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Promoting Students’ Well-Being by Developing Their Readiness for the Artificial Intelligence Age

Author

Listed:
  • Yun Dai

    (Department of Curriculum and Instruction, The Chinese University of Hong Kong, Hong Kong, China)

  • Ching-Sing Chai

    (Department of Curriculum and Instruction, The Chinese University of Hong Kong, Hong Kong, China
    Centre for Learning Sciences and Technologies, The Chinese University of Hong Kong, Hong Kong, China)

  • Pei-Yi Lin

    (Department of Curriculum and Instruction, The Chinese University of Hong Kong, Hong Kong, China)

  • Morris Siu-Yung Jong

    (Department of Curriculum and Instruction, The Chinese University of Hong Kong, Hong Kong, China
    Centre for Learning Sciences and Technologies, The Chinese University of Hong Kong, Hong Kong, China)

  • Yanmei Guo

    (Teacher Training and Development Centre of Chaoyang District, Beijing 100082, China)

  • Jianjun Qin

    (School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100081, China)

Abstract

This study developed and validated an instrument to measure students’ readiness to learn about artificial intelligence (AI). The designed survey questionnaire was administrated in a school district in Beijing after an AI course was developed and implemented. The collected data and analytical results provided insights regarding the self-reported perceptions of primary students’ AI readiness and enabled the identification of factors that may influence this parameter. The results indicated that AI literacy was not predictive of AI readiness. The influences of AI literacy were mediated by the students’ confidence and perception of AI relevance. The students’ AI readiness was not influenced by a reduction in their anxiety regarding AI and an enhancement in their AI literacy. Male students reported a higher confidence, relevance, and readiness for AI than female students did. The sentiments reflected by the open-ended responses of the students indicated that the students were generally excited to learn about AI and viewed AI as a powerful and useful technology. The student sentiments confirmed the quantitative findings. The validated survey can help teachers better understand and monitor students’ learning, as well as reflect on the design of the AI curriculum and the associated teaching effectiveness.

Suggested Citation

  • Yun Dai & Ching-Sing Chai & Pei-Yi Lin & Morris Siu-Yung Jong & Yanmei Guo & Jianjun Qin, 2020. "Promoting Students’ Well-Being by Developing Their Readiness for the Artificial Intelligence Age," Sustainability, MDPI, vol. 12(16), pages 1-15, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:16:p:6597-:d:399126
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    References listed on IDEAS

    as
    1. Vasile Gherheș & Ciprian Obrad, 2018. "Technical and Humanities Students’ Perspectives on the Development and Sustainability of Artificial Intelligence (AI)," Sustainability, MDPI, vol. 10(9), pages 1-16, August.
    2. Thomas K.F. Chiu & Ching-sing Chai, 2020. "Sustainable Curriculum Planning for Artificial Intelligence Education: A Self-Determination Theory Perspective," Sustainability, MDPI, vol. 12(14), pages 1-18, July.
    3. United Nations UN, 2015. "Transforming our World: the 2030 Agenda for Sustainable Development," Working Papers id:7559, eSocialSciences.
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    Cited by:

    1. Ching Sing Chai & Xingwei Wang & Chang Xu, 2020. "An Extended Theory of Planned Behavior for the Modelling of Chinese Secondary School Students’ Intention to Learn Artificial Intelligence," Mathematics, MDPI, vol. 8(11), pages 1-18, November.
    2. Piotr Gaczek & Grzegorz Leszczyński & Yuling Wei & Hao Sun, 2026. "The Bright Side of AI in Marketing Decisions: Collaboration with Algorithms Prevents Managers from Violating Ethical Norms," Journal of Business Ethics, Springer, vol. 204(4), pages 771-794, April.
    3. Janet Hanson & Chong Ho (Alex) Yu & Michael Hung Truong, 2025. "Reframing Avatar-Mediated Instruction in Higher Education: A Theory-Building Integrative Review," International Journal of Learning and Development, Macrothink Institute, vol. 15(2), pages 17-55, June.
    4. Panteha Farmanesh & Asim Vehbi & Niloofar Solati Dehkordi, 2025. "AI Literacy in Achieving Sustainable Development Goals: The Interplay of Student Engagement and Anxiety Reduction in Northern Cyprus Universities," Sustainability, MDPI, vol. 17(11), pages 1-18, May.
    5. Ines Djokic & Nikola Milicevic & Nenad Djokic & Borka Malcic & Branimir Kalas, 2024. "Students’ Perceptions of the Use of Artificial Intelligence in Educational Service," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(65), pages 294-294, February.
    6. Saifulnazirah Bongsu & Wan Nur Mardhiah Nik Mohamed & Wan Nazihah Wan Mohamed, 2025. "Determinants of Students’ Intention to Use AI-Powered Writing Tools in Academic Writing," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(3s), pages 5616-5630, July.
    7. Marc Pinski & Thomas Hofmann & Alexander Benlian, 2024. "AI Literacy for the top management: An upper echelons perspective on corporate AI orientation and implementation ability," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-23, December.

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