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NTIS 바로가기한국과학교육학회지 = Journal of the Korean association for science education, v.38 no.2, 2018년, pp.161 - 170
Various forms of visual representations enable scientific discovery and scientific reasoning when scientists conduct research. Similarly, in science education, visual representations are important as a means to promote students' understanding of science concepts and scientific thinking skills. To pr...
핵심어 | 질문 | 논문에서 추출한 답변 |
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시각적 표상이 하는 역할은? | 오늘날 컴퓨터와 각종 테크놀로지의 발전으로 과학에서 더욱 다양한 시각적 표상을 이용하는 것이 가능해 졌고 이전에 불가능했던 시각적 정보들을 활용하게 되었다(전자현미경 사진이나 위성사진 등). 시각적 표상은 눈으로 관찰할 수 없는 거시적 혹은 미시적 현상을 보여주고, 과학 개념을 시각적으로 번역하여 나타내기도 하며(소리, 에너지 다이어그램 등), 실험이나 관찰 데이터를 조직하여 나타내기도 한다(표나 그래프 등). 과학 활동에서 시각적 표상은 문제해결을 돕고, 지식 구성이나 전달을 도울 수 있다(Lynch, 2006). | |
과학교육에서 시각적 표상은 어떻게 사용되는가? | 유사하게 과학교육에서도 다양한 시각적 표상이 활용되며 시각적 표상은 과학 개념을 가르치거나 이해하기 위한 수단으로, 또 학생의 과학적 사고를 촉진하고, 탐구 능력을 증진시키기 위한 도구로 사용될 수 있다. 시각적 표상의 활용과 관련된 과학교육 선행 연구를 살펴보면 과학 교과서에 제시된 시각적 표상의 유형 구분 및 사용과 관련된 연구(Dimopoulos, Koulaidis, & Sklaveniti, 2003; Bungum 2008), 학생이 주어진 시각적 정보를 해석할 수 있는 능력에 대한 연구(Chittleborough & Treagust, 2007; Colin, Chauvet, & Viennot, 2002; Topsakal & Oversby, 2013), 과학 활동 과정에서 학생이 생성한 시각적 표상이나 모델의 특징에 대한 연구(Dori, Tal, & Tsaushu, 2003; Lehrer & Schauble 2012; Schwarz et al. | |
사진, 다이어그램, 그래프 등 다양한 유형의 시각적 표상이 하는 역할은? | 사진, 다이어그램, 그래프 등 다양한 유형의 시각적 표상은 과학자의 연구 과정에서 중요한 역할을 한다. 그것은 효과적인 의사소통 도구일 뿐만 아니라 과학적 발견과 과학적 추론을 가능하게 하는 사고의 도구이다. 대표적인 예로 영국의 과학자 패러데이는 자석 주변 철가루의 모양을 ‘역선’으로 나타냈는데 역선을 통한 그의 시각적 추론은 이후 전자기 연구와 ‘장 이론(field theory)’을 발달시키는 데 매우 중요한 역할을 했다(Evagorou, Erduran, & Mantyla, 2015; Gooding, 2006). |
Ainsworth, S., Prain, V., & Tytler, R. (2011). Drawing to learn in science. Science, 333(6046), 1096-1097.
Anderson, L. W., Krathwohl, D. R., Airiasian, W., Cruikshank, K. A., Mayer, R. E., Pintrich, P. R., Raths, J. & Wittrock, M. C. (2001). A taxonomy for learning, teaching and assessing: A revision of Bloom's Taxonomy of educational objectives: Abridged edition. New York: Longman.
Bloom, B. S. (1956). Taxonomy of educational objectives. Handbook I: Cognitive Domain. New York: David McKay Company. Inc.
Bucat, B., & Mocerino, M. (2009). Learning at the sub-micro level: Structural representations. In Multiple representations in chemical education (pp. 11-29). Springer, Dordrecht.
Bungum, B. (2008). Images of physics: an explorative study of the changing character of visual images in Norwegian physics textbooks. Nordic Studies in Science Education, 4(2), 132-141.
Burton, L. (2004). Helping students become media literate. In Workshop's paper. Australian School Library Association (NSW) Inc. 5th State Conference.
Chittleborough, G., & Treagust, D. F. (2007). Correct interpretation of chemical diagrams requires transforming from one level of representation to another. Research in Science Education, 38(4), 463-482.
Churches, A. (2009). Bloom's digital taxonomy. Educational Origami, 4.
Colin, P., Chauvet, F., & Viennot, L. (2002). Reading images in optics: Students' difficulties and teachers' views. International Journal of Science Education, 24(3), 313-332.
Dimopoulos, K., Koulaidis, V., & Sklaveniti, S. (2003). Towards an analysis of visual images in school science textbooks and press articles about science and technology. Research in Science Education, 33(2), 189-216.
diSessa, A. A., & Sherin, B. L. (2000). Meta-representation: An introduction. The Journal of Mathematical Behavior, 19(4), 385-398.
Dori, Y. J., Tal, R.T., & Tsaushu, M. (2003). Teaching biotechnology through case studies: can we improve higher order thinking skills of nonscience majors? Science Education, 87(6), 767.793.
Evagorou, M., Erduran, S., & Mantyla, T. (2015). The role of visual representations in scientific practices: from conceptual understanding and knowledge generation to 'seeing' how science works. International Journal of STEM Education, 2(1), 11.
Gilbert, J. K., & Treagust, D. F. (2009). Towards a coherent model for macro, submicro and symbolic representations in chemical education. In Multiple representations in chemical education (pp. 333-350). Springer, Dordrecht.
Gooding, D. (2006). From phenomenology to field theory: Faraday’s visual reasoning. Perspectives on Science, 14(1), 40-65.
Hauenstein, A. D. (1998). A conceptual framework for educational objectives. University Press of America, Inc.
Jho, H., Jo, K., & Yoon, H.-G. (2017). Analysis of middle school students’ visual representation competences for electric current. New Physics: Sae Mulli, 67(6), 714-724.
Jo, K., Jho, H., & Yoon, H.-G. (2015) Analysis of visual representations related to electromagnetism in primary and secondary science textbooks. New Physics: Sae Mulli, 65(4), 343-357.
Johnstone, A. H. (1993). The development of chemistry teaching: A changing response to changing demand. Journal of Chemical Education, 70(9), 701.
Kim, O.-N. (2006). The comparative analysis of educational taxonomies in cognitive domain. The Korea Educational Review, 12(2), 165-189.
Kim, T.-S., & Kim, B.-K. (2002). The comparison of graphing abilities of pupils in grades 7 to 12 based on TOGS (The test of graphing in science). Journal of the Korean Association for Science Education, 22(4), 768-778.
Klopfer, L. E. (1971). Evaluation of learning in science. In B. S. Bloom, J. T. Hastings & G. F. Madaus (Eds.), Handbook on formative and summative evaluation of student learning. New York: MaGraw-Hill.
Kozma, R., & Russell, J. (2005). Students becoming chemists: Developing representational competence. In J. K. Gilbert (Ed.), Visualizations in Science Education (pp. 121-146). Dordrecht, The Netherlands: Springer.
Lee, J. (2011). Revisiting graphicacy: The roles of graphicacy in the digital era and tasks of geographic education. The Journal of the Korean Association of Geographic and Environmental Education, 19(1), 1-15.
Lehrer, R., & Schauble, L. (2000). Developing model-based reasoning in mathematics and science. Journal of Applied Developmental Psychology, 21(1), 39-48.
Lynch, M. (2006). The production of scientific images: vision and re-vision in the history, philosophy, and sociology of science. In L Pauwels (Ed.), Visual cultures of science: rethinking representational practices in knowledge building and science communication (pp. 26-40). Lebanon, NH: Darthmouth College Press.
Marzano, R. J. (2001). Designing a new taxonomy of educational objectives. Corwin Press, Inc.
Mayer, R. E. (2003). The promise of multimedia learning: using the same instructional design methods across different media. Learning and instruction, 13(2), 125-139.
McKenzie, D. L., & Padilla, M. J. (1986). The construction and validation of the test of graphing in science (TOGS). Journal of Research in Science Teaching, 23(7), 571-579.
Mnguni, L. E. (2014). The theoretical cognitive process of visualization for science education. SpringerPlus, 3(1), 184.
Moline, S. (1995). I see what you mean: Children at work with visual information. Teachers Pub Group Inc.
Nitz, S., Ainsworth, S., Nerdel, C., & Prechtl, H. (2014). Do student perceptions of teaching predict the development of representational competence and biological knowledge? Learning & Instruction, 31, 13-22.
Ozcelik, A. T., & McDonald, S. P. (2013). Preservice science teachers’ uses of inscriptions in science teaching. Journal of Science Teacher Education, 24(7), 1103-1132.
Paivio, A. (1991). Dual coding theory: Retrospect and current status. Canadian journal of psychology, 45(3), 255-287.
Park, S., Kim, H., & Lee E.-H. (2014). An Analysis of students’ graphicacy in Korea based on the national assessment of educational achievement, from 2005 to 2007. Journal of the Korean Geographical Society, 44(3), 410-427.
Postigo, Y., & Pozo, J. I. (2004). On the road to graphicacy: The learning of graphical representation systems. Educational Psychology, 24(5), 623-644.
Schwarz, CV, Reiser, BJ, Davis, EA, Kenyon, L, Acher, A, Fortus, D, et al. (2009). Developing a learning progression for scientific modeling: making scientific modeling accessible and meaningful for learners. Journal of Research in Science Teaching, 46(6), 632-654. doi:10.1002/tea.20311.
Talanquer, V. (2011). Macro, submicro, and symbolic: the many faces of the chemistry "triplet". International Journal of Science Education, 33(2), 179-195.
Tippett, C. D. (2016) What recent research on diagrams suggests about learning with rather than learning from visual representations in science, International Journal of Science Education, 38(5), 725-746.
Topsakal, U. U., & Oversby, J. (2013). What do scientist and non-scientist teachers notice about biology diagrams? Journal of Biological Education, 47(1), 21-28.
Waldrip, B., Prain, V., & Carolan, J. (2010). Using multi-modal representations to improve learning in junior secondary science. Research in Science Education, 40(1), 65-80.
Yoon, H.-G. Jo, K., & Jho, H. (2016). Middle school students’ interpretation, construction, and application of visual representations for electrostatic induction. New Physics: Sae Mulli, 66(5), 580-589.
Yoon, H.-G., Jo, K., & Jho, H. (2017). Secondary teachers’ perception about and actual use of visual representations in the teaching of electromagnetism. Journal of the Korean Association for Science Education, 37(2), 253-262.
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