Development of Evidence-Based Guidelines for the Integration of Generative AI in University Education Through a Multidisciplinary, Consensus-Based Approach.

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Tác giả: Yianna Danidou, Argyro Kavadella, Loucas Louca, James Mackay, Violetta Raffay, Loizos Symeou

Ngôn ngữ: eng

Ký hiệu phân loại: 372.427 School-based programs

Thông tin xuất bản: England : European journal of dental education : official journal of the Association for Dental Education in Europe , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 56793

 INTRODUCTION: The introduction highlights the transformative impact of generative artificial intelligence (GenAI) on higher education (HE), emphasising its potential to enhance student learning and instructor efficiency while also addressing significant challenges such as accuracy, privacy, and ethical concerns. By exploring the benefits and risks of AI integration, the introduction underscores the urgent need for evidence-based, inclusive, and adaptable frameworks to guide universities in leveraging GenAI responsibly and effectively in academic environments. AIMS: This paper presents a comprehensive process for developing cross-disciplinary and consensus-based guidelines, based on the latest evidence for the integration of GenAI at European University Cyprus (EUC). In response to the rapid adoption of AI tools such as LLMs in HE, a task group at EUC created a structured framework to guide the ethical and effective use of GenAI in academia, one that was intended to be flexible enough to incorporate new developments and not infringe on instructors' academic freedoms, while also addressing ethical and practical concerns. RESULTS: The framework development was informed by extensive literature reviews and consultations. Key pillars of the framework include: addressing the risks and opportunities presented by GenAI
  promoting transparent communication
  ensuring responsible use by students and educators
  safeguarding academic integrity. The guidelines emphasise the balance between, on the one hand, leveraging AI to enhance educational experiences, and, on the other maintaining critical thinking and originality. The framework also includes practical recommendations for AI usage, classroom integration, and policy formulation, ensuring that AI augments rather than replaces human judgement in educational settings. CONCLUSIONS: The iterative development process, including the use of GenAI tools for refining the guidelines, illustrates a hands-on approach to AI adoption in HE, and the resulting guidelines may serve as a model for other higher education institutions (HEIs) aiming to integrate AI tools while upholding educational quality and ethical standards.
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