Instructional Science

, Volume 46, Issue 5, pp 639–680 | Cite as

Recurring patterns in the development of high school biology students’ system thinking over time

  • Jaklin Tripto
  • Orit Ben Zvi AssarafEmail author
  • Miriam Amit


The goal of this study was to identify and understand the mental models developed by 67 high school biology students as they learn about the human body as a complex system. Using concept maps, it sought to find an external way of representing how students organize their ideas about the human body system in their minds. We conducted a qualitative analysis of four concept maps created by each student throughout the 3-year learning process, which allowed us to identify that student’s systems thinking skills and the development of those skills over time. The improvement trajectories of the students were defined according to three central characteristics of complex systems: (a) hierarchy, (b) homeostasis and (c) dynamism. A comparative analysis of all of our students’ individual trajectories together revealed four typical learning patterns, each of which reflects a different form of development for systems thinking: “from the structure to the process level”, “from macro to micro level”, “from the cellular level to the organism level,” and “development in complexity of homeostasis mechanisms”. Despite their differences, each of these models developed over time from simpler structures, which evolved as they connected with more complex system aspects, and each indicates advancement in the student’s systems thinking.


High school biology Complex systems Systems thinking 



This research was supported by the ISRAELI SCIENCE FOUNDATION Research Grant Application no. 718/11.


  1. Alonzo, A. C., & Steedle, J. T. (2009). Developing and assessing a force and motion learning progression. Science Education, 93, 389–421. Scholar
  2. Ausubel, D. P. (1968). Educational psychology: A cognitive view. New York: Holt, Rinehart & Winston.Google Scholar
  3. Ausubel, D., Novak, J., & Hanesian, H. (1978). Educational psychology: A cognitive view (2nd ed.). New York: Rinehart & Winston.Google Scholar
  4. Ben-Zvi Assaraf, O., Dodick. J., & Tripto, J. (2013). High school students' understanding of the Human Body System. Research in Science Education, 43(1), 33–56.CrossRefGoogle Scholar
  5. Ben-Zvi Assaraf, O., & Orion, N. (2005). Development of system thinking skills in the context of Earth System education. Journal of Research in Science Teaching, 42(5), 518–560.CrossRefGoogle Scholar
  6. Ben-Zvi Assaraf, O., & Orion, N. (2010). Four case studies, six years later: Developing system thinking skills in junior high school and sustaining them over time. Journal of Research in Science Teaching, 47(10), 1253–1280.CrossRefGoogle Scholar
  7. Boersma, K., Waarlo, A. J., & Klaassen, K. (2011). The feasibility of systems thinking in biology education. Journal of Biological Education, 45(4), 190–197.CrossRefGoogle Scholar
  8. Bray-Speth, E., Shaw, N., Momsen, J., Reinagel, A., Le, P., Taqieddin, R., et al. (2014). Introductory biology students’ conceptual models and explanations of the origin of variation. CBE-Life Sciences Education, 13(3), 529–539.CrossRefGoogle Scholar
  9. Buckley, B. C., & Boulter, C. J. (2000). Investigating the role of representations and expressed models in building mental models. In J. K. Gilbert & C. Boulter (Eds.), Developing models in science education (pp. 105–122). Dordrecht: Kluwer.Google Scholar
  10. Chang, S. N. (2007). Externalising students’ mental models through concept maps. Journal of Biological Education, 41(3), 107–112. Scholar
  11. Chang, S. N., & Chiu, M. H. (2004). Probing students’ conceptions concerning homeostasis of blood sugar via concept mapping. In Proceedings of the annual meeting of the national association for Research in Science Teaching (pp. 1–4). Vancouver/Canada.Google Scholar
  12. Chase, S. E. (2005). Narrative inquiry: Multiple lenses, approaches, voices. In N. K. Denzin & Y. Lincoln (Eds.), The Sage handbook of qualitative research (3rd ed., pp. 651–679). Thousand Oaks, CA: Sage.Google Scholar
  13. Chi, M. T. H., De Leew, N., Chiu, M.-H., & Lavancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18(3), 439–477.Google Scholar
  14. Clandinin, D. J., & Connelly, F. M. (2000). Narrative inquiry: Experience and story in qualitative research. San Francisco: Jossey-Bass.Google Scholar
  15. Creswell, J. W. (2007). Qualitative inquiry and research design: Choosing among five approaches. CA: Sage.Google Scholar
  16. Dauer, J. T., & Long, T. M. (2015). Long-term conceptual retrieval by college biology majors following model-based instruction. Journal of Research in Science Teaching, 52, 1188–1206. Scholar
  17. Dauer, J. T., Momsen, J. L., Speth, E. B., Makohon-Moore, S. C., & Long, T. M. (2013). Analyzing change in students’ gene-to-evolution models in college-level introductory biology. Journal of Research in Science Teaching, 5(6), 639–659.CrossRefGoogle Scholar
  18. Duncan, R. G., & Reiser, B. J. (2007). Reasoning across ontologically distinct levels: Students’ understandings of molecular genetics. Journal of Research in Science Teaching, 44(7), 938–959. Scholar
  19. Evagorou, M., Korfiatis, K., Nicolaou, C., & Constantinou, C. (2009). An investigation of the potential of interactive simulations for developing system thinking skills in elementary school: A case study with fifth-graders and sixth-graders. International Journal of Science Education, 31(5), 655–674. Scholar
  20. Goel, A., Rugaber, S., & Vattam, S. (2009). Structure, behavior & function of complex systems: The SBF modeling language. International Journal of AI in Engineering Design, Analysis and Manufacturing, 23, 23–35. Scholar
  21. Goldstone, R. L., & Wilensky, U. (2008). Promoting transfer by grounding complex systems principles. Journal of the Learning Sciences, 17(4), 465–516. Scholar
  22. Hay, D. B. (2007). Using concept maps to measure deep, surface and non-learning outcomes. Studies in Higher Education, 32(1), 39–57.CrossRefGoogle Scholar
  23. Hay, D. B., Kinchin, I. M., & Lygo-Baker, S. (2008). Making learning visible: The role of concept mapping in higher education. Studies in Higher Education., 33(3), 295–311.CrossRefGoogle Scholar
  24. Henige, K. (2012). Use of concept mapping in an undergraduate introductory exercisephysiology course. Advances in Physiology Education, 36(3), 197–206. Scholar
  25. Hmelo-Silver, C. E., & Azevedo, R. A. (2006). Understanding complex systems: Some core challenges. Journal of the Learning Sciences, 15, 53–61.CrossRefGoogle Scholar
  26. Hmelo-Silver, C. E., Holton, D. L., & Kolodner, J. L. (2000). Designing learning about complex systems. Journal of the learning Science, 9(3), 247–298. Scholar
  27. Hmelo-Silver, C. E., Jordan, R., Eberbach, C., & Goel, A. (2011). Systems and cycles: Learning about aquatic ecosystems. Society for Research on Educational Effectiveness. Resource document
  28. Hmelo-Silver, C. E., Jordan, R., Eberbach, C., & Sinha, S. (2017). Systems learning with a conceptual representation: a quasi-experimental study. Instructional Science, 45(1), 53–72. Scholar
  29. Hmelo-Silver, C. E., Marathe, S., & Liu, L. (2007). Fish swim, rocks sit, and lungs breathe: Expert-novice understanding of complex systems. Journal of the Learning Sciences, 16(3), 307–331.CrossRefGoogle Scholar
  30. Hmelo-Silver, C. E., & Pfeffer, M. G. (2004). Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions. Cognitive Science, 28, 127–138.CrossRefGoogle Scholar
  31. Hung, P. H., Hwang, G. J., Su, I. H., & I-Hua, L. (2012). A concept-map integrated dynamic assessment system for improving ecology observation competences in mobile learning activities. The Turkish Online. Journal of Educational Technology (TOJET), 11(1), 10–19.Google Scholar
  32. Ifenthaler, D. (2010). Relational, structural, and semantic analysis of graphical representations and concept maps. Educational Technology Research and Development, 58(1), 81–97.CrossRefGoogle Scholar
  33. Ifenthaler, D., Masduki, I., & Seel, N. M. (2011). The mystery of cognitive structure and how we can detect it: Tracking the development of cognitive structures over time. International Science, 39, 41–61. Scholar
  34. Israeli Ministry of Education. (2015). Curriculum in biology in high school (10th–12th grades). State of Israel Ministry of Education Curriculum Center (2015). Retrieved from:
  35. Jacobson, M. (2001). Problem solving, cognition, and complex systems: Differences between experts and novices. Complexity, 6(3), 41–49.CrossRefGoogle Scholar
  36. Jacobson, M. J., Markauskaite, L., Portolese, A., Kapur, M., Lai, P. K., & Roberts, G. (2017). Designs for learning about climate change as a complex system. Learning and Instruction.Google Scholar
  37. Jacobson, M., & Wilensky, U. (2006). Complex systems in education: Scientific and educational importance and implications for the learning sciences. Journal of the Learning Sciences, 15(1), 11–34.CrossRefGoogle Scholar
  38. Johnson-Laird, P. N. (2001). Mental models and deduction. TRENDS in Cognitive Sciences, 5(10), 434–442.CrossRefGoogle Scholar
  39. Johnson-Laird, P. N. (2004). The history of mental models. In K. Manktelow & M. C. Chung (Eds.), Psychology of reasoning: Theoretical and historical perspectives (pp. 179–212). New York: Psychology Press.Google Scholar
  40. Jonassen, D., Beissner, K., & Yacci, M. (2013). Structural knowledge: Techniques for representing, conveying, and acquiring structural knowledge. Routledge.Google Scholar
  41. Jordan, R. C., Hmelo-Silver, C., Liu, L., & Gray, S. A. (2013). Fostering reasoning about complex systems: Using the aquarium to teach systems thinking. Applied Environmental Education & Communication, 12, 55–64. Scholar
  42. Kalinowski, S. T., Leonard, M. J., & Andrews, T. M. (2010). Nothing in evolution makes sense except in the light of DNA. CBE-Life Sciences Education, 9(2), 87–97.CrossRefGoogle Scholar
  43. Kinchin, I. M. (2001). Can a novice be viewed as an expert upside-down? School Science Review, 303(83), 91–95.Google Scholar
  44. Kinchin, I. M. (2011). Visualising knowledge structures in biology: Discipline, curriculum and student understanding. Journal of Biological Education, 45(4), 183–189. Scholar
  45. Kinchin, I. M., Hay, D. B., & Adams, A. (2000). How a qualitative approach to concept map analysis can be used to aid learning by illustrating patterns of conceptual development. Educational Research, 42(1), 43–57. Scholar
  46. Knippels, M. C. P. J. (2002). Coping with the abstract and complex nature of genetics in biology education: The yoyo teaching and learning Strategy. PhD Dissertation, Proefschrift Universiteit Utrecht. Retrieved from
  47. Lin, C.-Y., & Hu, R. (2003). Students’ understanding of energy flow and matter cycling in the context of the food chain, photosynthesis, and respiration. Journal of Science Education, 25(12), 1529–1544. Scholar
  48. Liu, L., & Hmelo-Silver, C. E. (2009). Promoting complex systems learning through the use of conceptual representations in hypermedia. Journal of Research in Science Teaching, 46(9), 1023–1040. Scholar
  49. Long, T. M., Dauer, J. T., Kostelnik, K. M., Momsen, J. L., Wyse, S. A., Speth, E. B., et al. (2014). Fostering ecoliteracy through model-based instruction. Frontiers in Ecology and the Environment, 12(2), 138–139.CrossRefGoogle Scholar
  50. Mayer, R. E., & Anderson, R. B. (1991). Animations need narrations: An experimental test of a dual-coding hypothesis. Journal of Educational Psychology, 83(4), 484–490.CrossRefGoogle Scholar
  51. Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52.CrossRefGoogle Scholar
  52. Merriam, S. B. (2009). Qualitative research: A guide to design and implementation. San Francisco, CA: John Wiley & Sons.Google Scholar
  53. Mintzes, J. J., Wandersee, J. H., & Novak, J. D. (2000). Assessing science understanding: A human constructivist view. San Diego: Academic Press.Google Scholar
  54. National Research Council. (2007). Taking science to school. Washington, DC: The National Academies Press.Google Scholar
  55. National Research Council. (2010). Exploring the intersection of science education and 21st century skills: A workshop summary. National Academy Press.Google Scholar
  56. Nesbit, J. C., & Adesope, O. O. (2006). Learning with concept and knowledge maps: A meta-analysis. Review of Educational Research, 76(3), 413–448.CrossRefGoogle Scholar
  57. NGSS Lead States. (2013). Next generation science standards: For states, by states. Washington DC: National Academy Press.Google Scholar
  58. Novak, J. D. (1990). Concept maps and vee diagrams: Two metacognitive tools for science and mathematics education. Instructional Science, 19, 29–52.CrossRefGoogle Scholar
  59. Novak, J. D. (1993). How do we learn our lesson? Taking students throug the process. The Science Teacher, 3(60), 51–55.Google Scholar
  60. Novak, J. D., & Canas, A. J. (2007). Theoretical origins of concept maps, how to construct them, and uses in education. Reflecting Education, 3(1), 29–42.Google Scholar
  61. Novak, J. D., & Gowin, D. B. (1984). Learning how to learn. Cambridge University Press. Scholar
  62. Plate, R. (2010). Assessing individuals’ understanding of nonlinear causal structures in complex systems. System Dynamics Review, 26(1), 19–33.CrossRefGoogle Scholar
  63. Raved, L., & Yarden, A. (2014). Developing seventh grade students’ systems thinking skills in the context of the human circulatory system. Frontiers in Public Health, 2, 60. Scholar
  64. Reiner, M., & Eilam, B. (2001). Conceptual classroom environment-a system view of learning. International Journal of Science Education, 23(6), 551–568.CrossRefGoogle Scholar
  65. Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awarness; contemporary. Educational Psychology, 19, 460–475.Google Scholar
  66. Schroeder, N. L., Nesbit, J. C., Anguiano, C. J., & Adesope, O. O. (2017). Studying and constructing concept maps: A meta-analysis. Educational Psychology Review. Scholar
  67. Shavelson, R. J., Ruiz-Primo, M. A., & Wiley, E. W. (2005). Windows into the mind. Higher Education, 49(4), 413–430.CrossRefGoogle Scholar
  68. Shell, D. F., Brooks, D. W., Trainin, G., Wilson, K. M., Kauffman, D. F., & Herr, L. M. (2010). The unified learning model. Dordrecht: Springer.CrossRefGoogle Scholar
  69. Sommer, C., & Lücken, M. (2010). System competence—Are elementary students able to deal with a biological system? NorDiNaNordic Studies in Science Education, 6(2), 125–143. Resource document
  70. Tripto, J., Ben-Zvi Assaraf, O., Snapir, Z., & Amit, M. (2016). A Reflection Interview - "What is a system" as a knowledge integration activity for high school students' understanding of complex systems in human biology. International Journal of Science Education, 38(4), 564–595.CrossRefGoogle Scholar
  71. Tripto, J., Ben-Zvi Assaraf, O., Snapir, Z., & Amit, M. (2017). How does the body’s systemic nature manifested amongst high school biology students? Instructional Science: Special Issue Proposal Models and Tools for Systems Learning and Instruction, 45, 73–98.CrossRefGoogle Scholar
  72. Tsui, C.-Y., & Treagust, D. F. (2013). Introduction to multiple representations: Their importance in Biology and Biological Education. In D. Treagust & C.-Y. Tsui (Eds.), Multiple representations in biological education (p. 7). New York: Springer.Google Scholar
  73. Vattam, S. S., Goel, A. K., Rugaber, S., Hmelo-Silver, C. E., Jordan, R., Gray, S., et al. (2011). Understanding complex natural systems by articulating structure-behavior-function models. Educational Technology & Society, 14(1), 66–81.Google Scholar
  74. Verhoeff, R. P., Waarlo, A. J., & Boersma, K. T. (2008). Systems modelling and the development of coherent understanding of cell biology. International Journal of Science Education, 30(4), 543–568. Scholar
  75. Wilensky, U., & Resnick, M. (1999). Thinking in levels: A dynamic systems approach to making sense of the world. Journal of Science Education and Technology, 8(1), 3–19.CrossRefGoogle Scholar
  76. Wilson, C. D., Anderson, C. W., Heidemann, M., Merrill, J. E., Merritt, B. W., Richmond, G., et al. (2006). Assessing students’ ability to trace matter in dynamic systems in cell biology. Life Science Education., 5, 323–331. Scholar
  77. Wu, P. H., Hwang, G. J., Milrad, M., Ke, H. R., & Huang, Y. M. (2012). An innovative concept map approach for improving students’ learning performance with an instant feedback mechanism. Journal of Educational Technology, 43(2), 217–232.CrossRefGoogle Scholar
  78. Yoon, S. A., Anderson, E., Koehler-Yom, J., Evans, C., Park, M., Sheldon, J., et al. (2016). Teaching about complex systems is no simple matter: Building effective professional development for computer-supported complex systems instruction. Instructional Science, 45(1), 99–121. Scholar
  79. Zion, M., & Klein, S. (2015). Conceptual understanding of homeostasis. International Journal of Biology Education, 4(1), 1–27.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Science and Technology EducationBen Gurion University of the NegevBeer ShevaIsrael

Personalised recommendations