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Development and Application of Convergence Education about Support Vector Machine for Elementary Learners

초등 학습자를 위한 서포트 벡터 머신 융합 교육 프로그램의 개발과 적용

  • Yuri Hwang ;
  • Namje Park (Department. of Computer Education, Teachers College, Jeju National University)
  • 황유리 (제주대학교 일반대학원 과학교육학부 컴퓨터교육전공, 대정초등학교) ;
  • 박남제 (제주대학교 교육대학 초등컴퓨터교육전공)
  • Received : 2023.05.14
  • Accepted : 2023.07.01
  • Published : 2023.07.31

Abstract

This paper proposes an artificial intelligence convergence education program for teaching the main concept and principle of Support Vector Machines(SVM) at elementary schools. The developed program, based on Jeju's natural environment theme, explains the decision boundary and margin of SVM by vertical and parallel from 4th grade mathematics curriculum. As a result of applying the developed program to 3rd and 5th graders, most students intuitively inferred the location of the decision boundary. The overall performance accuracy and rate of reasonable inference of 5th graders were higher. However, in the self-evaluation of understanding, the average value was higher in the 3rd grade, contrary to the actual understanding. This was due to the fact that junior learners had a greater tendency to feel satisfaction and achievement. On the other hand, senior learners presented more meaningful post-class questions based on their motivation for further exploration. We would like to find effective ways for artificial intelligence convergence education for elementary school students.

본 논문은 초등 학습자를 대상으로 서포트 벡터 머신의 개념과 원리를 교육하는 인공지능 융합 교육 프로그램을 제안한다. 개발된 프로그램은 초등 수학과 교육과정의 수직과 평행, 평행선 사이의 거리를 통해 서포트 벡터 머신의 결정 경계와 마진을 설명한다. 또한 제주의 자연환경을 학습 주제로 반영하여 사회과 교육과정과의 융합을 도모한다. 서포트 벡터 머신 융합 교육 프로그램을 초등학교 3학년 및 5학년 학습자를 대상으로 각각 2차시에 걸쳐 적용한 결과, 두 학년 모두에서 학습자 대부분이 탐방로로 비유된 결정 경계의 위치를 직관적으로 유추해냈다. 이때 5학년 학습자의 전반적인 활동 수행 정확도가 더욱 높았고, 설정 원리에 대해 합리적인 추론을 한 비율도 높았다. 4학년 수학 교육과정의 이수 여부도 이해도에 영향을 미쳤다. 그러나 학습 내용 이해도에 대한 자기평가에서는 실제 이해도와 상반되게 3학년에서 더 높은 평균값을 보였다. 이는 중학년 학습자는 생소한 인공지능 원리에 대해 새로 알게 되었다는 만족감과 성취감을 느끼는 경향성이 더 컸다는 점에서 기인하였다. 반면 고학년 학습자는 심화 탐구에 대한 동기를 기반으로 유의미한 수업 후 질문을 더 많이 제시하였다. 우리는 연구 결과를 바탕으로 초등학생을 대상으로 하는 인공지능 융합 교육이 나아가야 할 길을 모색하고자 한다.

Keywords

Acknowledgement

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2022S1A5C2A04092269), and, this work was supported by the Korea Foundation for the Advancement of Science and Creativity(KOFAC) grant funded by the Korea government(MOE).

References

  1. Ministry of Education, Korea (2021). Revised Curriculum General Guidelines Highlight.
  2. Shin, J. and Jo, M. (2021). Development and Implementation of an Activity-Based AI Convergence Education Program for Elementary School Students. Journal of The Korean Association of Information Education, 25(3), 437-448. https://doi.org/10.14352/jkaie.2021.25.3.437
  3. Kim, T. and Lee, Y. (2022). Analysis of Research Trends in Elementary Artificial Intelligence Education. 2022 Winter Proceeding of the Korean Association of Computer Education, 26(1), 285-287.
  4. Jang, Y. (2019). Development of Unplugged Education Program for Elementary School AI Classes. Seoul National University of Education.
  5. Kim, J. and Moon, S. (2021). Development of an AI Education Program based on Novel Engineering for Elementary School Students. The Journal of Korea Elementary Education, 32(1), 425-440.
  6. Jang, M. (2020). Unplugged Education Program for Artificial Intelligence Education in Elementary Schools : Focus on 'Constraint satisfaction problem. Gyeongin National University of Education.
  7. Choi, E. and Park, N. (2021). Application and Development of Machine Learning Training Program based on Understanding K-NN Algorithm. Journal of The Korean Association of Information Education, 25(1), 175-184 https://doi.org/10.14352/jkaie.2021.25.1.175
  8. Sim, S. (2021). A Study on the Development and Effectiveness of Python-based Artificial Intelligence Education Program in Elementary School : Focusing on Machine Learning. Daegu National University of Education.
  9. Ryu, M. and Han, S. (2019). AI Education Programs for Deep-Learning Concepts. Journal of The Korean Association of Information Education, 23(6), 583-590. https://doi.org/10.14352/jkaie.2019.23.6.583
  10. Park, D. and Shin, S. (2021). A Study on the Educational Meaning of eXplainable Artificial Intelligence for Elementary Artificial Intelligence Education. Journal of The Korean Association of Information Education, 25(5), 803-812. https://doi.org/10.14352/jkaie.2021.25.5.803
  11. Cheong, Y. and Lee, Y. (2022). A Case Study on the Convergence Education of Korean Studies Using Artificial Intelligence Contents. Journal of Learner-Centered Curriculum and Instruction, 22(5), 681-705. https://doi.org/10.22251/jlcci.2022.22.5.681
  12. Lee, S. and Kim, T. (2021). Development of Integration Program for Artificial Intelligence Education for Elementary School Student. 2021 Winter Proceeding of the Korean Association of Computer Education, 25(1), 245-248.
  13. Han, K. and Ahn, H. (2021). A Case Study of Artificial Intelligence Convergence Education using Entry in Elementary School. Journal of Creative Information Culture, 7(4), 197-206.
  14. Kim, H. and Choi, S. (2021). Development and Application of Artificial Intelligence STEAM Program for Real-time Interactive Online Class in Elementary Science - Focused on the Unit of 'Life of Plant' -. Journal of Korean Elementary Science Education, 40(4), 433-442.
  15. Yi, S. and Lee, Y. (2021). Development of Artificial Intelligence Education based Convergence Education Program for Classifying of Reptiles and Amphibians. Journal of Convergence for Information Technology, 11(12), 168-175.
  16. Shin, W. (2020). A Case Study on Application of Artificial Intelligence Convergence Education in Elementary Biological Classification Learning. Journal of Korean Elementary Science Education, 39(2), 284-295. https://doi.org/10.15267/KESES.2020.39.2.284
  17. Song, J. (2021). Development and Validation of Artificial Intelligence Educationon the Environmental Education Based on Unplugged. Journal of The Korean Association of Information Education, 25(5), 847-857. https://doi.org/10.14352/jkaie.2021.25.5.847
  18. Cho, H. (2021). Cultivation of Sustainability Literacy through Earth Citizenship Education Using Artificial Intelligence Technology. Seoul National University of Education.
  19. Yang, D. and Han, S. (2021). The Effect of A-STEAM Education Using Artificial Intelligence on Creativity of Elementary School Students. Korean Association of Artificial Intelligence Education Transactions, 2(3), 37-46. https://doi.org/10.52618/aied.2021.2.3.5
  20. Lee, Y. (2021). Development and effectiveness analysis of artificial intelligence STEAM education program. Journal of The Korean Association of Information Education, 25(1), 71-79. https://doi.org/10.14352/jkaie.2021.25.1.71
  21. Ministry of Education, Korea (2020). Comprehensive plan for information education[2020~2024].
  22. Kim, J. and Moon, S. (2021). Convergence Education Program Using Smart Farm for Artificial Intelligence Education of Elementary School Students. Journal of The Korea Convergence Society, 12(10), 203-210.
  23. Park, J. and Kim, S. (2022). Development and Application of Artificial Intelligence and Math Convergence Program in Specialized High School Classes - Focusing on the Equation of a Straight Line. 2022 Winter Proceeding of the Korean Association of Computer Education, 26(1), 289-292.
  24. Ministry of Education, Korea (2020). Teacher's guide book for Mathematics(Grade 4, 2nd Semester).