The Journal of Korean Association of Computer Education (컴퓨터교육학회논문지)

The Korean Association of Computer Education (한국컴퓨터교육학회)
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SEM-CT: Comparison of Problem Solving Processes in Science(S), Engineering(E), Mathematic(M), and Computational Thinking(CT)

SEM-CT: 과학(S), 공학(E), 수학(M)적 문제해결과정과 컴퓨팅 사고(CT)

  • 남윤경 (부산대학교 지구과학교육과) ;
  • 윤진아 (부산대학교 과학교육연구소) ;
  • 한금주 (부산대학교 수학교육과) ;
  • 정주훈 (부산대학교 소프트웨어교육센터)
  • Received : 2019.02.28
  • Accepted : 2019.05.20
  • Published : 2019.05.31
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Abstract

The main purpose of STEM education is to understand methods of inquiry in each discipline to develop convergent problem solving skills. To do this, we must first understand the problem-solving process that is regarded as an essential component of each discipline. The purposes of this study is to understand the relationship between the problem solving in science (S), engineering (E), mathematics (M), and computational thinking (CT) based on the comparative analysis of problem solving processes in each SEM discipline. To do so, first, the problem solving process of each SEM and CT discipline is compared and analyzed, and their commonalities and differences are described. Next, we divided the CT into the instrumental and thinking skill aspects and describe how CT's problem solving process differs from SEM's. Finally we suggest a model to explain the relationship between SEM and CT problem solving process. This study shows how SEM and CT can be converged as a problem solving process.

STEM 융합교육의 중요한 목적은 서로 다른 학문이 가지는 탐구의 방법을 이해함으로써 융합적 문제해결력을 기르는 것이다. 이를 위해 우선적으로 각 학문에서 중요하게 다루어지는 문제해결과정을 이해해야 한다. 본 연구는 과학(S), 공학(E), 수학(M) 각각의 분야에서 어떻게 문제해결과정을 정의하고 있는지 비교분석하고, 이를 근거로 SEM 문제해결과 CT 문제해결의 관련성을 파악하고자 하였다. 이를 위해 먼저 SEM 각 학문의 문제해결과정을 비교 분석하여 그 공통점과 차이점을 기술하였다. 다음으로 CT를 도구적 측면과 사고적 측면으로 구분하고 문제해결과정으로서 CT가 SEM 각각의 학문에서 문제해결과 어떤 차이가 있는지 기술하였다. 마지막으로, SEM 문제해결 프로세스와 CT와의 관계를 모형으로 제시하였다. 본 연구는 문제해결과정으로써 CT와 SEM이 융합할 수 있는 방향을 제시한다는 점에서 그 의미가 있다.

Keywords

References

  1. 교육부 (2015a). 과학과 교육과정. 교육부 고시 제2015-74호 [별책9]. 서울 : 교육부.
  2. National Research Council(NRC). (2010). Standards for K-12 engineering education?. National Academies Press.
  3. Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., &Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25 (1), 127-147. https://doi.org/10.1007/s10956-015-9581-5
  4. 최숙영 (2016). 문제해결의 관점에서 컴퓨팅 사고력 증진을 위한 교수학습에 대한 연구. 컴퓨터교육학회논문지, 19(1), 53-62. https://doi.org/10.32431/KACE.2016.19.1.006
  5. Wing, J. (2006). Computational thinking. Communications of the ACM, 49 (3), 33-35. https://doi.org/10.1145/1118178.1118215
  6. Wing, J. (2008). Computational thinking and thinking about computing. Philosophical transactions of the royal society of London A: mathematical, physical and engineering sciences, 366 (1881), 3717-3725. https://doi.org/10.1098/rsta.2008.0118
  7. Lockwood, J., & Mooney, A. (2017). Computational thinking in education: Where does it fit? A systematic literary review. arXiv preprint arXiv:1703.07659. Retrieved from: https://pdfs.semanticscholar.org/856e/ed bf3ad4902e86ba94ab8dd124e6a1495889.pdf
  8. 정웅열.이영준 (2018). SW.수학.과학 융합형 교수.학습 자료에 나타난 교육과정 성취기준 내용 분석. 컴퓨터교육학회논문지, 21(5), 11-23. https://doi.org/10.32431/kace.2018.21.5.002
  9. National Research Council (NRC). (2000). Inquiry in the national science education standards: A guide for teaching and learning. Washington, DC: National Academy Press.
  10. Chinn, C., & Malhotra, B. (2002). Epistemologically authentic inquiry in schools: A theoretical framework for evaluating inquiry tasks. Science Education, 86 (2), 175-218. https://doi.org/10.1002/sce.10001
  11. Bybee, R., Carlson-Powell, J., & Trowbridge, L. (2008). Teaching secondary school science: Strategies for developing scientific literacy. Columbus: Pearson/Merrill/Prentice Hall.
  12. Wang, L., Zhang, R., Clarke, D., & Wang, W. (2014). Enactment of scientific inquiry: Observation of two cases at different grade levels in China Mainland. Journal of Science Education and Technology, 23 (2), 280-297. https://doi.org/10.1007/s10956-013-9486-0
  13. Lunetta, V., Hofstein, A., & Clough, M. (2007). Learning and teaching in the school science laboratory: An analysis of research, theory, and practice. Handbook of Research on Science Education, 2.
  14. So, W. W. M., Zhan, Y., Chow, S. C. F., & Leung, C. F. (2017). Analysis of STEM activities in primary students' science projects in an informal learning environment. International Journal of Science and Mathematics Education, 1-12
  15. Chin, C., & Brown, D. (2002). Student-generated questions: A meaningful aspect of learning in science. International Journal of Science Education, 24(5), 521-549. https://doi.org/10.1080/09500690110095249
  16. Schwab, J. (1966). The teaching of science as inquiry. Cambridge, MA: Harvard University Press.
  17. 김영민.서혜애.박종석 (2013). 잘 알려진 창의적 과학자들의 과학적 문제 발견 패턴 분석. 한국과학교육학회지, 33(7), 1285-1299. https://doi.org/10.14697/jkase.2013.33.7.1285
  18. Hoover, S. & Feldhusen, J. (1990). The scientific hypothesis formulation th-grade students. Journal of Educational Psychology, 82(4), 838-848. https://doi.org/10.1037/0022-0663.82.4.838
  19. 전윤식.김정섭.윤경미 (2003). 창의성 교육의 새로운 접근 : 문제 찾기. 교육학연구, 41(3), 215-238.
  20. 조희형.김희경.윤희숙.이기영 (2009). 과학 교육의 이론과 실제. 서울: 교육과학사.
  21. 조현국 (2018). 2015 개정 교육과정에서 나타나는 과학적 탐구 요소 분석 : 과학탐구실험을 중심으로. 교과교육학연구, 22(3), 208-218. https://doi.org/10.24231/RICI.2018.22.3.208
  22. 한효순.최병순.강순민.박종윤 (2002). '생각하는 과학'프로그램의 변인활동이 초등학생의 변인통제 능력에 미치는 효과. 한국과학교육학회지, 22(3), 571-585.
  23. Dewey, J. (1938). Democracy and education. New York: Macmillan.
  24. Nam, Y., Lee, S. J., & Paik, S. H. (2016). The impact of engineering integrated science (EIS) curricula on first-year technical high school students' attitudes toward science and perceptions of engineering. Eurasia Journal of Mathematics, Science & Technology Education, 12 (7), 1881-1907.
  25. NGSS Lead States. (2013). Next generation science standards: For states, by states. National Academies Press.
  26. Hjalmarson, M., & Lesh, R. (2008). Engineering and design research: Intersections for education research and design. In Handbook of design research methods in education: Innovations in science, technology, engineering, and mathematics learning and teaching. (pp. 114-128). Routledge.
  27. 문대영 (2008). STEM 통합 접근의 사전 공학 교육 프로그램 모형 개발. 공학교육연구, 11(2), 90-101. https://doi.org/10.18108/JEER.2008.11.2.90
  28. 이영준.백성혜.신재홍.유헌창.정인기.안상진.최정원.전성균 (2014). 초중등 단계 Computational Thinking 도입을 위한 기초 연구[BD14060010]. 한국과학창의재단.
  29. Moore, T. J., Glancy, A. W., Tank, K. M., Kersten, J. A., Smith, K. A., Stohlmann. M. S. (2014). A framework for quality K-12 engineering education: Research and development. Journal of Pre-College Engineering Education Research, (J-PEER), 4 (1), 1-13.
  30. 교육부 (2015b). 수학과 교육과정. 교육부 고시 제2015-74호 [별책 8]. 서울 : 교육부.
  31. 김성준 (2002). 학교 대수 도입과 관련된 논의. 학교수학, 4(1), 29-47
  32. Polya, G. (1971). How to solve it: a new aspect of mathematical method (2nd ed.). Princeton, N.J. : Princeton University Press, c1957.
  33. Schoenfeld, A. H. (1985). Mathematical problem solving. New York: Academic Press
  34. Burton, D. (1985). The History of mathematics : An introduction. Boston: Allyn and Bacon.
  35. Mayer, R. E. (1999). Multimedia aids to problem-solving transfer. International Journal of Educational Research, 31 (7), 611-623. https://doi.org/10.1016/S0883-0355(99)00027-0
  36. Partnership for 21st Century Skills(P21). (2009). P21 framework definitions. Retrieved December 1, 2014, from http://www.p21.org
  37. ATC21S (2012). Defining twenty-first century skills. Retrieved December 1, 2014, from http://www.atc21s.org
  38. ISTE & CSTA (2011). Operational definition of computational thinking for K-12 education.
  39. Burgett, T., Folk, R., Fulton, J., Peel, A., Pontelli, E., & Szczepanski, V. (2015). DISSECT: Analysis of pedagogical techniques to integrate computational thinking into K-12 curricula. In Frontiers in Education Conference (FIE), 2015. 32614 2015. IEEE (pp. 1-9). IEEE.
  40. Henderson, P. B. (2009) Ubiquitous computational thinking, Computer, (2009 October), 100-102.
  41. 유중현.김종혜 (2008). 문제 해결과정에서의 정보과학적 사고 능력에 대한 개념적 고찰. 정보창의교육논문지, 2(2), 15-24.
  42. 박성빈.안성진 (2016). 컴퓨팅 사고력의 역량 탐색 연구 : 소프트웨어개발자를 중심으로. 컴퓨터교육학회논문지, 19(5), 41-53. https://doi.org/10.32431/KACE.2016.19.5.004
  43. Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: what is Involved and what is the role of the computer science education community?. Acm Inroads, 2 (1), 48-54. https://doi.org/10.1145/1929887.1929905
  44. Bundy, A. (2007). Computational thinking is pervasive. Journal of Scientific and Practical Computing, 1 (2), 67-69.
  45. Selby, C., Dorling, M., & Woollard, J. (2014). Evidence of assessing computational thinking. Brookes e Journal of Learning and Teaching, 1-12.
  46. Deek, F. P., Hiltz, S. R., Kimmel, H. & Router, N. (1999). Cognitive Assessment of Students' Problem Solving and Program Development Skills. Journal of Engineering Education, 88 (3), 317-326. https://doi.org/10.1002/j.2168-9830.1999.tb00453.x
  47. Guilford, J. P. (1967). Creativity: Yesterday, today and tomorrow. The Journal of Creative Behavior, 1 (1), 3-14. https://doi.org/10.1002/j.2162-6057.1967.tb00002.x
  48. Heller, K. A. (2007). Scientific ability and creativity. High Ability Studies, 18 (2), 209-234. https://doi.org/10.1080/13598130701709541
  49. 박종원 (2004). 과학적 창의성 모델의 제안 : 인지적 측면을 중심으로. 한국과학교육학회지, 24(2), 375-386.
  50. Runco, M. A., & Acar, S. (2012). Divergent thinking as an indicator of creative potential. Creativity Research Journal, 24 (1), 1-10. https://doi.org/10.1080/10400419.2012.649235
  51. Sternberg R.J., & Lubart, T. (1993). Creative giftedness: A multivariante investment ap-proach. Gifted Child Quarterly, 37 (1), 7-15. https://doi.org/10.1177/001698629303700102
  52. 하주현 (2003). 문제발견, 창의적 사고, 창의적 인성의 관계. 교육심리연구, 17(3), 99-115.
  53. 김영채 (1997). 창의적 문제 해결 : 창의력의 이론, 개발과 수업. 서울: 교육과학사
  54. Carson, D. K., & Runco, M. A. (1999). Creative problem solving and problem finding in young adults: Interconnections with stress, hassles, and coping abilities. The Journal of Creative Behavior, 33 (3), 167-188. https://doi.org/10.1002/j.2162-6057.1999.tb01195.x
  55. 박미진 (2016). 과학개념 융합을 통한 문제발견 및 문제해결 과정에서 나타나는 과학영재의 창의적 사고의 특성. 박사학위논문, 부산대학교.
  56. Harms, H. R., & Janosz, D. A. (2012). Pre-engineering. McGraw Hill Education.
  57. 황혜정.나귀수.최승현.박경미.임재훈.서동엽 (2016). 수학교육학신론. 서울: 문음사.
  58. NCTM(1991). Mathematical modeling in the secondary school curriculum, In Frank Swetz and J. S. Hartzler(Eds.). Reston, VA: The National Council of Teachers of Mathematics.
  59. 한병래 (2013). 초등정보교육에서의 계산적사고 교육을 위한 언플러그드 컴퓨팅 방법에 관한 고찰. 정보교육학회논문지, 17(2), 147-156.
  60. 이동영.남윤경 (2018) 공학설계 측면에서 한국 STEAM 프로그램 분석틀 제안. 대한지구과학교육학회지, 11(1), 63-77. https://doi.org/10.15523/JKSESE.2018.11.1.63
  61. Rodriguez, B., Rader, C. & Camp, T. (2016). Using student performance to assess CS unplugged activities in a classroom environment. In proceedings of the 2016 ACM conference on innovation and technology in computer science education (pp. 95-100). ACM.
  62. Taub, R., Armoni, M. and Ben-Ari, M., (2012). CS unplugged and middle-school students' views, attitudes, and intentions regarding CS. ACM Transactions on Computing Education (TOCE), 12(2), No 8.

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