DIGITAL LIBRARY
AI IN HIGHER EDUCATION: NUANCED UNDERSTANDINGS OF COMPETENCE, ETHICS AND EQUITY
University of Leeds (UNITED KINGDOM)
About this paper:
Appears in: ICERI2024 Proceedings
Publication year: 2024
Pages: 6767-6775
ISBN: 978-84-09-63010-3
ISSN: 2340-1095
doi: 10.21125/iceri.2024.1633
Conference name: 17th annual International Conference of Education, Research and Innovation
Dates: 11-13 November, 2024
Location: Seville, Spain
Abstract:
The integration of artificial intelligence (AI) in higher education (HE) is reshaping traditional educational paradigms. This necessitates a deeper understanding of key terms such as competence, ethical and equitable within this context. This talk presents findings from an interdisciplinary and multi-stakeholder research project that explores these concepts through the perspectives of academics, professional staff, students and employers. Our qualitative approach aimed to capture the complex and context-dependent nature of these terms.

Our research reveals a nuanced understanding of competence that extends beyond conventional academic skills to encompass digital literacy, adaptability and ethical reasoning particularly in relation to AI. The term ethical was found to encompass a broad spectrum of concerns from data privacy and algorithmic bias to moral implications. Similarly, equitable highlighted the need to address access disparities and ensure that AI technologies benefit all students (and staff) regardless of socio-economic background or expertise. This underscores the necessity for educational frameworks that integrate AI literacy and ethical and equitable considerations as core competencies.

The findings emphasise the necessity of developing case studies which reflect specific contexts and avoid generic statements. For example, while digital literacy is recognised as a component of competence, its application and importance vary significantly across different academic disciplines and institutional settings. Ethical considerations also differ, with some stakeholders highlighting transparency in AI algorithms, while others focus on the implications of AI in academic integrity and student assessment.

Our study underscores the importance of involving a diverse range of stakeholders in discussions about AI in HE. This inclusive approach ensures policies and practices are not only comprehensive but also contextually relevant. This talk advocates for a redefinition of competence to incorporate AI-related skills and ethical awareness to meet the needs of different educational contexts.

This presentation will provide insights into the nuanced understandings of competence, ethical and equitable in the landscape of AI in HE. We will offer insights for educators, policymakers and technologists, emphasising the importance of context-specific case studies to inform equitable and ethical AI integration in HE.
Keywords:
Education, Artificial Intelligence, AI, Higher Education, Competence, Ethical, Equitable.