The proliferation of artificial intelligence (AI) across higher education systems presents new challenges and opportunities for quality assurance (QA), calling for more anticipatory, inclusive, and adaptive approaches. This paper examines the integration of AI governance into QA mechanisms through a comparative analysis of institutional policies, with particular attention to stakeholder engagement, academic integrity, and policy coherence within the European Higher Education Area (EHEA).

 

The core of the study is a multi-institutional review of AI-related frameworks adopted by European universities, identifying common regulatory patterns such as the requirement for disclosure of AI-generated content, restrictions on AI use in student assessment, the emergence of dedicated oversight bodies, and the varying degrees of involvement of academic staff and students in policy formation. The analysis reveals both innovation and fragmentation in current practices, highlighting the need for more harmonised and student-inclusive models of governance.

Within this broader landscape, the paper presents a detailed case study of the University of Warsaw. In September 2023, the Student Parliament initiated and adopted a resolution on the responsible use of AI in education, which subsequently formed the basis of a university-wide policy officially adopted by the University Council. This instance of student-led governance not only underscores the potential of learners as co-creators of QA frameworks but also exemplifies proactive institutional adaptation. The policy is now undergoing formal review, further reflecting a dynamic QA process. The case has gained international visibility through its discussion during a 4EU+ Alliance student conference, illustrating its potential for cross-border learning and transferability.

The paper concludes with recommendations for embedding AI governance within QA systems through participatory design, digital oversight tools, and multi-level engagement, thereby strengthening institutional resilience and academic values in the face of rapid technological transformation.

This paper was presented at EQAF and reflects the views of the named authors only.

ISSN: 1375-3797

Redefining "Proactive QA" in the AI Era: a student-driven policy model within international AI Governance frameworks

Stanisław Zabandżała
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