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Cited by 96Teaching and Learning ProgrammingEducational Theory and Curriculum StudiesScience Education and Pedagogy

Collaborative construction of artificial intelligence curriculum in primary schools

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Dai, Yun, Liu, Ang, Qin, Jianjun, Guo, Yanmei, Jong, Morris Siu‐Yung, Chai, Ching‐Sing, Lin, Ziyan·2023·Journal of Engineering Education
DOI 10.1002/jee.20503
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Abstract

Abstract Background The recent discussion of introducing artificial intelligence (AI) knowledge to K–12 students, like many engineering and technology education topics, has attracted a wide range of stakeholders and resources for school curriculum development. While teachers often have to directly interact with external stakeholders out of the public schooling system, few studies have scrutinized their negotiation process, especially teachers' responses to external influences, in such complex environments. Purpose Guided by an integrated theoretical framework of social constructionism, this research examined the process of how a teacher‐initiated AI curriculum was constructed with external influences. The research focused on teachers' perspectives and responses in mediating external influences into local schools and classrooms. Methods A 3‐year ethnographic study was conducted in relation to an AI curriculum project among 23 Computer Science (CS) teachers from primary schools. Data collected from ethnographic observation, teacher interviews, and artifacts, were analyzed using open coding and triangulation rooted in the ethnographic, interpretivist approach. Results Three sets of external influences were found salient for teachers' curriculum decisions, including the orientation of state‐level educational policies, AI faculty at a partner university, and students' media and technology environments. The teachers' situational logics and strategic actions were reconstructed with thick descriptions to uncover how they navigated and negotiated the external influences to fulfill local challenges and expectations in classrooms and schools. Conclusions The ethnographic study uncovered the dynamic and multifaceted negotiation involved in the collaborative curriculum development, and offers insights to inform policymaking, teacher education, and student support in engineering education.

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  • Curriculum development-oriented studies focus primarily on students' AI literacy, rather than specifying the knowledge required by teachers and educators.

    “Curriculum development-oriented studies (1) focus primarily on stu dents ' AI literacy, rather than specifying the knowledge required by teachers and educators [69,71].”

    From In search of artificial intelligence (AI) literacy in teacher education: A scoping review (2024) · cites this paper as [71]

  • In the majority of papers covering teachers' professional development and curriculum development, teachers' epistemic knowledge is reflected in implicit terms, often briefly referring back to existing curricula or frameworks that are not further explained.

    “In the majority of the papers covering teachers ' pro fessional development (e.g., [86,87,89]) and curriculum development [70 -72,90,91], teachers ' epistemic knowledge is reflected in much more implicit terms, often briefly referring back to existing curricula or frameworks that are not further explained.”

    From In search of artificial intelligence (AI) literacy in teacher education: A scoping review (2024) · cites this paper as [71]

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Research works printed but not linked: 8

  1. Anderson-Levitt, K. M. (2006). Ethnography. In J. L. Green, G. Camilli, & P. B. Moore (Eds.), Handbook of complementary methods in educa- tional research (pp. 279-296).
  2. Berger, P., & Luckmann, T. (2016). The social construction of reality. In W. Longhofer & D. Winchester (Eds.), Social theory re-wired (pp. 110-122). Routledge.
  3. Chval, K. B., Weiss, I. R., & Taylan, R. D. (2014). Recommendations for generating and implementing a research agenda for studying the enacted mathematics curriculum. In D. R. Thompson & Z. Usiskin (Eds.), Enacted mathematics curriculum: Conceptual framework and research needs (pp. 114-134). Information Age Publishing.
  4. Goulding, C. (1999). Grounded theory: Some reflections on paradigm, procedures and misconceptions (Working paper series, June 1999, WP006/99). http://hdl.handle.net/2436/11403
  5. Green, J. L., Skukauskaite, A., & Baker, W. D. (2012). Ethnography as epistemology. In R. Coe, M. Waring, L. V. Hedges & L. D. Ashley (Eds.), Research Methods and Methodologies in Education, (pp. 309-321). Sage.
  6. Lindner, A., & Romeike, R. (2019). Teachers' perspectives on artificial intelligence. Paper presented at the12th International Conference on Informatics in Schools, "Situation, Evaluation and Perspectives", Larnaca, Cyprus. https://cyprusconferences.org/issep2019/wp-content/ uploads/2019/11/2019_Book_1.pdf
  7. Posner, G. J. (2004). Analyzing the curriculum (3rd ed.). McGraw-Hill.
  8. Morris Siu-Yung Jong is an Associate Professor of Curriculum and Instruction at the Chinese University of Hong Kong, New Territories, Hong Kong SAR, China; mjong@cuhk.edu.hk. Ching-Sing Chai is a Professor of Curriculum and Instruction at the Chinese University of Hong Kong, New Territories, Hong Kong SAR, China; cschai@cuhk.edu.hk. Ziyan Lin is a Research Assistant of Curriculum and Instruction at the Chinese University of Hong Kong, New Ter- ritories, Hong Kong SAR, China; ziyanlin@cuhk.edu.hk. How to cite this article: Dai, Y., Liu, A., Qin, J., Guo, Y., Jong, M. S.-Y., Chai, C.-S., & Lin, Z. (2023). Collaborative construction of artificial intelligence curriculum in primary schools. Journal of Engineering Education, 112(1), 23-42. https://doi.org/10.1002/jee.20503

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Authors
Dai, Y., Liu, A., Qin, J., Guo, Y., Jong, M. S., Chai, C., & Lin, Z.
Affiliations
  • Chinese University of Hong Kong (HK)
  • UNSW Sydney (AU)
  • Beijing University of Civil Engineering and Architecture (CN)
  • Teacher Training and Development Centre of Dongcheng District Beijing China
Corresponding author
Dai, Yun
ORCID
Venue
Journal of Engineering Education
Publisher
Wiley
Published
2022-12-30
Volume
112
Issue
1
Pages
23-42
ISSN
  • 1069-4730 (ISSN-L)
  • 2168-9830
DOI
10.1002/jee.20503
OpenAlex
W4313357303
Cited by
96
References
80
Citations by year
2026: 26 · 2025: 34 · 2024: 27 · 2023: 9
FWCI
13.51
Type
journal article
Language
en
Open access
Licence
Locations
Journal of Engineering Education (publishedVersion, cc-by)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
  • Social Sciences › Sociology and Political Science › Educational Theory and Curriculum Studies
  • Social Sciences › Education › Science Education and Pedagogy
Keywords
artificial intelligence in education, curriculum development, primary school teachers, social constructionism, state educational policy, university-industry collaboration, situational logic, strategic action, K-12 computer science education, teacher professional development

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