@article{ART003096254},
author={Eun Chul Lee and Young-Shin Pyun},
title={Development of checklist questions to measure AI capabilities of elementary school students},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2024},
volume={10},
number={3},
pages={7-12}
TY - JOUR
AU - Eun Chul Lee
AU - Young-Shin Pyun
TI - Development of checklist questions to measure AI capabilities of elementary school students
JO - Journal of Internet of Things and Convergence
PY - 2024
VL - 10
IS - 3
PB - The Korea Internet of Things Society
SP - 7
EP - 12
SN - 2466-0078
AB - The development of artificial intelligence technology changes the social structure and educational environment, and the importance of artificial intelligence capabilities continues to increase.
This study was conducted with the purpose of developing a checklist of questions to measure AI capabilities of elementary school students. To achieve the purpose of the study, a Delphi survey was used to analyze literature and develop questions. For literature analysis, two domestic studies, five international studies, and the Ministry of Education's curriculum report were collected through a search.
The collected data was analyzed to construct core competency measurement elements. The core competency measurement elements consisted of understanding artificial intelligence (6 elements), artificial intelligence thinking (4 elements), artificial intelligence ethics (4 elements), and artificial intelligence social-emotion (3 elements). Considering the knowledge, skills, and attitudes of the constructed measurement elements, 19 questions were developed. The developed questions were verified through the first Delphi survey, and 7 questions were revised according to the revision opinions.
The validity of 19 questions was verified through the second Delphi survey. The checklist items developed in this study are measured by teacher evaluation based on performance and behavioral observations rather than a self-report questionnaire. This has the implication that the measurement results of competency are raised to a reliable level.
KW - AI competency;AI core competency;AI competency measurement;AI checklist;AI core competency of elementary school student
DO -
UR -
ER -
Eun Chul Lee and Young-Shin Pyun. (2024). Development of checklist questions to measure AI capabilities of elementary school students. Journal of Internet of Things and Convergence, 10(3), 7-12.
Eun Chul Lee and Young-Shin Pyun. 2024, "Development of checklist questions to measure AI capabilities of elementary school students", Journal of Internet of Things and Convergence, vol.10, no.3 pp.7-12.
Eun Chul Lee, Young-Shin Pyun "Development of checklist questions to measure AI capabilities of elementary school students" Journal of Internet of Things and Convergence 10.3 pp.7-12 (2024) : 7.
Eun Chul Lee, Young-Shin Pyun. Development of checklist questions to measure AI capabilities of elementary school students. 2024; 10(3), 7-12.
Eun Chul Lee and Young-Shin Pyun. "Development of checklist questions to measure AI capabilities of elementary school students" Journal of Internet of Things and Convergence 10, no.3 (2024) : 7-12.
Eun Chul Lee; Young-Shin Pyun. Development of checklist questions to measure AI capabilities of elementary school students. Journal of Internet of Things and Convergence, 10(3), 7-12.
Eun Chul Lee; Young-Shin Pyun. Development of checklist questions to measure AI capabilities of elementary school students. Journal of Internet of Things and Convergence. 2024; 10(3) 7-12.
Eun Chul Lee, Young-Shin Pyun. Development of checklist questions to measure AI capabilities of elementary school students. 2024; 10(3), 7-12.
Eun Chul Lee and Young-Shin Pyun. "Development of checklist questions to measure AI capabilities of elementary school students" Journal of Internet of Things and Convergence 10, no.3 (2024) : 7-12.
