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Is It Possible for Young Students to Learn the AI-STEAM Application with Experiential Learning?

Author

Listed:
  • Ting-Chia Hsu

    (Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taipei City 10610, Taiwan)

  • Hal Abelson

    (Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA)

  • Natalie Lao

    (Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA)

  • Shih-Chu Chen

    (Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taipei City 10610, Taiwan
    Institute of Service Science, National Tsing Hua University, Hsinchu City 30013, Taiwan)

Abstract

This study attempted to evaluate the learning effectiveness of using the MIT App Inventor platform and its Personal Image Classifier (PIC) tool in the interdisciplinary application. The instructional design was focused on applying PIC in the integration of STEAM (i.e., Science, Technology, Engineering, Art, and Mathematics) interdisciplinary learning, so as to provide sustainable and suitable teaching content based on the experiential learning theory for 7th grader students. Accordingly, the sustainable AI-STEAM course with the experiential learning framework has been implemented and verified, so as to confirm that the AI-STEAM course is not too difficult for young students. Many basic concepts involved in the AI-STEAM course, regarding programming logic, electromechanical concepts, interface design, and the application of image recognition, were measured in this study. The results showed that the students not only made significant progress in learning effectiveness, but also in particular made significant improvements in two parts: electromechanical concepts and image recognition knowledge. In the end, this study further provides some advice on the sustainable AI-STEAM course based on the survey of some important factors including active learning, and self-efficacy after confirming that it is not a barrier for the young students to learn the sustainable AI-STEAM course developed in this study.

Suggested Citation

  • Ting-Chia Hsu & Hal Abelson & Natalie Lao & Shih-Chu Chen, 2021. "Is It Possible for Young Students to Learn the AI-STEAM Application with Experiential Learning?," Sustainability, MDPI, vol. 13(19), pages 1-15, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:11114-:d:651756
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    References listed on IDEAS

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    1. Xaro Benavent & Esther de Ves & Anabel Forte & Carmen Botella-Mascarell & Emilia López-Iñesta & Silvia Rueda & Sandra Roger & Joaquin Perez & Cristina Portalés & Esther Dura & Daniel Garcia-Costa & Pa, 2020. "Girls4STEM: Gender Diversity in STEM for a Sustainable Future," Sustainability, MDPI, vol. 12(15), pages 1-17, July.
    2. Peng-Wei Hsiao & Chung-Ho Su, 2021. "A Study on the Impact of STEAM Education for Sustainable Development Courses and Its Effects on Student Motivation and Learning," Sustainability, MDPI, vol. 13(7), pages 1-24, March.
    3. Francisco Ruiz Vicente & Alberto Zapatera Llinares & Nicolás Montés Sánchez, 2020. "“Sustainable City”: A Steam Project Using Robotics to Bring the City of the Future to Primary Education Students," Sustainability, MDPI, vol. 12(22), pages 1-21, November.
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    Cited by:

    1. Ting-Chia Hsu & Ching Chang & Lung-Hsiang Wong & Guat Poh Aw, 2022. "Learning Performance of Different Genders’ Computational Thinking," Sustainability, MDPI, vol. 14(24), pages 1-16, December.

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