Collaborative construction of artificial intelligence curriculum in primary schools

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 w...

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Published inJournal of engineering education (Washington, D.C.) Vol. 112; no. 1; pp. 23 - 42
Main Authors Dai, Yun, Liu, Ang, Qin, Jianjun, Guo, Yanmei, Jong, Morris Siu‐Yung, Chai, Ching‐Sing, Lin, Ziyan
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 01.01.2023
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Blackwell Publishing Ltd
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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.
AbstractList 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.
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.
BackgroundThe 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.PurposeGuided 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.MethodsA 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.ResultsThree 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.ConclusionsThe 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.
Audience Elementary Education
Author Lin, Ziyan
Qin, Jianjun
Chai, Ching‐Sing
Liu, Ang
Dai, Yun
Jong, Morris Siu‐Yung
Guo, Yanmei
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Snippet Background The recent discussion of introducing artificial intelligence (AI) knowledge to K–12 students, like many engineering and technology education topics,...
Background: The recent discussion of introducing artificial intelligence (AI) knowledge to K-12 students, like many engineering and technology education...
BackgroundThe recent discussion of introducing artificial intelligence (AI) knowledge to K–12 students, like many engineering and technology education topics,...
SourceID proquest
eric
crossref
wiley
SourceType Aggregation Database
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Enrichment Source
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StartPage 23
SubjectTerms Artificial Intelligence
Classrooms
Coding
Collaboration
Colleges & universities
Computer Science Education
Constructivism (Learning)
Cooperation
Core curriculum
Curricula
Curriculum Development
Education
Educational Policy
Elementary Education
Elementary School Teachers
Elementary Schools
Engineering education
Ethnography
Negotiations
primary school
Schools
Stakeholders
Students
teacher agency
Teacher Improvement
Teachers
Teaching Methods
Technology Education
Triangulation
Title Collaborative construction of artificial intelligence curriculum in primary schools
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fjee.20503
http://eric.ed.gov/ERICWebPortal/detail?accno=EJ1363508
https://www.proquest.com/docview/2769218902
Volume 112
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