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Дата издания
08.12.2025На каком языке издана
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2504284XОбласть исследования
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In the near future, AI may move beyond its role as a mere tool to function as a creative agent—potentially even as a virtual student or professor—capable of generating original artworks and contributing to research leadership. However, it remains unclear whether educational institutions are adequately prepared for such a rapid integration of AI into educational and research processes. This question becomes particularly relevant in the context of the rapid advancement of large language models (LLMs) and generative artificial intelligence (GenAI), given their potential to transform both the landscape of scientific research and educational methodologies. This study, therefore, examines how educational institutions are responding to the integration of AI into research and education. Specifically, we analyzed the policies and guidelines regulating the use of GenAI in both general universities and art-focused institutions, and conducted a strategic review of institutional approaches, along with a content analysis of selected curricula related to GenAI implementation. Based on the analysis, we posit that current GenAI policies in higher education are largely reactive, unevenly implemented across regions and disciplines, and often fail to address research-specific use cases and the distinct challenges faced by artfocused institutions. This finding aligns with recent studies showing that institutions tend to conform to external regulatory, normative, and mimetic pressures in their adoption of GenAI, often prioritizing legitimacy and compliance over proactive strategic vision (Singh, 2024). From an educational perspective, researchers further argued that Bloom’s Taxonomy requires revision to address the cognitive, affective, and metacognitive demands of AIassisted learning, underscoring the need for institutional policies that not only regulate GenAI but also foster critical thinking, ethical reasoning, and iterative learning processes in higher education (Gonsalves, 2024).DOI
https://doi.org/10.3389/feduc.2025.1644081Тип публикаций
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1.9Количество цитирований
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