Journal of The Korean Association of Information Education (정보교육학회논문지)

Korea Association of Information Education (한국정보교육학회)
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A Self-regulated Learning Model Development in Computer Programming Education

컴퓨터 프로그램 교육에서 자기조절 학습 모델 개발

  • Kim, Kapsu (Dept. of Computer Education, Seoul National University of Education)
  • 김갑수 (서울교육대학교 컴퓨터교육과)
  • Received : 2014.12.28
  • Accepted : 2015.03.10
  • Published : 2015.03.31
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Abstract

Information and knowledge society in the 21st century computer education is very important. Computer programming education in computer education is very important. There are very few teaching and learning model of computer programming education. In this paper, we develop a self-regulated learning model for students to be self-regulated learning. In this study, we propose self-regulated learning elements, a self-regulated learning steps and self-regulated learning modele. Self-regulated learning elements are task level, generalized level, and efficiency level. Self-regulated learning phases are problem understanding, design, and coding, testing, and maintenance. Self-regulated learning models are to copy, to modify, create, and to challenge. The results of this study are as follows. At Correlations between learning elements and achievement, generalized level, and efficiency level are higher than the task level. At Correlations between learning and achievement, Understanding and design stages are higher than the other stages. At Correlations between learning model and achievement, to transform, to create, and to challenge are higher than to copy.

21세기 지식 정보 사회에 컴퓨터 교육이 매우 중요하다. 컴퓨터 교육에서 컴퓨터 프로그래밍 교육이 매우 중요하다. 컴퓨터 프로그래밍 교육에는 교수 학습 모델이 거의 없다. 본 연구에서는 학생들이 자기조절 학습을 할 수 있는 자기 조절 학습 모형을 개발한다. 본 연구에서는 자기 조절 학습 요소, 자기 조절 학습 단계와 자기 조절 학습 모형을 제안한다. 자기조절 학습 요소는 과제 수준, 일반화, 효율화이다. 자기조절 학습 단계는 문제이해, 설계, 코딩, 시험, 유지보수이다. 자기조절 학습 모델은 복사하기, 변형하기, 창조하기, 도전하기이다. 본 연구의 결과는 다음과 같다. 학습 요소들과 성취도간의 상관관계 분석은 효율화와 일반화가 과제 수준보다 더 높았다. 학습 단계에는 문제 이해와 설계 단계가 다른 단계보다 더 높았다. 학습 모형에서는 변형하기, 창조하기, 도전하기가 구현하기보다 상관관계가 더 높았다.

Keywords

References

  1. B. J. Zimmerman (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist, 25(1), 3-17. https://doi.org/10.1207/s15326985ep2501_2
  2. Boekaerts, M. (1995). Self-regulated learning: Bridging the gap between metacognitive and metamotivation theories. Educational Psychologist, 30, 195-200. https://doi.org/10.1207/s15326985ep3004_4
  3. Boekarts, M., Pintrich, P. R., & Zeidner, M. (Eds.), (2000). Handbook of self-regulation. San Diego, CA: Academic.
  4. Dona M. Kagan (1989). Research on Computer Programming as a Cognitive Activity: implications for the study of classroom teaching. Journal of Education for Teaching, 15(3), 177-189. https://doi.org/10.1080/0260747890150301
  5. Garris, R., Ahlers, R., & Driskell, J. E. (2002). Games, motivation, and learning: A research and practice model. Simulation & Gaming, 33, 441-467. https://doi.org/10.1177/1046878102238607
  6. Gee, J. P. (2003). What video games have to teach us about learning and literacy. New York: Palgrave Macmillan.
  7. Gee, J. P. (2005). Learning by design: Good video games as learning machines. E-Learning, 2, 5-16. https://doi.org/10.2304/elea.2005.2.1.5
  8. Hur, Jae Eun & Kim, Hong Chan (2014). The effect of the Self-Regulated Learning Ability on the Process of Selecting Assisted-Learning in the Middle School Mathematics Education. Journal of the Korean School Mathematics Society, 17(1), 1-21.
  9. Kapsu Kim (2014). Measuring and Applying the Self-efficacy in Computer Programming Education. Journal Of The Korean Association Of Information Education, 18(1), 111-120. https://doi.org/10.14352/jkaie.2014.18.1.111
  10. Lan, W. (2005). Self-Monitoring and its relationship with educational level and task performance. Educational Psychology, 25(1), 109-127. https://doi.org/10.1080/0144341042000294921
  11. Miltiadou, M., & Yu, C. H. (2000). Validation of the Online Technologies Self-Efficacy Scale (OTSES)(Publication no. ED445672). Retrieved January 15, 2004.
  12. Nong Ye Gavriel Salvendy (1996). Expert-novice knowledge of computer programming at different levels of abstraction. Ergonomics, 39(3), 461-481. https://doi.org/10.1080/00140139608964475
  13. Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82, 33-40. https://doi.org/10.1037/0022-0663.82.1.33
  14. Pressley, M., & Ghatala, E. S. (1990). Self-regulated learning: Monitoring learning from text. Educational Psychologist, 25, 19-34. https://doi.org/10.1207/s15326985ep2501_3
  15. Pressley, M., & Ghatala, E. S. (1990). Self-regulated learning: Monitoring learning from text. Educational Psychologist, 25, 19-34. https://doi.org/10.1207/s15326985ep2501_3
  16. Salomon G & Perkins D. N. (1987). Transfer of cognitive skills from programming: When and how?. Journal of Educational computing Research, 3, 149-169. https://doi.org/10.2190/6F4Q-7861-QWA5-8PL1
  17. Schraw, G. (2007). The use of computer-based environments for understanding and improving selfregulation. Metacognition and Learning, 2, 169-176. https://doi.org/10.1007/s11409-007-9015-8
  18. Schraw, G., Crippen, K. J., & Hartley, K. (2006). Promoting self-regulation in science education: Metacognition as part of a broader perspective on learning. Research in Science Education, 36, 111-139. https://doi.org/10.1007/s11165-005-3917-8
  19. Youngsu Goo & Yeonsuk Yang (2013). A Comparison Study of Learning Style, Self-regulated Learning and Learning Flow between Gifted and Normal Student. Journal of Gifted/Talented Education, 23(2), 177-191. https://doi.org/10.9722/JGTE.2013.23.2.177

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