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Development of an artificial intelligence curriculum design for children in Taiwan and its impact on learning outcomes

Author

Listed:
  • Hong-Guang Zhao

    (Tianjin University of Technology)

  • Xin-Zhu Li

    (China University of Mining and Technology)

  • Xin Kang

    (NingboTech University)

Abstract

In the digital age, the application of Artificial Intelligence (AI) has become an irreversible trend, with its potential in the field of education being particularly noteworthy. However, there are currently few AI education programs for children in Taiwan, and there is a lack of systematic teaching resources and methods, which poses a major challenge to the promotion of AI education. To address this challenge, this study designed a tailor-made AI curriculum for children in Taiwan, aimed at enhancing their foundational knowledge in the AI field and skills in using generative AI. This study was conducted in Taiwan, involving 30 elementary school students from grades 3 and 4, employing a single-group pre-test and post-test research design. Data were collected and analyzed through pre-and post-tests on AI knowledge quizzes and AI knowledge self-assessment, as well as the expert consensual assessment technique and the pupils’ attitude toward technology survey questionnaire. Research shows that students who participated in the AI course significantly improved their test scores on AI knowledge before and after the course. The students AI knowledge increased by 62.75%, demonstrating the course’s effectiveness and showing a positive attitude towards AI technology. Additionally, the student’s project outcomes demonstrated a high level of creativity. The students exhibited an enhanced interest and positive attitude towards learning AI, expressing a willingness to participate in more AI educational courses. This work provides valuable experience and guidance for the future integration of AI technology in children’s education, offering practical guidelines for teachers and researchers on how to effectively teach AI knowledge, as well as serving as a robust reference for educational policy makers in formulating strategies to promote AI education.

Suggested Citation

  • Hong-Guang Zhao & Xin-Zhu Li & Xin Kang, 2024. "Development of an artificial intelligence curriculum design for children in Taiwan and its impact on learning outcomes," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-17, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03839-z
    DOI: 10.1057/s41599-024-03839-z
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    References listed on IDEAS

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    1. Woong Suh & Seongjin Ahn, 2022. "Development and Validation of a Scale Measuring Student Attitudes Toward Artificial Intelligence," SAGE Open, , vol. 12(2), pages 21582440221, May.
    2. Jaekyu Lee & Yeichang Kim, 2023. "Sustainable Educational Metaverse Content and System Based on Deep Learning for Enhancing Learner Immersion," Sustainability, MDPI, vol. 15(16), pages 1-17, August.
    3. Xin-Zhu Li & Chun-Ching Chen & Xin Kang, 2023. "Religious diversity education: raising children’s awareness of religious diversity through augmented reality," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    4. Jussi S. Jauhiainen & Agustín Garagorry Guerra, 2023. "Generative AI and ChatGPT in School Children’s Education: Evidence from a School Lesson," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    5. Manjul Gupta & Carlos M. Parra & Denis Dennehy, 2022. "Questioning Racial and Gender Bias in AI-based Recommendations: Do Espoused National Cultural Values Matter?," Information Systems Frontiers, Springer, vol. 24(5), pages 1465-1481, October.
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