article · F1000Research
A systematic review of over fifty peer-reviewed articles and institutional policy frameworks published between 2021 and 2026 examines the impact of generative artificial intelligence on higher education. The findings reveal that more than 64 percent of undergraduate students use artificial intelligence tools without formal institutional guidance or constraints. Traditional detection-based methods for managing academic dishonesty are steadily losing their effectiveness, resulting in contradictions where ambiguous regulations leave educators struggling to balance technological adoption with academic integrity. To address this challenge, governance frameworks must shift from punitive enforcement to an empowerment model that treats artificial intelligence literacy as a fundamental competency. Recommendations for universities include implementing mandatory artificial intelligence literacy classes for first-year students, instituting uniform disclosure policies, and adopting process-oriented assessment methods that emphasise relational originality.
The rapid uptake of generative artificial intelligence has rendered conventional anti-plagiarism mechanisms unreliable. By understanding where policy gaps exist, higher education leaders can transition away from ineffective surveillance toward structured digital governance. Teaching students how to engage with artificial intelligence transparently ensures that university degrees remain credible, relevant, and aligned with modern workplace demands.
The abstract does not indicate an application pathway, as the study focuses entirely on university policy frameworks and educational governance.
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The proliferation of Generative Artificial Intelligence (GenAI) in higher education, particularly among undergraduate student population, has raised major contradiction about the traditional notions of academic integrity. This study reviewed related literatures to evaluate the balance of choice between digital governance and academic integrity, with intention of shifting the focus of educators from enforcement of academic integrity to student empowerment strategy through AI-literacy. Altogether, over 50 peer-reviewed articles and institutional policy frameworks published in peer-reviewed journals between 2021 and 2026 were solicited, and synthesized as part of the systematic review process. The key findings revealed a significant policy gap in which over 64% of undergraduate students are utilizing AI tools without formal institutional guidance or constraints. The other significant findings show that the traditional detection-based methods of academic dishonesty are losing their effectiveness, and could lead to a stability contradiction where ambiguous rules cause educators to struggle with competing balance of choice between AI adoption and academic integrity. Overall, the research findings draw the attention of educators and stakeholders to a new empowerment strategy that view AI-literacy as a competency ability to reduce intentional misbehavior in academic process. The study concludes that in order for undergraduate education to continue to be relevant in a society where AI is pervasive, governance must change toward process-oriented evaluation and relational originality. The other key suggestions include making AI-literacy classes mandatory for first-year students, and establishing uniform disclosure policies to encourage transparency and intellectual responsibility.
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DOI: 10.12688/f1000research.179680.1
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