Research Article
Generative artificial intelligence and sustainable higher education: Mapping the potential
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1 Department of Early Childhood Education, National and Kapodistrian University of Athens, Athens, GREECE* Corresponding Author
Journal of Digital Educational Technology, 5(1), January 2025, ep2506, https://doi.org/10.30935/jdet/15860
Submitted: 22 November 2024, Published: 15 January 2025
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ABSTRACT
Generative artificial intelligence (GAI) becomes widespread in higher education, and it creates new educational possibilities, with a potential to transform the educational process and promote sustainability. This study aims to explore the potential of GAI tools such as ChatGPT in promoting sustainable higher education. ChatGPT was utilized to aid the investigation at the initial stage, while the output generated was reviewed and edited by the researcher. It is indicated that GAI’s integration into higher education can lead to advancements in sustainability, such as enhancing educational practices (e.g., personalized learning, automated assessment and feedback, and educators’ professional development), optimizing resource utilization (e.g., digital learning resources, and efficient energy use), supporting inclusive and accessible education, and promoting environmental awareness and sustainability. Through these contributions, GAI can assist in the creation of more efficient, inclusive, and sustainable educational environments. It is suggested that higher education policies are modified and re-formulated to serve sustainable development, while empirical research on GAI implementation in higher education is a necessity (most publications are theoretical/conceptual). Limitations and ethical considerations should also be addressed. The study contributes to the ongoing debate on the role of GAI for sustainability in higher education.
CITATION (APA)
Nikolopoulou, K. (2025). Generative artificial intelligence and sustainable higher education: Mapping the potential. Journal of Digital Educational Technology, 5(1), ep2506. https://doi.org/10.30935/jdet/15860
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