The Journal of Society for e-Business Studies (한국전자거래학회지)

Society for e-Business Studies (한국전자거래학회)
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Research of Computational Thinking based on Analyzed in Each Major Learner

계열별 학습자 분석 기반의 컴퓨팅사고력 연구

  • Kwon, Jungin (College of kyedang General Education, Sangmyung University)
  • Received : 2019.07.29
  • Accepted : 2019.10.21
  • Published : 2019.11.30
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Abstract

The rapid development of a software-core society emphasizes the importance of software competence as a basic condition for all academic disciplines. The purpose of this study is to investigate the difference of perceptions among students of basic software education which is currently being conducted in university. The results of applying the nine core elements of Computational Thinking for Problem Solving to the learners of the each majors are as follows. In humanities, learners mainly applied the elements of Data Collection, Problem Decomposition and Automation. On the other hand, natural science department learners mainly applied the elements of Data Analysis, Algorithm and Automation. In addition, arts learners mainly applied elements of Data Representation, Abstraction, and Automation. To apply Computational Thinking to the development of software, humanities learners mainly applied elements of Data Collection, Algorithm, Automation. On the other hand, natural science department learners mainly applied the elements of Data Analysis, Algorithm and Automation. In addition, arts learners mainly applied elements of Data Representation, Abstraction, and Automation. Based on the results of this study, it is expected that the educational effectiveness of the learner will be maximized by including the learner analysis with each majors in the design of the basic software curriculum that each university is conducting.

소프트중심의 급속한 사회변화로 인해 모든 학문분야 인재상의 기본 조건으로 소프트웨어 역량의 중요성이 강조되고 있다. 본 연구는 현재 대학에서 신입생을 대상으로 실시되고 있는 기초소프트웨어교육의 계열별 학습자들의 소프트웨어교육 인식 차이를 조사하고자 한다. 연구결과 문제해결을 위한 컴퓨팅사고력(Computational Thinking)의 9가지 핵심요소 적용에 계열별 학습자들은 다음과 같은 차이를 보였다. 인문계열 학습자들은 자료수집, 문제분해, 자동화의 요소를 주로 문제해결과정에 적용하는 반면, 자연계열 학습자들은 자료분석, 알고리즘, 자동화의 요소를 주로 적용하였다. 또한, 예술계열 학습자들은 자료표현, 추상화, 자동화의 요소를 주로 적용하였다. 소프트웨어 개발에 컴퓨팅사고력(Computational Thinking)을 적용할 때 역시 인문계열 학습자들은 자료수집, 알고리즘, 자동화의 요소를 주로 적용하는 반면, 자연계열 학습자들은 자료분석, 알고리즘, 자동화의 요소를 주로 적용하였다. 또한, 예술계열 학습자들은 자료표현, 추상화, 시뮬레이션의 요소를 주로 적용하였다. 본 연구의 결과를 토대로 각 대학에서 실시하고 있는 기초소프트웨어교육 과정의 설계에 계열별 학습자 분석이 반드시 포함되어 학습자의 교육적 효용성이 극대화되기를 바란다.

Keywords

References

  1. Bar, D., Harrison, J., and Conery, L., "Computational thinking: A Digital Age Skill for Everyone," Learning & Learning with Technology, Vol. 38, No. 6, pp. 20-23, 2011.
  2. Carlisle, M. C., Wilson, T. A., Humphries, J. W., and Hadfield, S. M., "RAPTOR: Introducing Programming to Non-Majors with Flowcharts," Journal of Computing Sciences in Colleges, Vol. 19, No. 4, pp. 52-60, 2004.
  3. Choi, J. W., "A Comparative Analysis of Curriculums for Software-related Departments based on Topic Modeling," The Journal of Society for e-Business Studies, Vol. 22, No. 4, pp. 193-214, 2017. https://doi.org/10.7838/jsebs.2017.22.4.193
  4. Computer Science Teachers Association & International Society for Technology in Education, Computational Thinking Teacher Resources, http://csta.acm.org/Curriculum/sub/CompThinking.html, 2011.
  5. Kim, C., "Needs of Improving the Curriculum of National University of Education for Strengthening SW Education," Journal of the Korean Association of Information Education, Vol. 23, No. 1, 2019.
  6. Kim, W. S., "A Study on the Recognition of Freshman on Computational Thinking as Essential Course," Culture and Convergence, Vol. 39, No. 6, pp. 141-170, 2017. https://doi.org/10.33645/cnc.2017.12.39.6.141
  7. Korea Institute for Curriculum and Evaluation, "Introduction to the revised curriculum in 2015", Research Report CRC 2015-28, 2015.
  8. Kwon, J. I. and Kim, J. H., "A Study on Design and Development of SW Course based on Computational Thinking", in Proc of Asia Pacific International Conference on Information Science and Technology(APIC-IST), 2017.
  9. Kwon, J. I., "A Study on the Effectiveness of Computational Thinking based Teaching and Learning on Students' Creative Problem Solving Skills," Ph.D. Dissertation, Sungkyunkwan University, 2014.
  10. Lee, M. S., "Non-Engineering Challenges of Software Education," The Korean Association of General Educational Conference, pp. 135-140, 2016.
  11. Lee, S. J., "A Study on Designing a Class of Convergence Thinking based on Computational Thinking," The Korean Society of Science & Art 36, pp. 255-26, 2018. https://doi.org/10.17548/ksaf.2018.12.30.255
  12. Papert, S., "An Exploration in the Space of Mathematics Educations," International Journal of Computers for Mathematical Learning, Vol. 1, No. 1, pp. 95-123, 1996. https://doi.org/10.1007/BF00191473
  13. Schwab, K., "Introduction in The Fourth Industrial Revolution," https://www.weforum.org/about/the-fourth-industrial-revolutionby-klaus-schwab (retrieved on February 1, 2017), 2016.
  14. Su, E. K., "Development of Creative Thinking and Coding Course method on Design Thinking using Flipped Learning," Journal of Learner-Centered Curriculum and Instruction, Vol. 17, No. 16, pp. 173-199, 2017.
  15. Urban-Lurain, M. and Weinshank, D. J., "Is There A Role for Programming in Non-Major Computer Science Courses?," Frontiers in Education Conference, FIE2000 30th Annual, 2000.
  16. Wing, J. M., "Computational Thinking and Thinking about Computing," Philosophical Transactions of the Royal Society, Vol. 366, pp. 3717-3725, 2008. https://doi.org/10.1098/rsta.2008.0118
  17. Wing, J. M., "Computational Thinking," Communications of the ACM, Vol. 49, No. 3, pp. 33-35, 2006. https://doi.org/10.1145/1118178.1118215