Implementing Generative AI (GenAI) in Higher Education: A Systematic Review of Case Studies

Marina Belkina; Scott Arthur Daniel; Sasha Nikolic; Rezwanul Haque; Sarah Lyden; Peter Neal; Sarah Grundy; Ghulam Mubashar Hassan

doi:10.1016/j.caeai.2025.100407

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Implementing Generative AI (GenAI) in Higher Education: A Systematic Review of Case Studies

Journal article

Open access

Peer reviewed

Implementing Generative AI (GenAI) in Higher Education: A Systematic Review of Case Studies

Marina Belkina, Scott Arthur Daniel, Sasha Nikolic, Rezwanul Haque, Sarah Lyden, Peter Neal, Sarah Grundy and Ghulam Mubashar Hassan

Computers & Education. Artificial Intelligence, Vol.8, pp.1-15

2025

DOI: https://doi.org/10.1016/j.caeai.2025.100407

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Abstract

generative AI

education

GenAI

case study

university

implementation

The introduction of Generative Artificial Intelligence (GenAI) tools, like ChatGPT, into higher education heralds a transformative era, reshaping instructional methods, enhancing student support systems, and redefining the educational landscape. Recent literature reviews on GenAI highlight a lack of focus on how these tools are being practically implemented in educational settings. Addressing this gap, the present study systematically examines empirical case studies that demonstrate the integration of GenAI into teaching and learning in higher education, offering actionable insights and guidance for academic practice. We conducted a search of relevant databases and identified 21 empirical studies that met our inclusion criteria. The selected studies cover a diverse range of disciplines, locations, types of participants (from first-year students to postgraduates and academics), and a variety of methodologies. We classified the selected publications based on the pedagogic theory of Laurillard’s Conversational Framework (LCF) and the Substitution, Augmentation, Modification, and Redefinition (SAMR) framework. We also synthesized definitions from selected empirical studies and recent research exploring Technological Pedagogical Content Knowledge (TPACK) in the age of GenAI, providing a comprehensive understanding of GenAI-TPACK factors. Limitations and future research opportunities are also discussed. The paper concludes by providing a GenAI-TPACK diagram to guide educators in effectively incorporating GenAI tools into their teaching practices, ensuring responsible and impactful use in higher education.

Details

Title: Implementing Generative AI (GenAI) in Higher Education: A Systematic Review of Case Studies
Authors: Marina Belkina (Corresponding Author) - UNSW Sydney
Scott Arthur Daniel - University of Technology Sydney
Sasha Nikolic - University of Wollongong
Rezwanul Haque - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
Sarah Lyden - University of Tasmania
Peter Neal - UNSW Australia
Sarah Grundy - UNSW Sydney
Ghulam Mubashar Hassan - The University of Western Australia
Publication details: Computers & Education. Artificial Intelligence, Vol.8, pp.1-15
Publisher: Elsevier Ltd
Date published: 2025
DOI: 10.1016/j.caeai.2025.100407
ISSN: 2666-920X
Copyright note: This article is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.
Grant note: This work was supported by the 2023 Australian Council of Engineering Deans (ACED) and the Australasian Association for Engineering Education (AAEE) Grant.
Organisation Unit: School of Science, Technology and Engineering
Language: English
Record Identifier: 991120352502621
Output Type: Journal article

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