Guiding principles of generative AI for employability and learning in UK universities

被引:0
作者
Nartey, Emmanuel K. [1 ]
机构
[1] Open Univ, Milton Keynes, England
来源
COGENT EDUCATION | 2024年 / 11卷 / 01期
关键词
Generative AI; ChatGPT; higher education institutions; teaching and learning; guiding principles; employability; ARTIFICIAL-INTELLIGENCE TOOLS; EDUCATION; CHATGPT; FUTURE; IMPACT;
D O I
10.1080/2331186X.2024.2357898
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
This article explores the implications of Generative AI in higher education institutions, focusing on its impact on academic integrity and educational policy. The study utilises qualitative methods and desk-based research to investigate the adoption of Generative Pre-Trained Transformer and similar programs within academic settings. While some institutions have implemented bans on Generative AI due to concerns about plagiarism and ethical implications, others have embraced its potential to enhance educational practices under ethical guidelines. However, such prohibitions may overlook the advantages of Generative AI and ignore students' inevitable engagement with technology. The article addresses these challenges by proposing guiding principles for the ethical and efficient application of Generative AI in UK universities, particularly in the realms of employability, teaching, and learning. The article is structured into three main sections: a review of existing literature on Generative AI, an exploration of its benefits and challenges, formulation of guiding principles for its implementation, and recommendations for future research and practical implementation. Through this analysis, the article aims to contribute to the ongoing discourse surrounding Generative AI in higher education, providing insights into its implications for educational policy and practice.
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收藏
页数:27
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  • [91] Exploring the Potential Impact of Artificial Intelligence (AI) on International Students in Higher Education: Generative AI, Chatbots, Analytics, and International Student Success
    Wang, Ting
    Lund, Brady D.
    Marengo, Agostino
    Pagano, Alessandro
    Mannuru, Nishith Reddy
    Teel, Zoe A.
    Pange, Jenny
    [J]. APPLIED SCIENCES-BASEL, 2023, 13 (11):
  • [92] Warschauer M., 2023, The affordances and contradictions of AI -generated text for second language writers.
  • [93] Watermeyer R., 2023, Postdigital Science and Education, DOI DOI 10.1007/S42438-023-00440-6
  • [94] Watermeyer R., 2023, Postdigital Science and Education, P1
  • [95] Wong W.K.O., 2024, J. Open Innov. Technol. Mark. Complex, V10, P100278, DOI [10.1016/j.joitmc.2024.100278, DOI 10.1016/J.JOITMC.2024.100278]
  • [96] Yeralan S., 2023, Sustainable Engineering and Innovation, V5, P107, DOI [DOI 10.37868/SEI.V5I2.ID196, 10.37868/sei.v5i2.id196]
  • [97] Zhai X., 2022, ChatGPT User Experience: Implications for Education, DOI DOI 10.2139/SSRN.4312418
  • [98] A Review of Artificial Intelligence (AI) in Education from 2010 to 2020
    Zhai, Xuesong
    Chu, Xiaoyan
    Chai, Ching Sing
    Jong, Morris Siu Yung
    Istenic, Andreja
    Spector, Michael
    Liu, Jia-Bao
    Yuan, Jing
    Li, Yan
    [J]. COMPLEXITY, 2021, 2021
  • [99] Distinct biophysical and chemical mechanisms governing sucrose mineralization and soil organic carbon priming in biochar amended soils: evidence from 10 years of field studies
    Zhang, Haoli
    Ma, Tao
    Wang, Lili
    Yu, Xiuling
    Zhao, Xiaorong
    Gao, Weida
    Van Zwieten, Lukas
    Singh, Bhupinder Pal
    Li, Guitong
    Lin, Qimei
    Chadwick, David R.
    Lu, Shenggao
    Xu, Jianming
    Luo, Yu
    Jones, David L.
    Jeewani, Peduruhewa H.
    [J]. BIOCHAR, 2024, 6 (01)
  • [100] Zhang Y., 2023, Gastroenterology Endoscopy, V1, P139, DOI [10.1016/j.gande.2023.07.002, DOI 10.1016/J.GANDE.2023.07.002]