Reduce cheating holistically by enhancing perceived assessment purpose, fostering self-efficacy, and increasing perceived costs of cheating¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends that "efforts to reduce cheating should focus on enhancing the perceived purpose of assessments, fostering self-efficacy in a broad sense, and increasing the perceived costs of cheating". It insists all three areas are needed together: any approach focusing solely on one or two will likely fail. The strategy is grounded in the planned-behaviour framing and is linked to Dawson et al.'s (2024) validity framework, which aligns assessments with intrinsic motivation and self-efficacy through authentic, real-world tasks.

Design Implications¶

Context¶

Requirements¶

• All three focus areas must be addressed together, since partial approaches are expected to fail
• A holistic and adaptive model considering the dynamic nature of planned behaviour

Constraints¶

• The article notes promoting self-efficacy is difficult in practice because the hidden curriculum of individualism may inadvertently promote cheating as a shortcut

Target Learners¶

• university students

Target Learning Goals¶

• academic integrity
• intrinsic motivation for learning
• ethical engagement with assessment

Affordances¶

• Tpb Self Efficacy Account Of Ai Cheating

Related Strategies¶

• Enhance students' AI literacy while alleviating excessive academic stress to reduce over-dependence on generative AI
• Consider students' perceived control over fine-grained task facets (technology, pedagogy, content) when designing ITS learning experiences

Examples¶

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Key Sources¶

• Sandra Leaton Gray, Dominic Edsall, Dimitris Parapadakis. (2025). AI-Based Digital Cheating At University, and the Case for New Ethical Pedagogies. Journal of Academic Ethics. https://doi.org/10.1007/s10805-025-09642-y