Drivers of academic dishonesty and multi-level prevention strategies: an umbrella review
DOI:
https://doi.org/10.19083/ridu.2026.2492Keywords:
Academic Integrity, Academic Dishonesty, Higher Education, Artificial Intelligence, Educational PolicyAbstract
Introducción: Academic dishonesty remains persistent in higher education, exacerbated by online assessment, contract cheating markets and generative AI.
Objective: This umbrella review synthesised review-level evidence on drivers of academic dishonesty and prevention strategies recommended for higher education.
Methodology: Searches were conducted in Scopus and Web of Science Core Collection from database inception to June 2025, without date restrictions, and complemented with citation searching. Seventy-eight peer-reviewed reviews were included. A structured extraction and coding instrument was piloted; review-level text segments were coded through keyword-assisted content analysis, independent coding and consensus. Findings are reported as non-exclusive review-level frequencies, not causal effect sizes.
Results: The most recurrent driver domains were motivation, attitudes and moral reasoning (43.6%), pressure, stress and workload (35.9%), assessment design and teaching context (33.3%), institutional governance gaps (28.2%) and technology-mediated opportunity (26.9%). The most frequent strategy domains were technology/AI and online-integrity guidance (73.1%), embedded integrity education (66.7%), institutional governance and policy (60.3%), monitoring controls (39.7%) and culture/communication (37.2%).
Conclusions: The findings support a multi-level integrity programme combining assessment redesign, curriculum-embedded integrity education, staff development, transparent policy, proportionate monitoring and continuing evaluation.
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Copyright (c) 2026 Valeria de Rosario Estrella-Bote, Maria Vallespir-Adillón, Martín Julián, Ruben Comas-Forgas
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