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Teachers’ Perceptions of Teaching Sustainable Artificial Intelligence: A Design Frame Perspective

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  • Xiao-Fan Lin

    (Guangdong Provincial Engineering and Technologies Research Centre for Smart Learning, Guangdong Provincial Institute of Elementary Education and Information Technology, Guangzhou 510631, China
    School of Education Information Technology, South China Normal University, Guangzhou 510631, China
    Guangdong Provincial Philosophy and Social Sciences Key Laboratory of Artificial Intelligence and Smart Education, Guangzhou 510631, China
    Institute for Artificial Intelligence Education, South China Normal University, Guangzhou 510631, China)

  • Lu Chen

    (School of Education Information Technology, South China Normal University, Guangzhou 510631, China)

  • Kan Kan Chan

    (Faculty of Education, University of Macau, Macau, China)

  • Shiqing Peng

    (School of Education Information Technology, South China Normal University, Guangzhou 510631, China)

  • Xifan Chen

    (School of Education Information Technology, South China Normal University, Guangzhou 510631, China)

  • Siqi Xie

    (School of Education Information Technology, South China Normal University, Guangzhou 510631, China
    Guangdong Provincial Philosophy and Social Sciences Key Laboratory of Artificial Intelligence and Smart Education, Guangzhou 510631, China)

  • Jiachun Liu

    (School of Education Information Technology, South China Normal University, Guangzhou 510631, China
    Institute for Artificial Intelligence Education, South China Normal University, Guangzhou 510631, China)

  • Qintai Hu

    (New Engineering Education Research Center, Guangdong University of Technology, Guangzhou 510090, China)

Abstract

Teaching artificial intelligence (AI) is an emerging challenge in global school education. There are considerable barriers to overcome, including the existing practices of technology education and teachers’ knowledge of AI. Research evidence shows that studying teachers’ experiences can be beneficial in informing how appropriate design in teaching sustainable AI should evolve. Design frames characterize teachers’ design reasoning and can substantially influence their AI lesson design considerations. This study examined 18 experienced teachers’ perceptions of teaching AI and identified effective designs to support AI instruction. Data collection methods involved semi-structured interviews, action study, classroom observation, and post-lesson discussions with the purpose of analyzing the teachers’ perceptions of teaching AI. Grounded theory was employed to detail how teachers understand the pedagogical challenges of teaching AI and the emerging pedagogical solutions from their perspectives. Results reveal that effective AI instructional design should encompass five important components: (1) obstacles to and facilitators of participation in teaching AI, (2) interactive design thinking processes, (3) teachers’ knowledge of teaching AI, (4) orienteering AI knowledge for social good, and (5) the holistic understanding of teaching AI. The implications for future teacher AI professional development activities are proposed.

Suggested Citation

  • Xiao-Fan Lin & Lu Chen & Kan Kan Chan & Shiqing Peng & Xifan Chen & Siqi Xie & Jiachun Liu & Qintai Hu, 2022. "Teachers’ Perceptions of Teaching Sustainable Artificial Intelligence: A Design Frame Perspective," Sustainability, MDPI, vol. 14(13), pages 1-20, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7811-:d:848770
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    References listed on IDEAS

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    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. 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.
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