Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Analyzing Teacher Competency with TPACK for K-12 AI Education

Authors
Kim, SeonghunJang, YeonjuChoi, SeongyuneKim, WoojinJung, HeeseokKim, SoohwanKim, Hyeoncheol
Issue Date
2021
Publisher
SPRINGER HEIDELBERG
Keywords
AI education; K-12; Curriculum; South Korea; Teacher competency; TPACK
Citation
KUNSTLICHE INTELLIGENZ, v.35, no.2, pp.139 - 151
Indexed
SCOPUS
Journal Title
KUNSTLICHE INTELLIGENZ
Volume
35
Number
2
Start Page
139
End Page
151
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/130238
DOI
10.1007/s13218-021-00731-9
ISSN
0933-1875
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.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Computer Science and Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Hyeon cheol photo

Kim, Hyeon cheol
컴퓨터학과
Read more

Altmetrics

Total Views & Downloads

BROWSE