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Pedagogical Design of K-12 Artificial Intelligence Education: A Systematic Review

Author

Listed:
  • Miao Yue

    (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)

  • Yun Dai

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

Abstract

In response to the growing popularity of artificial intelligence (AI) usage in daily life, AI education is increasingly being provided at the K-12 level, with relevant initiatives being launched worldwide. Examining how these programs have been implemented and summarizing useful experiences is thus imperative. Although prior reviews have described the characteristics of AI education programs in publications, the papers reviewed were mostly nonempirical reports, and the analysis typically only involved a descriptive summary. The current review focuses on the most recent empirical studies on AI teaching programs in K-12 contexts through a systematic search of the Web of Science database from 2010 to 2022. To provide a comprehensive overview of the status of AI teaching and learning (T&L), 32 empirical studies were analyzed both descriptively and thematically. We analyzed (1) the research status, (2) the pedagogical design, and (3) the assessments and outcomes of the AI teaching programs. An increasing number of studies have focused on AI education at the K-12 stage, but most of them have a small sample size. Moreover, the data were mostly collected through interviews and self-reports. We reviewed the pedagogical design of AI teaching programs by using Gerlach and Ely’s pedagogical design model. The results comprehensively delineated current AI teaching programs through nine dimensions: learning theory, pedagogical approach, T&L activities, learning content, scale, teaching resources, prior knowledge prerequisite, aims and objectives, assessment, and learning outcome. The results highlighted the positive impact of current AI teaching programs on students’ motivation, engagement, and attitude. However, we observed a lack of sufficient research objectively measuring students’ knowledge acquisition as learning outcomes. Overall, in this paper, we discussed relevant findings in terms of research trends, learning content, teaching units, characteristics of the pedagogical design, and assessment and evaluation by providing illustrations of exemplary designs; we also discussed future directions for research and practice in AI education in the K-12 context.

Suggested Citation

  • Miao Yue & Morris Siu-Yung Jong & Yun Dai, 2022. "Pedagogical Design of K-12 Artificial Intelligence Education: A Systematic Review," Sustainability, MDPI, vol. 14(23), pages 1-29, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15620-:d:982706
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    References listed on IDEAS

    as
    1. Xin Li & Michael Yi-chao Jiang & Morris Siu-yung Jong & Xinping Zhang & Ching-sing Chai, 2022. "Understanding Medical Students’ Perceptions of and Behavioral Intentions toward Learning Artificial Intelligence: A Survey Study," IJERPH, MDPI, vol. 19(14), pages 1-17, July.
    2. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    3. Morris Siu-Yung Jong & Jie Geng & Ching Sing Chai & Pei-Yi Lin, 2020. "Development and Predictive Validity of the Computational Thinking Disposition Questionnaire," Sustainability, MDPI, vol. 12(11), pages 1-17, May.
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    1. Pantelimon Florin-Valeriu & Posedaru Bogdan-Stefan & Toader Liviu-Andrei & Dulgheru Mihai-Nicolae & Georgescu Tiberiu-Marian, 2024. "The Dynamics of the ICT Workforce and the Effects on the Use of Artificial Intelligence Technologies in the European Union," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 18(1), pages 3490-3502.

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