Journal of The Korean Association For Science Education (한국과학교육학회지)

The Korean Association for Science Education (한국과학교육학회)
권호 표지
DOI QR코드

DOI QR Code

A Study on Middle School Students' Problem Solving Processes for Scientific Graph Construction

중학생의 과학 그래프 구성에 관한 문제 해결 과정 연구

  • Received : 2019.10.05
  • Accepted : 2019.10.30
  • Published : 2019.12.28
Download PDF
⟨ Previous Next ⟩

Abstract

In this study, we investigated the middle school students' processes of scientific graph construction from the perspective of the problem solving process. Ten 9th graders participated in this study. They constructed a scientific graph based on pictorial data depicting precipitation reaction. The think-aloud method was used in order to investigate their thinking processes deeply. Their activities were videotaped, and semi-structured interviews were also conducted. The analysis of the results revealed that their processes of scientific graph construction could be classified into four types according to the problem solving strategy and the level of representations utilized. Students using the structural strategy succeeded in constructing scientific graph regardless of the level of representation utilized, by analyzing the data and identifying the trend based on the propositional knowledge about the target concept of the graph. Students of random strategy-higher order representation type were able to succeed in constructing scientific graph by systematically analyzing the characteristics of the data using various representations, and considering the meaning of the graph constructed in terms of the scientific context. On the other hand, students of random strategy-lower order representation type failed to construct correct scientific graph by constructing graph in a way of simply connecting points, and checking the processes of graph construction only without considering the scientific context. On the bases of the results, effective methods for improving students' ability to construct scientific graphs are discussed.

이 연구에서는 중학생들의 과학 그래프 구성 과정을 문제 해결의 관점에서 심층적으로 조사하였다. 중학교 3학년 학생 10명이 연구에 참여하였으며, 이들은 앙금 생성 반응을 묘사한 그림 자료를 바탕으로 과학 그래프를 구성하였다. 학생들이 그래프를 구성할 때 거치는 사고 과정을 심층적으로 조사하기 위하여 발성사고법을 활용하였고, 그래프 구성 과정에 대한 녹화 및 반구조화된 면담을 실시하였다. 연구 결과, 학생들의 과학 그래프 구성 유형은 사용한 문제 해결 전략과 활용한 표상의 수준에 따라 네 가지 유형으로 구분할 수 있었다. 구조적 전략을 사용한 학생들은 그래프의 목표 개념에 대한 명제적 지식을 바탕으로 자료를 분석하고 경향성을 파악함으로써 활용한 표상의 수준과 무관하게 과학 그래프 구성에 성공하였다. 임의 전략-고차원 표상 유형의 학생들은 다양한 표상을 활용해 자료의 특징을 체계적으로 분석하고 자신이 구성한 그래프의 의미를 과학적 맥락에서 검토하는 과정을 거치며 과학 그래프 구성에 성공할 수 있었다. 반면, 임의전략-저차원 표상 유형의 학생들은 단순히 점을 연결하는 방식으로 그래프를 구성하였고, 과학적 맥락에 대한 고려 없이 그래프 구성 과정만을 점검하는 수준에 머물며 올바른 과학 그래프 구성에 실패하였다. 연구 결과를 바탕으로 학생들의 과학 그래프 구성 능력을 효과적으로 함양하는 방안을 제안하였다.

Keywords

References

  1. Atwater, M. M., & Alick, B. (1990). Cognitive development and problem solving of Afro-American students in chemistry. Journal of Research in Science Teaching, 27(2), 157-172. https://doi.org/10.1002/tea.3660270207
  2. Beaumont-Walters, Y., & Soyibo, K. (2001). An analysis of high school students' performance on five integrated science process skills. Research in Science & Technological Education, 19(2), 133-145. https://doi.org/10.1080/02635140120087687
  3. Beichner, R. J. (1994). Testing student interpretation of kinematics graphs. American Journal of Physics, 62(8), 750-762. https://doi.org/10.1119/1.17449
  4. Berg, C. A., & Smith, P. (1994). Assessing students' abilities to construct and interpret line graphs: Disparities between multiple-choice and freeresponse instruments. Science Education, 78(6), 527-554. https://doi.org/10.1002/sce.3730780602
  5. Bing, T. J., & Redish, E. F. (2006). The cognitive blending of math and physics knowledge. In Proceedings of the 2006 Physics Education Research Conference, Syracuse, NY, USA.
  6. Bing, T. J., & Redish, E. F. (2009). Analyzing problem solving using math in physics: Epistemological framing via warrants. Physical Review Special Topics-Physics Education Research, 5(2), 020108. https://doi.org/10.1103/PhysRevSTPER.5.020108
  7. Brasell, H. M. (1990). Graphs, graphing, and graphers. What Research Says to the Science Teacher, 6, 69-85.
  8. Byun, T. (2012). An understanding of students' physics problem solving processes by using house model. Doctoral dissertation, Seoul National University, Seoul.
  9. Canham, M., & Hegarty, M. (2010). Effects of knowledge and display design on comprehension of complex graphics. Learning and Instruction, 20 (2), 155-166. https://doi.org/10.1016/j.learninstruc.2009.02.014
  10. Chiu, M.-H. (2001). Algorithmic problem solving and conceptual understanding of chemistry by students at a local high school in Taiwan. Proceedings of the National Science Council, Republic of China Part D: Mathematics, Science and Technology Education, 11(1), 20-38.
  11. Cho, S. (1993). A comparison of students' responses to everyday and scientific context problems about the particulate nature of matter. Master's thesis, Seoul National University, Seoul.
  12. Choi, J., & Heo, H. (2013). A study on formation of the process-object perspective of function using excel to specialized high school math underachievers. The Korea Society of Educational Studies in Mathematics, 23(2), 213-235.
  13. Cooper, M. M., Grove, N., Underwood, S. M., & Klymkowsky, M. W. (2010). Lost in Lewis structures: An investigation of student difficulties in developing representational competence. Journal of Chemical Education, 87(8), 869-874. https://doi.org/10.1021/ed900004y
  14. Dori, Y. J., & Sasson, I. (2008). Chemical understanding and graphing skills in an honors case-based computerized chemistry laboratory environment: The value of bidirectional visual and textual representations. Journal of Research in Science Teaching, 45(2), 219-250. https://doi.org/10.1002/tea.20197
  15. Ferguson, L. E., Braten, I., & Stromso, H. I. (2012). Epistemic cognition when students read multiple documents containing conflicting scientific evidence: A think-aloud study. Learning and Instruction, 22(2), 103-120. https://doi.org/10.1016/j.learninstruc.2011.08.002
  16. Friel, S. N., Curcio, F. R., & Bright, G. W. (2001). Making sense of graphs: Critical factors influencing comprehension and instructional implications. Journal for Research in Mathematics Education, 32(2), 124-158. https://doi.org/10.2307/749671
  17. Gabel, D. L., Sherwood, R. D., & Enochs, L. (1984). Problem-solving skills of high school chemistry students. Journal of Research in Science Teaching, 21(2), 221-233. https://doi.org/10.1002/tea.3660210212
  18. Gultepe, N. (2016). Reflections on high school students' graphing skills and their conceptual understanding of drawing chemistry graphs. Educational Sciences: Theory and Practice, 16(1), 53-81.
  19. Hill, M., & Sharma, M. D. (2015). Students' representational fluency at university: A cross-sectional measure of how multiple representations are used by physics students using the representational fluency survey. Eurasia Journal of Mathematics, Science & Technology Education, 11(6), 1633-1655.
  20. Hipkins, R. (2011). Challenges with graph interpretation: A review of the literature. Studies in Science Education, 47(2), 183-210. https://doi.org/10.1080/03057267.2011.605307
  21. Hong, M. (1995). Influence of characteristics of problems and problem solvers on chemistry problem solving. Doctoral dissertation, Seoul National University, Seoul.
  22. Hong, M., & Park, Y. (1994). Analysis of characteristics of problem solving process in gas phase problems of college students. Journal of the Korean Association for Science Education, 14(2), 143-158.
  23. Hsu, L., Brewe, E., Foster, T. M., & Harper, K. A. (2004). Resource letter RPS-1: Research in problem solving. American Journal of Physics, 72(9), 1147-1156. https://doi.org/10.1119/1.1763175
  24. Ibrahim, B., & Rebello, N. S. (2012). Representational task formats and problem solving strategies in kinematics and work. Physical Review Special Topics-Physics Education Research, 8(1), 010126. https://doi.org/10.1103/PhysRevSTPER.8.010126
  25. Jeon, K. (1999). Problem solving strategy and paired think aloud problem solving: Instructional effect and small group problem solving process in chemistry class. Doctoral dissertation, Seoul National University, Seoul.
  26. 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.
  27. Kim, T. S., Ko, S. K., & Kim, B. K. (2005). Relationships of graphing ability to science-process skills and academic achievement of high school students. Journal of the Korean Association for Science Education, 25(5), 624-633.
  28. Kim, Y., Choi, G., & Noh, T. (2009). High school students' errors in constructing and interpreting science graph. Journal of the Korean Association for Science Education, 29(8), 978-989.
  29. Kim, Y., Moon, S., Kang, H., & Noh, T. (2009). Analysis of the types of errors in science graph construction processes of middle school students. Journal of the Korean Association for Science Education, 29(2), 168-178.
  30. Kohl, P. B., & Finkelstein, N. D. (2008). Patterns of multiple representation use by experts and novices during physics problem solving. Physical Review Special Topics-Physics Education Research, 4(1), 010111. https://doi.org/10.1103/PhysRevSTPER.4.010111
  31. Kwon, J., & Lee, S. (1988). A Comparative analysis of expert's and novice's thinking processes in solving physics problems. A Journal of the Korean Association for Science Education, 8(1), 43-55.
  32. Lapp, D. A., & Cyrus, V. F. (2000). Using data-collection devices to enhance students' understanding. Mathematics Teacher, 93(6), 504-510. https://doi.org/10.5951/MT.93.6.0504
  33. Larkin, J. H. (1978). Problem solving in physics: Structure, process, and learning. In J. M. Scandura & C. J. Brainerd (Eds.), Structural/process models of complex human behavior. (pp. 445-458). The Netherlands: Sijthoff & Noordhoff.
  34. Larkin, J. H. (1981). Cognition of learning physics. American Journal of Physics, 49(6), 534-541. https://doi.org/10.1119/1.12667
  35. Larkin, J. H., McDermott, J., Simon, D. P., & Simon, H. A. (1980). Models of competence in solving physics problems. Cognitive Science, 4(4), 317-345. https://doi.org/10.1016/S0364-0213(80)80008-5
  36. Lee, H., Ryu, H., & Chang, K. (2009). Investigation to teach graphical representations and their interpretations of functions to fifth graders. The Korea Society of Educational Studies in Mathematics, 11(1), 131-145.
  37. Lemke, J. (1998). Multimedia literacy demands of the scientific curriculum. Linguistics and Education, 10(3), 247-271. https://doi.org/10.1016/S0898-5898(99)00009-1
  38. Lim, H.-M., Kim, Y.-H., & Kim, Y.-S. (2010). Female high school students' ability to construct graphs in biology. The Korean Society of Biology Education, 38(2), 342-352.
  39. Madden, S. P., Jones, L. L., & Rahm, J. (2011). The role of multiple representations in the understanding of ideal gas problems. Chemistry Education Research and Practice, 12(3), 283-293. https://doi.org/10.1039/C1RP90035H
  40. 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. https://doi.org/10.1002/tea.3660230702
  41. Meredith, D. C., & Marrongelle, K. A. (2008). How students use mathematical resources in an electrostatics context. American Journal of Physics, 76(6), 570-578. https://doi.org/10.1119/1.2839558
  42. Noh, T., Jeon K., Han, I., & Kim, C. (1996). Comparison of chemistry problem solving behaviors in the aspects of cognitive developmental level of student and context of problem. Journal of the Korean Association for Science Education, 16(4), 389-400.
  43. Park, H.-K., & Kwon, J.-S. (1994). A study on students' thinking processes in solving physics problems. Journal of the Korean Association for Science Education, 14(1), 85-102.
  44. Park, J. (2018). Features of elementary students' intuitive thinking during the problem solving activities on thermal phenomena: Focusing on the processes of emergence and elaboration. Doctoral dissertation, Seoul National University, Seoul.
  45. Park, Y. (2002). Teaching and learning of physics problem solving[물리문제해결 학습과 지도]. In I. Kim, J. Park, K. Choi, J. Song & Y. Park (Eds.), General physics education II[물리교육학 총론 II]. (pp. 69-136). Seoul: Bookshill.
  46. Park, Y., & Cho, Y.-K. (2005). Analysis of physics problem solving processes of high school students to qualitative and quantitative problems. Journal of the Korean Association for Science Education, 25(4), 526-532.
  47. Ploetzner, R., Lippitsch, S., Galmbacher, M., Heuer, D., & Scherrer, S. (2009). Students' difficulties in learning from dynamic visualisations and how they may be overcome. Computers in Human Behavior, 25(1), 56-65. https://doi.org/10.1016/j.chb.2008.06.006
  48. Potgieter, M., Harding, A., & Engelbrecht, J. (2008). Transfer of algebraic and graphical thinking between mathematics and chemistry. Journal of Research in Science Teaching, 45(2), 197-218. https://doi.org/10.1002/tea.20208
  49. Rau, M. A. (2015). Enhancing undergraduate chemistry learning by helping students make connections among multiple graphical representations. The Royal Society of Chemistry, 16(3), 654-669.
  50. Secken, N., & Yoruk, N. Z. (2012). An analysis of relations between concerns about the use of graphs in chemistry classes and multiple intelligences in terms of different variables. International Journal of New Trends in Arts, Sports & Science Education, 1(2), 142-156.
  51. Tuminaro, J., & Redish, E. F. (2004). Understanding students' poor performance on mathematical problem solving in physics. In Proceedings of the 2004 Physics Education Research Conference, University of Maryland, MD, USA.
  52. Vermaat, H., Terlouw, C., Dijkstra, S., & Vermaat, J. H. (2003). Multiple representations in web-based learning of chemistry concepts. In Proceedings of the 84th Annual Meeting of the American Educational Research Association, San Francisco, CA, USA.
  53. Yang, S. J., & Jang, M. D. (2012). Analysis of children's constructing and interpreting of a line graph in science. Journal of Korean Elementary Science Education, 31(3), 321-333. https://doi.org/10.15267/KESES.2012.31.3.321
  54. Zoller, U., Dori, Y., & Lubezky, A. (2002). Algorithmic, LOCS and HOCS (chemistry) exam questions: Performance and attitudes of college students. International Journal of Science Education, 24(2), 185-203. https://doi.org/10.1080/09500690110049060