Author Identifier (ORCID)
Abstract
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).
Keywords
academic integrity, artificial intelligence, contract cheating, higher education, theory of planned behaviour
Document Type
Journal Article
Date of Publication
1-1-2026
E-ISSN
15737608
ISSN
13602357
Publication Title
Education and Information Technologies
Publisher
Springer
School
School of Business and Law
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Senali, M. G. (2026). Extending the theory of planned behaviour to explain contract cheating in the age of generative AI: Evidence from Australian higher education. Education and Information Technologies. Advance online publication. https://doi.org/10.1007/s10639-026-14145-3