Author
Listed:
- Yifen Yin
(Macao Polytechnic University, Faculty of Humanities and Social Sciences)
- Zekai Zhang
(Guangdong Huaqian Accounting Firm)
- Zhenpeng Wang
(Macao Polytechnic University, Faculty of Humanities and Social Sciences)
- Ka Seng Fok
(Macao Polytechnic University, Faculty of Humanities and Social Sciences)
- Haoqian Hu
(Macao Polytechnic University, Faculty of Humanities and Social Sciences)
Abstract
China’s youth education policy mainly consists of three policy systems: youth policy, higher education policy, and talent policy. At present, the basic policy stance of the country towards artificial intelligence is to give equal importance to encouraging support and strict regulation. As an advanced language tool model, ChatGPT has the potential to revolutionize the quality of youth education, especially higher education. It is conducive to forming personalized learning for young people, promoting innovative thinking, enhancing the interactivity of youth learning, and stimulating the emergence and growth of blended learning models. At the same time, ChatGPT also poses technological and ethical challenges to youth education, including eliminating student autonomy in learning, triggering a crisis of educational integrity, weakening the emotional learning ecosystem, and triggering data security risks; In the era of ChatGPT, the government’s public policies should strive to achieve situational integration between ChatGPT and youth education, regulate and restrict the application boundaries of ChatGPT, highlight the educational concept of student subjectivity, be alert to the negative impact of ChatGPT on young people’s ideology, enhance the digital literacy and skills of teachers and students, and ensure their privacy and data security.
Suggested Citation
Yifen Yin & Zekai Zhang & Zhenpeng Wang & Ka Seng Fok & Haoqian Hu, 2025.
"Policy Analysis of Youth Education in the ChatGPT Era,"
Advances in Economics, Business and Management Research, in: Soon M. Chung & Fairouz Kamareddine & Azah Kamilah Draman & Sim Kwan Yong (ed.), Proceedings of 2024 4th International Conference on Public Management and Big Data Analysis (PMBDA 2024), pages 305-319,
Springer.
Handle:
RePEc:spr:advbcp:978-94-6463-656-7_30
DOI: 10.2991/978-94-6463-656-7_30
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