APPLICATION PROSPECT AND RISK ANALYSIS OF GENERATIVE ARTIFICIAL INTELLIGENCE TECHNOLOGY IN HIGHER EDUCATION

Authors

  • Ling Zhang (Corresponding Author) Jiangxi Regional Development Research Institute, Jiangxi University of Technology, Nanchang 330098, Jiangxi, China.

Keywords:

Generative artificial intelligence, Higher education, Application potential, Application risk

Abstract

Nowadays, generative artificial intelligence technology is closely related to many subdivisions in higher education, and its impact on higher education is increasingly apparent. This paper discusses the potential and risk of the application of generative artificial intelligence technology in higher education. In terms of application potential, it can be divided into five aspects: innovation of learning mode, effective promotion of knowledge production, extension of evaluation system dimension, wisdom innovation of teaching mode, and stimulation of educational concept transformation. In terms of application risk, it is mainly divided into five aspects: the doubt of knowledge legitimacy and authenticity, the risk of data security and privacy, the impact on students' discerning and creative thinking, the ban on users' imagination and innovation, and the ethical and moral risks associated with information output. The application of generative artificial intelligence technology in the field of education involves a multi-faceted and multi-level process. It is necessary to clarify the advantages and disadvantages of generative artificial intelligence technology in order to better play the potential of generative artificial intelligence application in the field of education and promote the digital transformation and upgrading of education.

References

[1] Wang Tianming, Cong Xiaoli. Research on Artificial intelligence assisting tourism development in Hainan. Guide of Economic Research, 2019, (08): 108-110.

[2] Ye Ni, Yu Guoming. Innovative Content Production based on AIGC Extension: Scenarios, users and core elements. Social Science Front, 2023, (10): 58-65.

[3] Guo Yike. On the History, Present Situation and Future Development Strategy of Artificial Intelligence. People's Forum. Academic Frontiers, 2021, (23): 41-53.

[4] Wang Jing-jing, Ye Ying. Analysis on the transformation of information management and communication by generative AI and its GPT technology application. Journal of Library Science, 2023, 49(06): 41-50.

[5] Yu Guoming, Li Vanadium, Teng Wenqiang. AI+ Education: Upgrading and transformation of teaching model in the era of Artificial Intelligence. Ningxia Social Sciences, 2024, (02): 191-198.

[6] Fan Wei, Zeng Lei. Analysis on intelligent data generation Path for the activated utilization of cultural heritage in the new Era of AI. Journal of Libraries of China, 2024, 50(02): 4-29.

[7] Wan Ping, Gu Xiaoqing. Human-machine Collaborative Evaluation supported by Generative Artificial Intelligence: Practice model and Explanatory case. Modern Distance Education, 2024, (02): 33-41.

[8] Qin Yuchao, Liu Geping, Xu Ying. How Generative Artificial Intelligence reshapes Teaching activities: Model construction and application based on activity theory. China Distance Education, 2023, 43(12): 34-45.

[9] Xiao Jun, Reconstruction and Collaboration: Thinking of "Breaking Five Only" from the perspective of Generative Artificial Intelligence. Journal of Higher Education Administration, 2024, 18(02): 53-64.

[10] Cheng Sifan.ChatGPT Knowledge Production Framework, Technical myths and future evolution. Contemporary Communication, 2023, (06): 60-64.

[11] Liu Zhifeng, Wu Yaping, Wang Jimin. Influence of artificial Intelligence-generated content Technology on Knowledge Production and Dissemination. Journal of Information, 2023, 42(07): 123-130.

[12] Miganin, Dong Changqi. The era of Grand Model: the generative form of knowledge "emergence". Xuehai, 2024, (01): 81-96+214-215.

[13] Li Sen, Zheng LAN. Challenges and Responses of Generative Artificial Intelligence to Classroom Teaching. Curriculum. Teaching Materials. Teaching Methods, 2019, 44(01): 39-46.

[14] Zhou Wenhui, ZHAO Jinmin. The value and challenge of ChatGPT to the cultivation of graduate students' innovation ability. Journal of University Education Administration, 2019, 18(02): 42-52.

[15] Yang Zongkai, Wang Jun, Wu Di, et al. ChatGPT/ Generative Artificial Intelligence's impact on education and its countermeasures. Journal of East China Normal University (Educational Science Edition), 2023, 41(07): 26-35.

[16] He Qizong, Yan Zhiwei. The Aesthetic Quality of teachers in the era of Artificial Intelligence: Why it is necessary and Why it is generated. China Audio-Visual Education, 2021, (11): 46-53.

[17] Li Yanyan, Zheng Yafeng. Educational application of Generative Artificial Intelligence. People's Forum, 2023, (23): 69-72.

[18] Wu Gang, Yuan Lei. The Logic of Education and the Temptation of Artificial Intelligence. Educational Review of Peking University, 2023, 21(01): 2-26+187.

[19] Yang Xiaozhe, Wang Qingqing, Jiang Jialong. Analysis of teacher-student dialogue in classroom based on artificial intelligence: Automatic classification and level construction of IRE. Research on Audio-visual Education, 2023, 44(10): 79-86.

[20] Liu Bangqi. The Core value of classroom transformation enabled by artificial intelligence: wisdom generation and model innovation. Open Education Research, 2022, 8(04): 42-49.

[21] Zhai Xuesong, Chu Xiaoyan, Jiao Lizhen, et al. Research on Human-machine collaborative learning model based on "Generative Artificial intelligence + meta-universe". Open Education Research, 2023, 29(05):26-36.

[22] Zhou Ling, Wang Feng. Educational implications of generative artificial Intelligence: Let everyone be himself. China Audio-visual Education, 2023, (05): 9-14.

[23] Shang Zhichun, Yan Yuhong. The application of ChatGPT in education and its changes and ethical challenges. Journal of Northeast Normal University (Philosophy and Social Sciences Edition), 2023, (05): 44-54.

[24] Xiao Jun, Reconstruction and Collaboration: Thinking of "Breaking Five Only" from the perspective of Generative Artificial Intelligence. Journal of Higher Education Administration, 2024, 18(02): 53-64.

[25] Zhang Zhi. The Underlying logic and possible Path of ChatGPT/ Generative Artificial Intelligence Reshaping Education. Journal of East China Normal University (Educational Science Edition), 2023, 41(07): 131-142.

[26] Xiong Yu, Wang Ying, CAI Ting, et al. Modern Distance Education, 2023, (01): 32-39

[27] Wu Qinghua, Guo Lijun. Teaching Reform in Higher vocational colleges in the era of generative artificial Intelligence: Challenges, framework and path. University Education Science, 2023, (06): 112-120.

[28] Xu Lei. Integrated Regulation of content risk in Generative Artificial Intelligence. Publication and Distribution Research, 2024, (01): 59-66.

[29] Song Huajian. On the legal risk and governance path of Generative Artificial Intelligence. Journal of Beijing Institute of Technology (Social Sciences), 2024, 26(03): 134-143.

[30] 3. Fang Jiaojiao, Gao Tianshu. Hidden trouble of Generative Artificial Intelligence assisted administrative decision algorithm and its governance path. H

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Published

2024-01-01

Issue

Vol. 6 No. 3 (2024)

Section

Articles

DOI:

https://doi.org/10.61784/ejst3010

How to Cite

Ling Zhang. Application prospect and risk analysis of generative artificial intelligence technology in higher education. Eurasia Journal of Science and Technology. 2024, 6(3): 13-19. DOI: 10.61784/ejst3010.