DOI QR코드

DOI QR Code

문제해결학습 기반의 소프트웨어 교육에 대한 만족도와 학업 성적의 상관관계 분석

Analysis of Correlation between Satisfaction and Academic Achievement of Software Education Based on Problem-solving Learning

  • 이영석 (강남대학교 KNU 참인재대학) ;
  • 조정원 (제주대학교 컴퓨터교육과)
  • Lee, Youngseok (KNU College of Liberal Arts and Sciences, Kangnam University) ;
  • Cho, Jungwon (Department of Computer Education, Jeju National University)
  • 투고 : 2019.01.14
  • 심사 : 2019.02.20
  • 발행 : 2019.02.28

초록

대학 교육은 컴퓨팅 사고력 기반의 융합 인재 양성을 강조하고 있으며, 문제 해결력을 향상시키기 위해 소프트웨어 교육을 강조하고 있다. 본 연구에서는 문제해결학습 기반의 파이선 프로그래밍을 통한 소프트웨어 교육을 실시하고, 이에 대한 만족도와 학업 성적간의 상관관계를 분석한다. 문제해결학습 기반의 소프트웨어 교육을 받는 대학생 143명을 대상으로 설문조사를 실시한 결과, 실제 학업 성적과의 상관관계 분석과 다중회귀분석을 통해 문제해결학습의 만족도와 학업 성적 간에 관련성이 있고, 학업 성적에도 영향을 주는 것으로 나타났다. 다양한 문제상황을 파악하고 컴퓨팅 사고력을 활용하여 문제를 해결하는 능력은 점점 더 중요해질 것이므로, 대학 소프트웨어 교육은 문제해결학습 기반으로 실시하는 것이 바람직한 방향이 될 것이다.

University education emphasizes the development of convergent as well as computational thinking, many universities provide software education to improve their problem-solving ability. In this study, we use Python programming based on problem-solving learning, and analyze the correlation between problem-solving learning satisfaction and academic achievement. A questionnaire survey was conducted among 143 students, we tried to analyze the relationship of problem-solving learning with actual academic performance using correlation and multiple regression analysis. The results indicate a relationship between satisfaction and academic achievement, and that it affects students' academic achievement. The ability to identify various problem situations and solve problems using computational thinking will become increasingly important, it is desirable that the universities provide software education based on problem-solving learning.

키워드

Table 1. Detailed criteria for satisfaction with software education based on problem-solving learning

JKOHBZ_2019_v9n2_49_t0001.png 이미지

Table 2. A questionnaire survey

JKOHBZ_2019_v9n2_49_t0002.png 이미지

Table 5. The results of correlation analysis

JKOHBZ_2019_v9n2_49_t0003.png 이미지

Table 6. The results of multiple regression analysis

JKOHBZ_2019_v9n2_49_t0004.png 이미지

Table 3. The results of descriptive table

JKOHBZ_2019_v9n2_49_t0005.png 이미지

Table 4. The results of ANOVA analysis

JKOHBZ_2019_v9n2_49_t0006.png 이미지

참고문헌

  1. G. Chen, J. Shen, L. Barth-Cohen, S. Jiang, X. Huang, & M. Eltouhky. (2017). Assessing Elementary Students' Computational Thinking in Everyday Reasoning and Robotics Programming. Computer and Education, 109, 162-175. DOI : https://doi.org/10.1016/j.compedu.2017.03.001
  2. I. Jeong. (2017). Study on the Preliminary Teachers' Perception for the Development of Curriculum of the Robot-based Software Education in the Universities of Education. Journal of The Korean Association of Information Education, 21(3), 277-284. https://doi.org/10.14352/jkaie.21.3.277
  3. Y. Jeon & T. Kim. (2015). The Design and Application of an Experience-Driven Online Software Class Based on Creative Problem Solving for Cultivating the Creative Personality of the Elementary Informatics-Gifted Students. The Journal of Korea Elementary Education, 26(4), 477-494. https://doi.org/10.20972/kjee.26.4.201512.477
  4. S. Paik. (2017). The Effects of Educational Programming Language with PBL(Problem Based Learning) on logical thinking ability and Problem Solving ability in elementary school environments. Master thesis. Korea National University of Education, Chung-Buk.
  5. B. Kim, Y. Jeon, J. Kim & T. Kim. (2016). Development and Application of Real Life Problem Solving Lesson Contents Based on Computational Thinking for Informatics Integrated-Gifted Elementary School Students' Creativity. Korean Journal of Teacher Education, 32(1), 159-186. https://doi.org/10.14333/KJTE.2016.32.1.159
  6. J. Ku, Y. Jeon & T. Kim. (2016). The Development and Application of Lesson Contents Based on the CT-CPS Framework for Improving the Creative Problem Solving Ability of Elementary Informatics Gifted Students. The Journal of Korea Elementary Education, 27(2), 339-357. https://doi.org/10.20972/kjee.27.2.201606.339
  7. H. Y. Jung. (2014). An Empirical Study on Information Liberal Education in University based on IT Fluency and Computational Thinking Concept. Journal of the Korea society of computer and information, 19(2), 263-274. https://doi.org/10.9708/jksci.2014.19.2.263
  8. K. Kim & H. Kim. (2014). A Case Study on Necessity of Computer Programming for Interdisciplinary Education. Journal of Digital Convergence, 12(11), 339-348. https://doi.org/10.14400/JDC.2014.12.11.339
  9. S. J. Kim & D. E. Cho. (2018). A Stduy on Learning Model for Effective Coding Education. Journal of the Korea Convergence Society, 9(2), 7-12. https://doi.org/10.15207/JKCS.2018.9.2.007
  10. J. Seo. (2017). A Case Study on Programming Learning of Non-SW Majors for SW Convergence Education. Journal of Digital Convergence, 15(7), 123-132. https://doi.org/10.14400/JDC.2017.15.7.123
  11. S. H. Kim. (2015). Analysis of Non-Computer Majors' Difficulties in Computational Thinking Education. The Journal of Korean Association of Computer Education, 18(3), 15-23. https://doi.org/10.32431/KACE.2015.18.3.002
  12. Y. Lee. (2018). Analyzing the effect of software education applying problem-solving learning. Journal of Digital Convergence, 16(3), 95-100. https://doi.org/10.14400/JDC.2018.16.3.095
  13. Y. Lee. (2018). Python-based Software Education Model for Non-Computer Majors. Journal of the Korea Convergence Society, 9(3), 73-78. https://doi.org/10.15207/JKCS.2018.9.3.073