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dc.contributor.authorKim, Seonghun
dc.contributor.authorJang, Yeonju
dc.contributor.authorChoi, Seongyune
dc.contributor.authorKim, Woojin
dc.contributor.authorJung, Heeseok
dc.contributor.authorKim, Soohwan
dc.contributor.authorKim, Hyeoncheol
dc.date2021-06-01
dc.date.accessioned2021-10-04T12:29:01Z
dc.date.available2021-10-04T12:29:01Z
dc.date.issued2021
dc.identifier.issn1610-1987
dc.identifier.urihttp://dx.doi.org/10.1007/s13218-021-00731-9
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/37484
dc.description.abstractAs the need for teaching Artificial Intelligence (AI) for K-12 is increasing, discussions on what competencies teacher should have for effective teaching of AI is overlooked. In this work, we determine what teacher competencies are necessary for improving the teaching and learning of AI for K-12 with Technological Pedagogical Content Knowledge (TPACK) framework. First, we identify current AI education resources and investigate the core foundations of AI taught to K-12. Based on the findings, we propose teacher competency for K-12 AI education by analyzing AI curricula and resources using the TPACK framework. We conclude that teachers who teach AI to K-12 students require TPACK to construct, prepare an environment, and facilitate project-based classes that solve problems using AI technologies.de
dc.publisherSpringer
dc.relation.ispartofKI - Künstliche Intelligenz: Vol. 35, No. 2
dc.relation.ispartofseriesKI - Künstliche Intelligenz
dc.subjectAI education
dc.subjectCurriculum
dc.subjectK-12
dc.subjectSouth Korea
dc.subjectTeacher competency
dc.subjectTPACK
dc.titleAnalyzing Teacher Competency with TPACK for K-12 AI Educationde
dc.typeText/Journal Article
mci.reference.pages139-151
dc.identifier.doi10.1007/s13218-021-00731-9


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