TY - JOUR
T1 - Unveiling the landscape of generative artificial intelligence in education
T2 - A comprehensive taxonomy of applications, challenges, and future prospects
AU - Samala, Agariadne Dwinggo
AU - Rawas, Soha
AU - Wang, Tianchong
AU - Reed, Janet Marie
AU - Kim, Jinhee
AU - Howard, Natalie-Jane
AU - Ertz, Myriam
PY - 2024/8/13
Y1 - 2024/8/13
N2 - 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.
AB - 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.
KW - AI applications in education
KW - ChatGPT
KW - Educational technology
KW - GenAI
KW - Generative AI
KW - Quality education
UR - http://www.scopus.com/inward/record.url?scp=85201268755&partnerID=8YFLogxK
U2 - 10.1007/s10639-024-12936-0
DO - 10.1007/s10639-024-12936-0
M3 - Article
AN - SCOPUS:85201268755
SN - 1360-2357
JO - Education and Information Technologies
JF - Education and Information Technologies
ER -