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Cited by 20Artificial Intelligence in EducationGlobal Educational Policies and ReformsDigital Education and Society

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AI policies in school education: a comparative study on China, Singapore, Finland, and the US

Kundu, Arnab, Bej, Tripti·2025·Journal of Science and Technology Policy Management
DOI 10.1108/jstpm-06-2024-0218
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Abstract

Purpose The purpose of this study is to compare artificial intelligence (AI)-integration strategies in school education across China, Singapore, Finland and the USA, aiming to uncover shared patterns and localized innovations that could inform a globally responsive AI education framework. Design/methodology/approach The qualitative desktop study draws on secondary data from five recent government policy documents: China’s New Generation Artificial Intelligence Development Plan, Singapore’s EdTech Masterplan 2030, Finland’s Age of Artificial Intelligence, California’s Computer Science Strategic Implementation Plan and Massachusetts’ Digital Literacy and Computer Science Standards. These were analyzed using the SMART criteria and a researcher-constructed “Nine-point framework of operational components in AI policy for schools.” Findings Despite varying governance models and socio-cultural contexts, all four countries share a common intent to integrate AI into school education. Nine thematic propositions emerged: “SMART” policy design, balanced vision, curriculum and ethics integration, dynamic teacher training, equitable funding, multi-stakeholder partnerships, adaptive monitoring, localized implementation and contextual alignment. Finland and Singapore demonstrate strong ethical and human-centered policies, while China and the USA lean toward innovation and workforce development. Implementation remains challenged by equity gaps, teacher readiness and contextual mismatches. Res…

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References 28 · Cited by 20

Research works printed but not linked: 29

  1. Dexe, 2020, Nordic lights? National AI policies for doing well by doing good, Journal of Cyber Policy, 5, 332, 10.1080/23738871.2020.1856160 · DOI · Paper page
  2. Doran, 1981, There’s a S.M.A.R.T. Way to write management’s goals and objectives, Management Review, 70, 35
  3. Feldstein, 2023, Evaluating Europe’s push to enact AI regulations: how will this influence global norms?, Democratization, 31, 1, 10.1080/13510347.2023.2196068 · DOI
  4. Filipova, 2024, Legal regulation of artificial intelligence: Experience of China, Journal of Digital Technologies and Law, 2, 46, 10.21202/jdtl.2024.4 · DOI
  5. Gamito, 2023, The influence of China in AI governance through standardization, Telecommunications Policy, 47, 102673, 10.1016/j.telpol.2023.102673 · DOI
  6. Gursoy, 2023, Artificial intelligence research strategy of the United States: critical assessment and policy recommendations, Frontiers in Big Data, 6, 1206139, 10.3389/2Ffdata.2023.1206139 · DOI
  7. IEEE-USA (2021), “Artificial intelligence: Jobs, education, workforce, and diversity”, available at:Link to the cited article.
  8. Kaplan, 2018, Siri, Siri in my hand, who’s the fairest in the land? On the interpretations, illustrations and implications of artificial intelligence, Business Horizons, 62, 15, 10.1016/2Fj.bushor.2018.08.004 · DOI
  9. Khan, 2023, How to promote AI in the US federal government: Insights from policy process frameworks, Government Information Quarterly, 41, 10.1016/j.giq.2023.101908 · DOI
  10. Khanal, 2024, Development of new generation of artificial intelligence in China: When Beijing’s global ambitions meet local realities, Journal of Contemporary China, 34, 19, 10.1080/10670564.2024.2333492 · DOI
  11. Kwek, 2020, Policy and pedagogical reforms in Singapore: Taking stock, moving forward, Asia Pacific Journal of Education, 40, 425, 10.1080/02188791.2020.1841430 · DOI
  12. Kundu, 2025, Crafting effective school teachers: a comparative study of Finland, Japan, and India, International Journal of Comparative Education and Development, 10.1108/IJCED-05-2024-0042 · DOI
  13. Lai, 2024, The application of artificial intelligence technology in education influences Chinese adolescent’s emotional perception, Current Psychology, 43, 5309, 10.1007/s12144-023-04727-6 · DOI
  14. Lee, 2023, AI in education and learning analytics in Singapore: an overview of key projects and initiatives, Information and Technology in Education and Learning, 3, Inv-p001, 10.12937/itel.3.1.inv.p001 · DOI
  15. Lim, 2024, Verifying AI: will Singapore’s experiment with AI governance set the benchmark?, Communication Research and Practice, 10, 1, 10.1080/22041451.2024.2346416 · DOI
  16. Marda, 2018, Artificial intelligence policy in India: a framework for engaging the limits of data-driven decision-making, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376, 20180087, 10.1098/rsta.2018.0087 · DOI · Paper page
  17. Mertala, 2023, Finnish 5th and 6th graders’ misconceptions about artificial intelligence, International Journal of Child-Computer Interaction, 39, 100630, 10.1016/j.ijcci.2023.100630 · DOI
  18. Mochizuki, 2024, UNESCO, the geopolitics of AI, and china’s engagement with the futures of education, Comparative Education, 60, 478, 10.1080/03050068.2024.2335125 · DOI
  19. Mukhopadhyay, 2023, Academic Framework for 21st-Century Schooling: Promoting Global Peace and Harmony, 10.4018/978-1-6684-7005-3 · DOI
  20. Neyazi, 2023, Understanding user interactions and perceptions of AI risk in Singapore, Big Data and Society, 10, 10.1177/20539517231213823 · DOI
  21. Roberts, 2021, Ethics, Governance, and Policies in Artificial Intelligence. Philosophical Studies Series, 10.1007/978-3-030-81907-1_5 · DOI · Paper page
  22. UNESCO, 2023, Technology in education: a case study on Singapore. UNESCO: Paris, 10.54676/HOOV5879 · DOI
  23. Wei, 2023, AI in Learning: Designing the Future, 10.1007/978-3-031-09687-7_16 · DOI
  24. Wu, 2020, Ethical principles and governance technology development of AI in China, Engineering, 6, 302, 10.1016/2Fj.eng.2019.12.015 · DOI
  25. Wu, 2020, Towards a new generation of artificial intelligence in China, Nature Machine Intelligence, 2, 312, 10.1038/s42256-020-0183-4 · DOI · Paper page
  26. Xu, 2022, Present situation and enlightenment of artificial intelligence lifelong education system in Singapore, Journal of Autonomous Intelligence, 5, 1, 10.32629/jai.v5i1.499 · DOI
  27. Yuan, 2023, Where does AI-driven education, in the Chinese context and beyond, go next?, International Journal of Artificial Intelligence in Education, 34, 10.1007/s40593-023-00341-6 · DOI
  28. Zahra, 2021, The strategy of develop artificial intelligence in Singapore, United States, and United Kingdom, IOP Conf. Ser.: Earth Environ. Sci., 717, 12012, 10.1088/1755-1315/717/1/012012 · DOI · Paper page
  29. Nettel, P.F. (2023), “Canada’s AI policy: Leading the way in ethics, innovation, and talent – Oxford insights”, Oxford Insights, available at:Link to the cited article.

Metadata

Authors
Kundu, A., & Bej, T.
Affiliations
Institute for Educational Research and Policy School Research Division, , Bankura,
Corresponding author
Kundu, Arnab
ORCID
Venue
Journal of Science and Technology Policy Management
Publisher
Emerald
Published
2025-10-08
ISSN
  • 2053-4620 (ISSN-L)
  • 2053-4639
DOI
10.1108/jstpm-06-2024-0218
OpenAlex
W4414911487
Cited by
20
References
28
Citations by year
2026: 19 · 2025: 1
FWCI
20.80
Type
journal article
Language
en
Open access
closed
Locations
Journal of Science and Technology Policy Management (publishedVersion)
Funders
Institute for Educational Research and Policy (09/2024)
Topics
  • Social Sciences › Education › Artificial Intelligence in Education
  • Social Sciences › Political Science and International Relations › Global Educational Policies and Reforms
  • Social Sciences › Education › Digital Education and Society
Keywords
artificial intelligence in education, AI education policy, school education, AI integration strategies, teacher professional development, AI ethics, educational equity, multi-stakeholder partnerships, policy monitoring, comparative policy analysis, China, Singapore, Finland

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CoChat. (2026). Citation check: AI policies in school education: a comparative study on China, Singapore, Finland, and the US. https://app.cochat.ai/papers/10.1108/jstpm-06-2024-0218
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Kundu, A., & Bej, T. (2025). AI policies in school education: a comparative study on China, Singapore, Finland, and the US. Journal of Science and Technology Policy Management. https://doi.org/10.1108/jstpm-06-2024-0218