Best Practices for the Responsible Adoption of Generative AI in Higher Education

Mikroyannidis, Alexander; Ekuban, Audrey; Kwarteng, Joseph and Domingue, John (2025). Best Practices for the Responsible Adoption of Generative AI in Higher Education. Proceedings, 114(1) pp. 1–8.

DOI: https://doi.org/10.3390/proceedings2025114006

Abstract

In this paper, we propose a set of best practices for the responsible adoption of Generative Artificial Intelligence (AI) in higher education. These best practices provide a comprehensive framework for higher education institutions to effectively and ethically integrate Generative AI into their teaching and learning practices. The framework prioritises a responsible and human-centred approach, alongside pedagogical soundness, careful planning, transparency, as well as content quality. By exploring the responsible adoption of Generative AI in higher education, we seek to provide scalable, personalised learning experiences for large cohorts of students. Our research focuses on harnessing Generative AI to offer tailored educational content and generate constructive feedback for students. Additionally, by adhering to responsible AI practices, we aim to address challenges such as misinformation, copyright violations, and bias.

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