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ABSTRACT
Generative artificial intelligence has been regarded as a transformative tool. While responsible and ethical applications could bring opportunities to education, their misuse could pose demanding challenges. It is necessary to clarify the technological affordances and challenges in a normative way to lay the foundation for future development. This study addressed the dearth of literature by performing a systematic review, aiming to (i) explore the utility and availability from the technological affordances perspective; (ii) summarize the current challenges in risks prevention; and (iii) propose possible directions for future research and practice. A total of 27 academic articles published in core journals between 2020 and 2023 were analyzed, and the inductive grounded approach was used to categorize the coding schemes. The findings revealed four technological affordances: accessibility, personalization, automation, and interactivity; and five challenges: academic integrity risk, response errors and bias, over-dependence risk, the widening digital divide, and privacy and security. We propose future directions, encourage educational organizations to formulate guidelines for the ethical use of AI in education, call on educators to embrace future trends in AI education instead of shunning its use, and guide students to treat it as a thought aid and reference, rather than relying on it entirely.
Acknowledgements
This study was supported by the National Science and Technology Council, Taiwan, under grant NSTC 111-2410-H-019-006-MY3 and NSTC 111-2423-H-153-001-MY3.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Nan Wang
Nan Wang is studying for a master’ s degree at Nanjing Normal University, China. Her research interests include Intelligent System, Information-based Instructional Design and Instructional Behavior Analysis.
Xiao Wang
Xiao Wang is studying for a master’ s degree at Nanjing Normal University, China. Her research interests include Intelligent System, Information-based Instructional Design and Instructional Behavior Analysis.
Yu-Sheng Su
Yu-Sheng Su is currently an associate professor of department of computer science and information engineering at National Chung Cheng University, Taiwan. His research interests include Cloud Computing, Big Data Analytics, Intelligent System, and Metaverse.