- Volume 23 Issue 2
DOI QR Code
An Analysis of the Influence of Block-type Programming Language-Based Artificial Intelligence Education on the Learner's Attitude in Artificial Intelligence
블록형 프로그래밍 언어 기반 인공지능 교육이 학습자의 인공지능 기술 태도에 미치는 영향 분석
- Lee, Youngho (Seoul Youngdo Elementary School)
- 이영호 (서울영도초등학교)
- Received : 2019.04.25
- Accepted : 2019.04.28
- Published : 2019.04.30
Artificial intelligence has begun to be used in various parts of our lives, and recently its sphere has been expanding. However, students tend to find it difficult to recognize artificial intelligence technology because education on artificial intelligence is not being conducted on elementary school students. This paper examined the teaching programming language and artificial intelligence teaching methods, and looked at the changes in students' attitudes toward artificial intelligence technology by conducting education on artificial intelligence. To this end, education on block-type programming language-based artificial intelligence technology was provided to students' level. And we looked at students' attitudes toward artificial intelligence technology through a single group pre-postmortem. As a result, it brought about significant improvements in interest in artificial intelligence, possible access to artificial intelligence technology and the need for education on artificial intelligence technology in schools.
- Amazon Web Services (AWS) - Cloud Computing Services (2018). Retrieved from https://aws.amazon.com
- An Sungman. (2016). Model of Deep Learning and Application Examples. Intelligent Information Research, 22(2), 127-142.
- Becker, K. H., &Maunsaiyat, S. (2002). Thai Students' Attitudes and Concepts of Technology. Journal of Technology education, 13(2), 6-20.
- Chen, Y., Argentinis, J. E., & Weber, G. (2016). IBM Watson: how cognitive computing can be applied to big data challenges in life sciences research. Clinical therapeutics, 38(4), 688-701. https://doi.org/10.1016/j.clinthera.2015.12.001
- Chollet, F. (2017). Deep learning with python. Manning Publications Co..
- Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2011). How to design and evaluate research in education. New York: McGraw-Hill Humanities/Social Sciences/Languages.
- IBM Cloud - Next-Generation Cloud App Development Platform. (2018). Retrieved from https://console.bluemix.net/
- Kum Yeongchung, & Bae Seona. (2012). The Effects of Elementary Technology Based STEAM Education on Elementary School Students' Attitudes Toward Technology. Korean Journal of Practical Arts Education, 25(3), 195-216.
- Lee Chunsik, & Lee Yonghwan. (1999). Attitudes toward technology and related variables of middle school students. Vocational Education Research, 18(1), 59-73.
- Lee Chunsik. (2008). Developing students' attitudes toward technology. Studies in Practical Arts Education, 14(2), 157-174.
- Lee Youngho, & Koo Dukhoi. (2017). Development of Deep Learning - based Learning System for Improving Data Analytical Thinking Ability. Journal of The Korea Information Society Society, 21(4), 393-401.
- Lee Youngho. (2018). Development of intelligent problem solving path prediction model for customized programming education. Graduate School of Education, Seoul National University of Education. Doctoral thesis.
- Machine Learning for Kids (2018). Retrieved from https://machinelearningforkids.co.uk
- National Korean Language Institute (2019) Standard Korean Language Dictionary, Retrieved from http://stdweb2.korean.go.kr/search/List_dic.jsp.
- Nunnally, J. (1978). Psychometric methods.
- Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215
- Won Donggyu, & Lee Sangpil. (2016). Implications of Artificial Intelligence and the Fourth Industrial Revolution. ie Magazine, 23(2), 13-22.