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Decoding AI ethics from Users' lens in education: A systematic review

Authors :
Qin An
Jingmei Yang
Xiaoshu Xu
Yunfeng Zhang
Huanhuan Zhang
Source :
Heliyon, Vol 10, Iss 20, Pp e39357- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

In recent years, Artificial Intelligence (AI) has witnessed remarkable expansion, greatly benefiting the education sector. Nonetheless, this advancement brings forth several ethical dilemmas. The existing research on these ethical concerns within the educational framework is notably scarce, particularly when viewed from a user's standpoint. This research systematically reviewed 17 empirical articles from January 2018 to June 2023, sourced from peer-reviewed journals and conferences, to outlined existing ethical framework in Artificial Intelligence in Education (AIED), identify related concerns from user's perspectives, and construct Ethics Guideline for AIED. The finding revealed that certain ethical aspects, including the ethics of learning analytics and the ethics of algorithms in AIED, are often neglected in the existing ethical frameworks, principles, and standards for AIED. Based on the blank between existing ethical frameworks and ethic concerns from user's perspectives, the research proposes more inclusive and thoughtfully Ethics Guideline for AIED. The study also provides actionable recommendations for multiple stakeholders, emphasizing the need for guidelines that address user-centered concerns. In addition, How this Ethics Guideline for AIED could be developed is discussed, along with outlining potential avenues for future research.

Details

Language :
English
ISSN :
24058440
Volume :
10
Issue :
20
Database :
Directory of Open Access Journals
Journal :
Heliyon
Publication Type :
Academic Journal
Accession number :
edsdoj.5c806e4a2d41473387481d05ca76ecb7
Document Type :
article
Full Text :
https://doi.org/10.1016/j.heliyon.2024.e39357