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The Educational Perception on Artificial Intelligence by Elementary School Teachers

초등 교사들의 인공지능에 관한 교육적 인식

  • Ryu, Miyoung (Dept. of Computer Education, Gyeong-in National University of Education) ;
  • Han, SeonKwan (Dept. of Computer Education, Gyeong-in National University of Education)
  • 류미영 (경인교육대학교 컴퓨터교육과) ;
  • 한선관 (경인교육대학교 컴퓨터교육과)
  • Received : 2018.04.26
  • Accepted : 2018.06.19
  • Published : 2018.06.30

Abstract

This study analyzes elementary school teachers' perception of Artificial Intelligence, educational effect, and necessity in education. To analyze teachers' perceptions, we developed questionnaires with expert advice. We collected questionnaires for 151 elementary school teachers. The collected data were analyzed by t-test and one-way ANOVA. As a result, AI' perceptions of female teachers were lower than those of male teachers and the necessity of education was less. Teachers with experience in leading schools recognized that AI education would help to improve creativity. Teachers who have a lot of teaching experience, many experience in SW education, the experience in SW education have a high interest in AI and understand the relevance of the subject. We expect that this study will help the direction of SW education.

본 연구는 인공지능의 이해와 교육적 영향에 대한 초등 교사들의 인식을 분석한 것이다. 교사들의 인식을 분석하기 위해 전문가의 자문을 받아 30문항의 설문지를 개발하였다. 초등 교사 151명을 대상으로 설문 자료를 수집하여 t-검정과 일원배치 분산분석을 실시하였다. 분석결과, 여자교사가 남자교사보다 AI의 인식이 적었고 교육의 필요성도 낮았다. 선도학교 운영 여부에 따라 AI교육이 창의성 신장에 도움을 줄 것으로 인식하였다. 경력이 많은 교사일수록, SW교육 연수 경험과 교육 지도 경험이 많을수록 AI의 이해가 좋았으며 교육적 필요성이 높았다. 본 연구 자료가 향후 SW 교육이 현장에 안착하기 위한 자료가 되길 기대한다.

Keywords

References

  1. Information & Telecommunication Technology Promotion Center(2016), Information and Communication Industry Promotion Center (2016), Survey on Awareness and Response Strategy of Artificial Intelligence, KOSEN-Trend Report, www.kosen21.org
  2. J. H. Park, N. M. Shin(2017), Students' perceptions of Artificial Intelligence Technology and Artificial Intelligence Teachers, The Journal of Korean Teacher Education, 34(2),169-192
  3. K. Schwab(2016), The Fourth Industrial Revolution. Colony/Geneva: World Economic Forum.
  4. M. Y. Ryu, S. K. Han(2016), Analysis of Software Image using Semantic Differential Scale in Elementary School Students, Journal of The Korean Association of Information Education, 20(5), 527-534 https://doi.org/10.14352/jkaie.20.4.527
  5. M. Y. Ryu, S. K. Han(2016), The Structural Equation Modeling of Factors Affecting the Parent Willingness on Child's Software Education, Journal of The Korean Association of Information Education, 20(5), 443-450 https://doi.org/10.14352/jkaie.20.4.443
  6. M. Y. Ryu, S. K. Han(2017), Image of Artificial Intelligence of Elementary Students by using Semantic Differential Scale, Journal of The Korean Association of Information Education, 21(5), 1-9 https://doi.org/10.14352/jkaie.21.1.1
  7. National Science and Technology Council Committee on Technology(2016), Preparing for the Future of Artificial Intelligence, Report for Executive Office of the President of the USA, 1-58.
  8. Research Area of Artificial Intelligence https://blogs.thomsonreuters.com/answerson/artificial-intelligence
  9. S. G. Han, S. H. Kim(2015), Analysis on the Parents Aware of the Need for the Elementary SW Education, Journal of The Korean Association of Information Education, 19(2), 187-196 https://doi.org/10.14352/jkaie.2015.19.2.187
  10. S. H. Kim, S. K. Han(2014), A Perception on SW Education of Students with Scratch-Day, Journal of The Korean Association of Information Education, 18(4), 461-470 https://doi.org/10.14352/jkaie.2014.18.4.461
  11. S. I. Shin, M. S. Ha, J. K. Jun(2017), High School Students' Perception of Artificial Intelligence: Focusing on Conceptual Understanding, Emotion and Risk Perception, Journal of Learner-Centered Curriculum and Instruction, 17(21), 289-312.
  12. S. J. Russell, P. Norvig(2016), Artificial Intelligence : A Modern Approach, Prentice Hall Publisher, Newyork

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