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Artificial Intelligence Empowers Postgraduate Education Ecologically Sustainable Development Model Construction

Author

Listed:
  • Zhe Zhu

    (School of Marxism, Jilin University, Changchun 130000, China)

  • Lizhi Zhang

    (School of Marxism, Jilin University, Changchun 130000, China)

Abstract

Postgraduate education provides valuable intellectual resources for the development and progress of human society. At present, the development of postgraduate education in China is at a moderate level. The level of internationalization is not high, and there remain objective problems, such as a shortage of educational resources. To solve these problems, this paper proposes the use of artificial intelligence technology to build a sustainable development model for graduate students. It is aims to study the means of building a favorable environment for the development of postgraduate education and to optimize the educational structure of postgraduate studies, so as to improve the training model and enhance China’s international influence. Under the influence of the sustainable development model of educational ecology, developed under the background of artificial intelligence, this study included a questionnaire survey of current tutors, as well as doctoral and master’s students; a total of 30% of master’s students and 37% of doctoral students were “very satisfied” and “relatively satisfied” with the evaluation of “teaching content”.

Suggested Citation

  • Zhe Zhu & Lizhi Zhang, 2023. "Artificial Intelligence Empowers Postgraduate Education Ecologically Sustainable Development Model Construction," Sustainability, MDPI, vol. 15(7), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:7:p:6157-:d:1114985
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    References listed on IDEAS

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    1. Mohammad Ali & Jingjing Wang & Heather Himmelberger & Jennifer Thacher, 2021. "An Economic Perspective on Fiscal Sustainability of U.S. Water Utilities: What We Know and Think We Know," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 7(01), pages 1-30, January.
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