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Academic contract cheating (CC) poses a significant challenge for Higher Education (HE), a problem that has become more complex with the increasing use of Generative Artificial Intelligence (Gen AI) tools. While similarity detection software can flag AI-generated text, it remains ineffective in identifying CC, potentially displacing misconduct rather than reducing it. Drawing on and extending the Theory of Planned Behaviour (TPB), this study examines how traditional TPB constructs and technology-mediated perceptual factors jointly influence students’ intentions and behaviours related to CC within the Australian HE context. The findings reveal significant direct and indirect pathways linking perceived instructor involvement, detection awareness, AI-related risk perceptions, and perceived behavioural control to students’ intentions and behaviours. These results extend the TPB framework to the context of AI-mediated academic misconduct and offer practical implications for universities in Australia and potentially other similar contexts. The study provides actionable insights for HE institutions to design integrity policies, assessment strategies, detection mechanisms, and digital literacy initiatives to strengthen academic integrity in alignment with the United Nations Sustainable Development Goal (SDG) on Quality Education (Goal 4).
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Madugoda Gunaratnege Senali (2026) studied this question.
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