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Using ChatGPT to Reduce Academic Misconduct in a Systems Analysis Course: a Case Study
Conference proceeding

Using ChatGPT to Reduce Academic Misconduct in a Systems Analysis Course: a Case Study

Raina Mason, Carolyn Seton and Jenelle Benson
AI Revolution: Research, Ethics and Society: International Conference, AIR-RES 2025, Las Vegas, NV, USA, April 14–16, 2025, Proceedings, Part III, pp.3-16
Communications in Computer and Information Science
01/2026
DOI: https://doi.org/10.1007/978-3-032-13056-3_1
Appears in  Recent Faculty of Science and Engineering Publications

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Abstract

This paper presents an observational study on the redevelopment of an Australian systems analysis and design course to incorporate a Generative Artificial Intelligence (GenAI) tool, primarily ChatGPT, for student skill development and assessment. Addressing concerns about academic misconduct, the course was redesigned following Sydney University’s “two-lane” approach to assessment. The study, conducted in a master of computing program, evaluated the effectiveness of this redesigned assessment approach. Findings indicate that while integrating GenAI tools was largely successful, unexpected outcomes necessitated further course improvements. Lessons learned from this study have implications for both postgraduate and undergraduate computing programs, emphasizing the need for continuous adaptation in assessment design to maintain academic integrity and enhance learning outcomes.

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