Agariadne Dwinggo Samala, Soha Rawas, Tianchong Wang, Janet Marie Reed, Jinhee Kim, Natalie-Jane Howard, Myriam Ertz
The rapid advancement of Generative Artificial Intelligence (GenAI) models, particularly ChatGPT, has sparked widespread discussion among educators and researchers regarding their potential implications for education. This study presents a comprehensive taxonomy of GenAI in academia and education, encompassing a wide range of applications, challenges, ethical considerations, and future prospects. Drawing on a scoping review of 453 articles, including the 50 most cited works throughout 2023, the taxonomy provides a state-of-the-art analysis of the current landscape of GenAI in education. The taxonomy offers a theoretical framework that aligns with the current discourse in GenAI and education, providing a critical evaluation of the existing literature and proposing innovative perspectives and solutions. The practical implications of the taxonomy for educators, researchers, and policymakers are highlighted, emphasizing the need for ethical considerations and informed policies to maximize the benefits of GenAI while minimizing its risks and negative impacts. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Faculty of Engineering, Universitas Negeri Padang, West Sumatra, Padang, Indonesia; Department of Mathematics and Computer Science, Beirut Arab University, Beirut, Lebanon; Flinders University, Adelaide, Australia; Kent State University, Kent, OH, United States; Old Dominion University, Norfolk, VA, United States; Lancaster University, Lancashire, Lancaster, United Kingdom; LaboNFC, University of Quebec at Chicoutimi, Saguenay, Canada
