Research Article

Turkish and American science teachers’ perceptions about science models and modelling

Kathy L. Malone 1 2 * , Özkan Yılmaz 3
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1 University of Hawai’i at Hilo, Hilo, HI, USA2 Nazarbayev University, Astana, KAZAKHSTAN3 Erzincan Binali Yildirim University, Erzincan, TURKEY* Corresponding Author
Eurasian Journal of Science and Environmental Education, 3(1), June 2023, 33-42, https://doi.org/10.30935/ejsee/13065
Published: 12 March 2023
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ABSTRACT

The need for authentic practices such as science modelling in school science has been shown through international assessment scores. Numbers of studies have shown the efficacy of the use of modelling on students’ conceptual knowledge and reasoning abilities. However, the international assessment scores have not risen greatly in most countries. Thus, the question becomes are students being taught modelling practices in schools. Research implies that teachers, both pre- and in-service, may lack the expertise to guide students in the usage of models and modelling. This study compares the perceptions of models and modelling in two countries, the US and Turkey, using a qualitative interview research design to determine what differences exist between teachers’ perceptions in these two countries since the US scores higher than Turkey on international assessments. The results show that there are few differences in teachers’ perceptions of models and modelling between these two countries. The paper concludes with suggestions that are pertinent to science educators in terms of training needs for both pre- and in-service science teachers.

CITATION (APA)

Malone, K. L., & Yılmaz, Ö. (2023). Turkish and American science teachers’ perceptions about science models and modelling. Eurasian Journal of Science and Environmental Education, 3(1), 33-42. https://doi.org/10.30935/ejsee/13065

REFERENCES

  1. Ainsworth, S., Prain, V., & Tytler, R. (2011). Drawing to learn in science. Science, 333(6046), 1096-1097. https://doi.org/10.1126/science.1204153
  2. Bahtaji, M. A. A. (2023). Pre-service science teachers’ emphases and views about science education curriculum. International Journal of Instruction, 16(1), 919-932. https://doi.org/10.29333/iji.2023.16151a
  3. Berber, N. C., & Guzel, H. (2009). Fen ve matematik öğretmen adaylarının modellerin bilim ve fendeki rolüne ve amacına ilişkin algıları [Science and mathematics teacher candidates’ perceptions of the role and purpose of models in science and science]. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi [Selcuk University Journal of Social Sciences Institute], 21, 87-97.
  4. Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121-152. https://doi.org/10.1207/s15516709cog0502_2
  5. de Jong, T., Ainsworth S., Dobson M., van der Hulst A., Levonen J., & Reimann P. (1998). Acquiring knowledge in science and mathematics: The use of multiple representations in technology-based learning environments. In M. W. van Someren, P. Reimann, H. P. A. Boshuizen, & T. de Jong (Eds.), Learning with multiple representations (pp. 9-40). Elsevier.
  6. Dori, Y. J., & Kaberman, Z. (2012). Assessing high school chemistry students’ modeling sub-skills in a computerized molecular modeling learning environment. Instructional Science, 40, 69-91. https://doi.org/10.1007/s11251-011-9172-7
  7. Dori, Y. J., & Belcher, J. (2005). Learning electromagnetism with visualizations and active learning. In J. K. Gilbert (Ed.), Visualization in science education (pp. 198-216). Springer. https://doi.org/10.1007/1-4020-3613-2_11
  8. Dukerich, L. (2015). Applying modeling instruction to high school chemistry to improve students’ conceptual understanding. Journal of Chemical Education, 92(8), 1315-1319. https://doi.org/10.1021/ed500909w
  9. Eymur, G., & Capps, D. K. (2022). A model-based approach to teaching about solutions. Science Activities, 59(3), 135-141. https://doi.org/10.1080/00368121.2022.2071814
  10. Giere, R. N. (2004). How models are used to represent reality. Philosophy of Science, 71, 742-752. https://doi.org/10.1086/425063
  11. Gilbert, J. K. (2004). Models and modelling: Routes to more authentic science education. International Journal of Science and Mathematics Education, 2(2), 115-130. https://doi.org/10.1007/s10763-004-3186-4
  12. Gilbert, J. K., & Justi, R. (2016). Modelling-based teaching in science education. Springer. https://doi.org/10.1007/978-3-319-29039-3
  13. Gilbert, J. K., & Treagust, D. F. (2009). Towards a coherent model for macro, submicro and symbolic representations in chemical education. In J. K. Gilbert, & D. Treagust (Eds.), Multiple representations in chemical education (pp. 333-350). Springer. https://doi.org/10.1007/978-1-4020-8872-8_15
  14. Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine Pub. Co. https://doi.org/10.1097/00006199-196807000-00014
  15. Göhner, M. F., Bielik, T., & Krell, M. (2022). Investigating the dimensions of modeling competence among preservice science teachers: Meta‐modeling knowledge, modeling practice, and modeling product. Journal of Research in Science Teaching, 59(8), 1354-1387. https://doi.org/10.1002/tea.21759
  16. Göhner, M., & Krell, M. (2020). Preservice science teachers’ strategies in scientific reasoning: The case of modeling. Research in Science Education, 52, 395-414. https://doi.org/10.1007/s11165-020-09945-7
  17. Gunes, B., Gulcicek, C., & Bagci, N. (2004). Eğitim fakültelerindeki fen ve matematik öğretim elemanlarının model ve modelleme hakkındaki görüşlerinin incelenmesi [Examining the views of science and mathematics instructors in education faculties about modeling and modelling.]. Türk Fen Eğitimi Dergisi [Turkish Journal of Science Education], 1(1), 35-48.
  18. Harbour, K. E., Evanovich, L. L., Sweigart, C. A., & Hughes, L. E. (2015). A brief review of effective teaching practices that maximize student engagement. Preventing School Failure: Alternative Education for Children and Youth, 59(1), 5-13. https://doi.org/10.1080/1045988X.2014.919136
  19. Harman, G. (2012). Fen bilgisi öğretmen adaylarinin model ve modelleme ile ilgili bilgilerinin incelenmesi [Examination of pre-service science teachers’ knowledge about modeling and modelling]. In Proceedings of the 10th National Congress of Science and Mathematics Education.
  20. Harrison, A. G., & Treagust, D. F. (2000). Learning about atoms, molecules, and chemical bonds: A case study of multiple-model use in grade 11 chemistry. Science Education, 84, 352-381. https://doi.org/10.1002/(SICI)1098-237X(200005)84:3<352::AID-SCE3>3.0.CO;2-J
  21. Heijnes, D., van Joolingen, W., & Leenaars, F. (2018). Stimulating scientific reasoning with drawing-based modeling. Journal of Science Education and Technology, 27(1), 45-56. https://doi.org/10.1007/s10956-017-9707-z
  22. Henze, I., Van Driel, J., & Verloop, N. (2007). The change of science teachers’ personal knowledge about teaching models and modeling in the context of science education reform. International Journal of Science Education, 15(3), 1819-1846. https://doi.org/10.1080/09500690601052628
  23. Hestenes, D. (2010). Modeling theory for math and science education. In R. Lesh, C. R. Haines, P. L. Galbraith, & A. Harford (Eds.), Modeling students’ mathematical modeling competencies (pp. 13-41). Springer. https://doi.org/10.1007/978-1-4419-0561-1_3
  24. Hestenes, D., Wells, M., & Swackhamer, G. (1992). Force concept inventory. The Physics Teacher, 30, 141-158. https://doi.org/10.1119/1.2343497
  25. Isik, A., & Mercan, E. (2015). Ortaokul matematik öğretmenlerinin model ve modelleme hakkindaki görüşlerinin incelenmesi [Examination of secondary school mathematics teachers’ views on modeling and modelling]. Kastamonu Eğitim Dergisi [Kastamonu Journal of Education], 23(4), 1835-1850.
  26. Jackson, J., Dukerich, L., & Hestenes, D. (2008). Modeling instruction: An effective model for science education. Science Educator, 17(1), 10-17.
  27. Justi, R., & Gilbert, J. (2003). Teachers’ views on the nature of models. International Journal of Science Education, 25(11), 1369-1386. https://doi.org/10.1080/0950069032000070324
  28. Kozma, R. (2003). The material features of multiple representations and their cognitive and social affordances for science understanding. Learning and Instruction, 13, 205-226. https://doi.org/10.1016/S0959-4752(02)00021-X
  29. Krell, M., & Kruger, D. (2016). Testing models: A key aspect to promote teaching activities related to models and modelling in biology lessons? Journal of Biological Education, 50(2), 160-173. https://doi.org/10.1080/00219266.2015.1028570
  30. Liang, L. L., Fulmer, G. W., Majerich, D. M., Clevenstine. R., & Howanski, R. (2012). The effects of a model-based physics curriculum program with a physics first approach: A causal-comparative study. Journal of Science Education and Technology, 21(1), 114-124. https://doi.org/10.1007/s10956-011-9287-2
  31. Loughran, J., & Berry, A. (2005). Modelling by teacher educators. Teaching and Teacher Education, 21(2), 193-203. https://doi.org/10.1016/j.tate.2004.12.005
  32. Malone, K. L., Schuchardt, A. M., & Sabree, Z. (2019). Models and modeling in evolution. In U. Harms, & M. J. Reiss (Eds.), Evolution education re-considered: Understanding what works (pp. 207-226). Springer. https://doi.org/10.1007/978-3-030-14698-6_12
  33. Malone, K. L., & Schuchardt, A. (2020). Population growth modelling simulations: Do they affect the scientific reasoning abilities of students?. In Computer Supported Education: 11th International Conference, CSEDU 2019, Heraklion, Crete, Greece, May 2-4, 2019, Revised Selected Papers 11 (pp. 285-307). Springer International Publishing. https://doi.org/10.1007/978-3-030-58459-7_14
  34. McCullagh, P., Law, B., & Ste-Marie, D. (2012). Modeling and performance. In S. M. Murphy (Ed.), The Oxford handbook of sport and performance psychology (pp. 250-272). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199731763.013.0013
  35. Miller, A. R., & Kastens, K. A. (2017). Investigating the impacts of targeted professional development around models and modeling on teachers’ instructional practice and student learning. Journal of Research in Science Teaching, 55(5), 641-663. https://doi.org/10.1002/tea.21434
  36. Mullis, I. V. S., Martin, M. O., Goh, S., & Cotter, K. (Eds.) (2016). TIMSS 2015 encyclopedia: Education policy and curriculum in mathematics and science. Boston College. TIMSS & PIRLS International Study Center. http://timssandpirls.bc.edu/timss2015/encyclopedia/
  37. OECD. (2014). What are tertiary students choosing to study? Organization for Economic Co-operation and Development Publishing. http://www.oecd.org/education/skills-beyond-school/EDIF%202014--No19.pdf
  38. OECD. (2016). Low-performing students: Why they fall behind and how to help them succeed, PISA. OECD Publishing. https://doi.org/10.1787/9789264250246-en
  39. Passmore, C., & Stewart, J. (2002). A modeling approach to teaching evolutionary biology in high schools. Journal of Research in Science Teaching, 39(3), 185-204. https://doi.org/10.1002/tea.10020
  40. Quinn, H., Schweingruber, H., & Keller., T. (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. National Academies Press.
  41. Roslina, Andalia, N., AG, B., & Zulfajri, M. (2020). The student ability in graph understanding for mastering natural science concepts through the process skills approach. International Journal of Instruction, 13(4), 145-160. https://doi.org/10.29333/iji.2020.13410a
  42. Rost, M., & Knuuttila, T. (2022). Models as epistemic artifacts for scientific reasoning in science education research. Education Sciences, 12(4), 276. https://doi.org/10.3390/educsci12040276
  43. Saleh, S., & Jing, T. A. (2020). Instructional practices in science education in German and Malaysian secondary schools: A comparative case study. International Journal of Instruction, 13(4), 267-282. https://doi.org/10.29333/iji.2020.13417a
  44. Schleicher, A. (2019). PISA 2018: Insights and interpretations. OECD Publishing.
  45. Schuchardt, A., Malone, K., Diehl, W., Harless, K., McGinnis, R., & Parr, TD. (2008). A case study of student performance following a switch to a modeling-based physics first course sequence [Paper presentation]. 2008 Annual International Conference of the National Association for Research in Science Teaching, Baltimore, United States.
  46. Schuchardt, A., & Schunn, C. D. (2016). Modeling scientific processes with mathematics equations enhances student qualitative conceptual understanding and quantitative problem solving. Science Education, 100(2), 290-320. https://doi.org/10.1002/sce.21198
  47. Schwarz, C. V., & Gwekwerere, Y. N. (2007). Using a guided inquiry and modeling instructional framework (EIMA) to support preservice K‐8 science teaching. Science Education, 91(1), 158-186. https://doi.org/10.1002/sce.20177
  48. Schwarz, C. V., Reiser, B. J., Davis, E. A., Kenyon, L., Achér, A., Fortus, D., Shwartz, Y., Hug, B., & Krajcik, J. (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. https://doi.org/10.1002/tea.20311
  49. Svoboda, J., & Passmore, C. (2013). The strategies of modeling in biology education. Science & Education, 22(1), 119-142. https://doi.org/10.1007/s11191-011-9425-5
  50. Tsui, C. Y., & Treagust, D. F. (2003). Genetics reasoning with multiple external representations. Research in Science Education, 33(1), 111-135. https://doi.org/10.1023/A:1023685706290
  51. Tsui, C. Y., & Treagust, D. F. (2007). Understanding genetics: Analysis of secondary students’ conceptual status. Journal of Research in Science Teaching, 44(2), 205-235. https://doi.org/10.1002/tea.20116
  52. van Someren, M.W., Boshuizen, H. P. A., de Jong, T., & Reimann, P. (1998). Introduction. In M.W. van Someren, P. Reimann, H. P. A. Boshuizen, & T. de Jong (Eds.), Learning with multiple representations (pp. 1-5). Pergamon.
  53. Won, M., Yoon, H., & Treagust, D. F. (2014). Students’ learning strategies with multiple representations: Explanations of the human breathing mechanism. Science Education, 98(5), 840-866. https://doi.org/10.1002/sce.21128
  54. Yenilmez Turkoglu, A., & Oztekin, C. (2016). Science teacher candidates’ perceptions about roles and nature of scientific models. Research in Science & Technological Education, 34(2), 219-236. https://doi.org/10.1080/02635143.2015.1137893