intelligent tutoring system on subjective factors aligned with positive student outcomes. We further explore areas for future research in model efficiency, privacy, security, and scalability.

Suggested Citation

  • Madhav Mukherjee & John Le & Yang-Wai Chow, 2025. "Generative AI-Enhanced Intelligent Tutoring System for Graduate Cybersecurity Programs," Future Internet, MDPI, vol. 17(4), pages 1-19, March.
    • Handle: RePEc:gam:jftint:v:17:y:2025:i:4:p:154-:d:1624882
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