Analyzing Teacher Competency with TPACK for K-12 AI Education

Seonghun Kim; Yeonju Jang; Seongyune Choi; Woojin Kim; Heeseok Jung; Soohwan Kim; Hyeoncheol Kim

doi:10.1007/s13218-021-00731-9

Analyzing Teacher Competency with TPACK for K-12 AI Education

Seonghun Kim^*
, Yeonju Jang
, Seongyune Choi
, Woojin Kim
, Heeseok Jung
, Soohwan Kim
, Hyeoncheol Kim^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

92 Citations (Scopus)

Abstract

As 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.

Original language	English
Pages (from-to)	139-151
Number of pages	13
Journal	KI - Kunstliche Intelligenz
Volume	35
Issue number	2
DOIs	https://doi.org/10.1007/s13218-021-00731-9
Publication status	Published - 2021 Jun

Bibliographical note

Publisher Copyright:
© 2021, Gesellschaft für Informatik e.V. and Springer-Verlag GmbH Germany, part of Springer Nature.

Keywords

AI education
Curriculum
K-12
South Korea
TPACK
Teacher competency

ASJC Scopus subject areas

Artificial Intelligence

Access to Document

10.1007/s13218-021-00731-9

Cite this

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title = "Analyzing Teacher Competency with TPACK for K-12 AI Education",

abstract = "As 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.",

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note = "Publisher Copyright: {\textcopyright} 2021, Gesellschaft f{\"u}r Informatik e.V. and Springer-Verlag GmbH Germany, part of Springer Nature.",

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doi = "10.1007/s13218-021-00731-9",

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AU - Kim, Seonghun

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AU - Choi, Seongyune

AU - Kim, Woojin

AU - Jung, Heeseok

AU - Kim, Soohwan

AU - Kim, Hyeoncheol

PY - 2021/6

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N2 - As 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.

AB - As 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.

KW - AI education

KW - Curriculum

KW - K-12

KW - South Korea

KW - TPACK

KW - Teacher competency

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Analyzing Teacher Competency with TPACK for K-12 AI Education

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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