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评估沙特阿拉伯教育中生成式人工智能的整合:一项混合方法研究。

Evaluating generative AI integration in Saudi Arabian education: a mixed-methods study.

作者信息

Alammari Abdullah

机构信息

Faculty of Education, Curriculums and Teaching Department, Umm Al-Qura University, Makkah, Makkah, Saudi Arabia.

出版信息

PeerJ Comput Sci. 2024 Feb 16;10:e1879. doi: 10.7717/peerj-cs.1879. eCollection 2024.

DOI:10.7717/peerj-cs.1879
PMID:38435558
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10909195/
Abstract

Incorporating generative artificial intelligence (GAI) in education has become crucial in contemporary educational environments. This research article thoroughly investigates the ramifications of implementing GAI in the higher education context of Saudi Arabia, employing a blend of quantitative and qualitative research approaches. Survey-based quantitative data reveals a noteworthy correlation between educators' awareness of GAI and the frequency of its application. Notably, around half of the surveyed educators are at stages characterized by understanding and familiarity with GAI integration, indicating a tangible readiness for its adoption. Moreover, the study's quantitative findings underscore the perceived value and ease associated with integrating GAI, thus reinforcing the assumption that educators are motivated and inclined to integrate GAI tools like ChatGPT into their teaching methodologies. In addition to the quantitative analysis, qualitative insights from in-depth interviews with educators unveil a rich tapestry of perspectives. The qualitative data emphasizes GAI's role as a catalyst for collaborative learning, contributing to professional development, and fostering innovative teaching practices.

摘要

在当代教育环境中,将生成式人工智能(GAI)融入教育已变得至关重要。本文通过定量和定性相结合的研究方法,深入探讨了在沙特阿拉伯高等教育背景下实施GAI的影响。基于调查的定量数据显示,教育工作者对GAI的认知与应用频率之间存在显著相关性。值得注意的是,约一半的受访教育工作者处于对GAI整合有一定理解和熟悉的阶段,这表明他们在采用GAI方面有切实的准备。此外,该研究的定量结果强调了整合GAI所带来的感知价值和便利性,从而强化了教育工作者有动机且倾向于将ChatGPT等GAI工具融入其教学方法的假设。除了定量分析,对教育工作者进行深入访谈所获得的定性见解揭示了丰富多样的观点。定性数据强调了GAI作为协作学习的催化剂、促进专业发展以及培养创新教学实践的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae4d/10909195/4e8f483f9de6/peerj-cs-10-1879-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae4d/10909195/4e8f483f9de6/peerj-cs-10-1879-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae4d/10909195/4e8f483f9de6/peerj-cs-10-1879-g001.jpg

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Artificial intelligence in education: Addressing ethical challenges in K-12 settings.教育中的人工智能:应对K-12教育环境中的伦理挑战。
AI Ethics. 2022;2(3):431-440. doi: 10.1007/s43681-021-00096-7. Epub 2021 Sep 22.
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Out of the laboratory and into the classroom: the future of artificial intelligence in education.
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AI Soc. 2021;36(1):331-348. doi: 10.1007/s00146-020-01033-8. Epub 2020 Aug 9.
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Exploring the impact of artificial intelligence on teaching and learning in higher education.探索人工智能对高等教育教学与学习的影响。
Res Pract Technol Enhanc Learn. 2017;12(1):22. doi: 10.1186/s41039-017-0062-8. Epub 2017 Nov 23.