박사

지속가능한 흥미 발달을 위한 피지컬 컴퓨팅 활용 프로그래밍 교육 연구 = A study on Programming Education using Physical Computing for Sustainable Interest Development

전성균 2016년
논문상세정보
' 지속가능한 흥미 발달을 위한 피지컬 컴퓨팅 활용 프로그래밍 교육 연구 = A study on Programming Education using Physical Computing for Sustainable Interest Development' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • 초등교육( 국민학교 교육 )
  • 스튜디오기반 학습
  • 프로그래밍
  • 피지컬 컴퓨팅
  • 흥미
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
393 0

0.0%

' 지속가능한 흥미 발달을 위한 피지컬 컴퓨팅 활용 프로그래밍 교육 연구 = A study on Programming Education using Physical Computing for Sustainable Interest Development' 의 참고문헌

  • 흥미 연구의 현재와 향후 연구 방향
    우연경 교육심리연구, 26(4), 1179-1199 [2012]
  • 학업동기: 이론, 연구와 적용
    김아영 서울: 학지사. 162-172 [2010]
  • 초중 등 단계Computational Thinking 도입을 위한 기초연구
  • 미래학교 지원을 위한 21 세기 교수- 학습 활동 개발 시리즈 1: 21 세기 학습자 및 교수자 역량 모델링. 한국교육학술정보원 연구보고
  • 듀이의 흥미 개념과 학생중심 교육과정
    양은주 교육과정연구, 21(1), 179-202 [2003]
  • Roseman, I. J., & Smith, C. A. (2001). Appraisal theory: Overview, assumptions, varieties, controversies. In K. R. Scherer, A. Schorr, & T. Johnstone (Eds.), Appraisal processes in emotion: Theory, methods, research (pp. 3–19). New York: Oxford University Press
  • Partnership for 21st century skills. (2009). P21 Framework Definitions. Available from http://www.p21.org/
  • Papert, S., & Harel, I. (1991). Situating Constructionism. In Papert, S., Harel, I. (Eds.), Constructionism. Ablex Publishing Corporation, Norwood.
  • Papert, S. (1980). Mindstorms - Children, Computers, and Powerful Ideas. Basic Books, Inc., New York.
  • Oatley, K., Keltner, D., & Jenkins, J. M. (2006). Understanding emotions . Blackwell publishing.
  • OECD(2003). Definition and selection of competencies: Theoretical and conceptual foundations
  • O'Sullivan, D., & Igoe, T. (2004). Physical computing: sensing and controlling the physical world with computers. Course Technology Press.
  • Nunez, R. E., Edwards, L. D., & Matos, 1. F. (1999). Embodied cognition as grounding for situatedness and context in mathematics education. Educational Studies in Mathematics, 39, 45-65.
  • Nathan, M.J., R. Srisurichan, C. Walkington, M. Wolfgram, C. Williams, and M.W. Alibali. (2013). Cohesion as a mechanism of STEM integration. Journal of Engineering Education, 102(1), 1–216. (Special issue on representation in engineering education.)
  • Monson, C. (2007). Studio school: Propose, critique, iterate. Retrieved March 30, 2007, from the Mississippi State University, College of Education Web s i t e : h t t p : / / ww w. e d u c .ms s t a t e . e d u / s t u d i o s c h o o l . h tm( n owa t http://www.studioschool.org)
  • Millis, K. (2001). Making meaning brings pleasure: the influence of titles on aesthetic experiences. Emotion, 1(3), 320-329.
  • Meerbaum-Salant, O., Armoni, M., & Ben-Ari, M. (2013). Learning computer science concepts with Scratch. Computer Science Education, 23(3), 239- 264.
  • McKinsey & Company. (2004). Using Logic models to bring together planning, evaluation, and action: Logic model development guide. Battle Creek, MI: W. K. KelloggFoundation.
  • McDaniel, M. A., Waddill, P. J., Finstad, K., & Bourg, T. (2000). The effects of text-based interest on attention and recall. Journal of Educational Psychology, 92(3), 492-502.
  • Mayer, J. D., & Gaschke, Y. N. (1988). The experience and meta-experience of mood. Journal of personality and social psychology, 55(1), 102-111.
  • Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12?. Computers in Human Behavior, 41, 51-61.
  • Latour, B. (1999). Pandora’s hope. Essays on the reality of science studies. Cambridge, MA:Harvard University Press.
  • Lackney, J. (1999). A history of the studio-based learning model. Retrieved http://www.edi.msstate.edu/work/pdf/history_studio_based_learning.pdf
  • Krapp, A. (1999). Interest, motivation and learning: An educational-psychological perspective. European journal of psychology of education, 14(1), 23-40.
  • Krapp A., Hidi, S., & Renninger, K.A. (1992). Interest, learning, and development. In K.A. Renninger, S. Hidi, & Krapp, A (Eds.), The role of interest in learning and development. (3-25). Hillsdale, NJ: Lawrence Erlbaum.
  • Kozma, R., E. Chin, J. Russell, and N. Marx. (2000). The role of representations and tools in the chemistry laboratory and their implications for chemistry learning. Journal of the Learning Sciences 9(3), 105–144.
  • Koulouri, T., Lauria, S., & Macredie, R. D. (2015). Teaching introductory programming: a quantitative evaluation of different approaches. ACM Transactions on Computing Education (TOCE), 14(4), 26.
  • Kosslyn, S . M. (2005). Mental images and the brain. Cognitive Neuropsychology, 22(3/4),333-347.
  • Keller, J. M. (1987). Development and use of the ARCS model of instructional design. Journal of instructional development, 10(3), 2-10.
  • Kelleher, C., & Pausch, R. (2005). Lowering the barriers to programming: A taxonomy of programming environments and languages for novice programmers. ACM Computing Surveys (CSUR), 37(2), 83-137.
  • Kaminski, J.A., V.M. Sloutsky, and A. Heckler. (2009). Transfer of mathematical knowledge: The portability of generic instantiations. Child Development Perspectives, 3(3), 151–155.
  • Kaminiski, J. A., Sloutsky, V. M., Heckler, A. F., Sun, R., & Miyake, N. (2006). Effects of concreteness on representation: An explanation for differential transfer. In Proceedings of the XXVIII Annual Conference of the Cognitive Science Society, 1581-1586.
  • Kahneman, D. (2003). A perspective on judgement and choice. American Psychologist, 58(9), 697-720.
  • Kafai, Y. B., & Burke, Q. (2013). Computer Programming Goes Back to School. Phi Delta Kappan, 95(1), 61-65.
  • K ller, O., Baumert, J., & Schnabel, K. (2001). Does interest matter? The relationship between academic interest and achievement in mathematics. Journal for Research in Mathematics Education, 32(5), 448-470.
  • Honey, M., Pearson, G., & Schweingruber, H. (Eds.). (2014). STEM Integration in K-12 Education: Status, Prospects, and an Agenda for Research. National Academies Press.
  • Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn?. Educational psychology review, 16(3), 235-266.
  • Hidi, S., & Anderson, V. (1992). Situational interest and its impact on reading and expository writing. The role of interest in learning and development, 215-238.
  • Hidi, S. (1990). Interest and its contribution as a mental resource for learning. Review of Educational research, 60(4), 549-571.
  • Hergenhahn, B. R., & Olson, M. H. (2001). An introduction to theories oflearning (6th ed.). Upper Saddle River, NJ: MerrilllPrentice Hall.
  • Hepper, P. P., & Petersen, C. H. (1982). The development and implications of a personal problem-solving inventory. Journal of Counseling Psychology, 29(1), 66-75.
  • Hekkert, P., & van Wieringen, P. C. (1996). The impact of level of expertise on the evaluation of original and altered versions of post-impressionistic paintings. Acta psychologica, 94(2), 117-131.
  • Hauk, O., Johnsrude, 1., & Pulvermi.iller, F. (2004). Somatotopic representation of action words in human motor and premotor cortex. Neuron, 41(2), 30 1-307.
  • Grover, S., & Pea, R. (2013). Computational Thinking in K–12 A Review of the State of the Field. Educational Researcher, 42(1), 38-43.
  • Green, L. N., & Bonollo, E. (2003). Studio-based teaching: history and advantages in the teaching of design. World Transactions on Eng. and Tech. Edu, 2(2), 269-272.
  • Goldstone, R. L., and J. . Son. (2005). The transfer of scientific principles using concrete and idealized simulations. Journal of the Learning Sciences 14(1), 69–110.
  • Goldstone, R . L., Landy, D. H., & Son, J. Y. (2009). The education of perception. Topics in Cognitive Science, 2(2), 265-284.
  • Gick, M. L., & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive psychology, 15(1), 1-38.
  • Gallese, v., & Lakoff, G. (2005). The brain's concepts: The role of the sensory-motor system in conceptual knowledge. Cognitive Neuropsychology, 22(3-4), 455-479.
  • Frances, R. (1976). Comparative effects of six collative variables on interest and preference in adults of different educational levels. Journal of Personality and Social Psychology, 33(1), 62-79.
  • Forte, A., & Guzdial, M. (2005). Motivation and nonmajors in computer science: identifying discrete audiences for introductory courses. Education, IEEE Transactions on, 48(2), 248-253.
  • Fischbein, E. (1987). Intuition in science and mathematics. Dordrecht, Holland: D. Reidel.
  • Estey, A., Long, J., Gooch, B., & Gooch, A. A. (2010). Investigating studio-based learning in a course on game design. In Proceedings of the Fifth International Conference on the Foundations of Digital Games (pp. 64–71). Monterey, CA: ACM.
  • Entwistle, N. (1988). Motivational factors in students’ approaches to learning. In Learning strategies and learning styles (pp. 21-51). Springer US.
  • Ekman, P. (1992). An argument for basic emotions. Cognition & emotion, 6(3-4), 169-200.
  • Eisenman, R. (1966). Pleasing and interesting visual complexity: Support for Berlyne. Perceptual and motor skills, 23(3), 1167-1170.
  • Eggen, P., & Schellenberg, S. (2010). Human memory and the new science of learning. In New Science of Learning (pp. 79-107). Springer New York.
  • Ebbinghaus, H. (1885). Memory: A contribution to experimental psychology. New York Teachers College, Columbia University
  • Dubois, D. D. (1993). Competency-Based Performance Improvement: A Strategy for Organizational Change. HRD Press, Inc., 22 Amherst Road, Amherst, MA 01002.
  • Dreyfus, H. L., & Dreyfus, S. E. (1999). The challenge of Merleau-Ponty's phenomenology of embodiment for cognitive science. In G. Weiss & H. F. Haber (Eds.), Perspectives on embodiment: The intersections of nature and culture (pp. 103-120). New York: Routledg
  • Docherty, M., Sutton, P., Brereton, M., Kaplan, S., & Brown, A. (2000). The information environments program: A new design based IT degree. SIGCSE Bulletin, 33(1), 233–237. doi:http://doi.acm.org/10.1145/359369.359379
  • Dewey, J. (1958). Experience and nature (Vol. 1). Courier Corporation.
  • Dewey, J. (1913). Interest and effort in education. Boston: Riverside.
  • Cuff, D. (1992). Architecture: The story of practice. Mit Press.
  • Computational Thinking 능력 향상을 위한 로봇프로그래 밍 교수 학습 모형. 박사학위논문
    이은경 한국교원대학교 [2009]
  • Cobb, P., Yackel, E., & Wood, T. (1992). A constructivist alternative to the representational view of mind in mathematics education. Journal for Research in Mathematics education, 2-33.
  • Chomsky, N. (1959). A review of BF Skinner's Verbal Behavior. Language, 35(1), 26-58.
  • Chi, M. T. H., P.J. Feltovich, and R. Glaser. 1981. Categorization and representation of physics problems by experts and novices. Cognitive Science 5(2), 121–152.
  • Bransford J., T. Hasselbring, B. Barron, S. Kulweicz, J. Littlefield, and L. Goin 1988 Uses of macro-contexts to facilitate mathematical thinking. pp. 125-147 in The Teaching and Assessing of Mathematical Problem Solving, R.I. Charles and E.A. Silver, eds. Hillsdale, NJ: Erlbaum.
  • Bragg, B. W. E., & Crozier, J. B. (1974). The development with age of verbal and exploratory responses to sound sequences varying in uncertainty level. Studies in the new experimental aesthetics, 91-108.
  • Berlyne, D. E. (1967). Arousal and reinforcement. In Nebraska symposium on motivation, 15, 1-110
  • Berlyne, D. E. (1963). Complexity and incongruity variables as determinants of exploratory choice and evaluative ratings. Canadian Journal of Psychology, 17(3), 274-290.
  • Beck, I. L., McKeown, M. G., Sinatra, G. M., & Loxterman, J. A. (1991). Revising social studies text from a text-processing perspective: Evidence of improved comprehensibility. Reading Research Quarterly, 251-276.
  • Banzi, M. (2011). Getting Started with Arduino (2nd Edition). O’Reilly Media / Make, Sebastopol, CA.
  • Bamberger, J., & diSessa, A. A. (2003). Music as embodied mathematics: a study of a mutually informing affinity. International Journal of Computers for Mathematical Learning, 8(2),123-160.
  • Atkinson, R, & Shiffrin, R (1968). Humanmemory: A proposed system and its control processes. In K; Spence & J. Spence (Eds.), The psychology of learning and motivation: Advances in research and theory (Vol. 2). San Diego, CA: Academic Press.
  • Asher, S. R. (1980). Topic interest and children's reading comprehension. Theoretical issues in reading comprehension, 525-534.
  • Anderson, R. C. (1982). Allocation of attention during reading. In A. Flammer & W. Kinstsch(Eds.), Dicourse processing (292-305). Amsterdam: North Holland.
  • Anderson, R. (2005). Cognitive psychology and its implications (6th ed.). New York: Worth.
  • Aitken, P. P. (1974). Judgments of pleasingness and interestingness as functions of visual complexity. Journal of Experimental Psychology, 103(2), 240-244.
  • Ainley, M., Hidi, S., & Berndorff, D. (2002). Interest, learning, and the psychological processes that mediate their relationship. Journal of educational psychology, 94(3), 545-561.
  • Abrahamson, D., & Lindgren, R. (2014). Embodiment and embodied design. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (2nd Edition) (pp. 358-376). Cambridge, UK: Cambridge University Press.
  • Abrahamson, D. (2009). Embodied design: constructing means for constructing meaning. Educational Studies in Mathematics, 70(1), 27-47.
  • ARCS 전략을 적용한 구성주의적 수업이 과학개념 획득과 동기유발에 미치는 효과
    박수경 부산대학교 대학원 박사학위 논문 [1998]