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

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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Publication Details

Published
2025-03-06
DOI
https://doi.org/10.3390/proceedings2025114006
Citations
3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.96
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article

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

Audrey Ekuban, Joseph Kwarteng, Alexander Mikroyannidis, John Domingue
3 citations
Artificial Intelligence in Healthcare and Education
1.96
article

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

Audrey Ekuban, Joseph Kwarteng, Alexander Mikroyannidis, John Domingue
article en
3 citations

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.

The Open University (GB)
Quality Education
Openalex Percentile: Top 13%
Artificial Intelligence in Healthcare and Education
1.96
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Best Practices for the Responsible Adoption of Generative AI in Higher Education — Audrey Ekuban, Joseph Kwarteng, et al. · (2025) | TGRS Research Map | TGRS