Analyzing Teacher Competency with TPACK for K-12 AI Education

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

Research output: Contribution to journalArticlepeer-review

2 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 languageEnglish
Pages (from-to)139-151
Number of pages13
JournalKI - Kunstliche Intelligenz
Volume35
Issue number2
DOIs
Publication statusPublished - 2021 Jun

Keywords

  • AI education
  • Curriculum
  • K-12
  • South Korea
  • TPACK
  • Teacher competency

ASJC Scopus subject areas

  • Artificial Intelligence

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