Characterising the development of the understanding of human body systems in high-school biology students – a longitudinal study

References

• Bar-Yam, Y. (1997). Dynamics of complex systems. Reading, MA: Addison-Wesley.
   Google Scholar
• Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441. doi: 10.1016/j.shpsc.2005.03.010
   PubMedGoogle Scholar
• Bell, H. (2006). Respiratory control at exercise onset: An integrated systems perspective. Respiratory Physiology & Neurobiology, 152, 1–15. doi: 10.1016/j.resp.2006.02.005
   PubMed Web of Science ®Google Scholar
• Ben-Zvi Assaraf, O., Dodick, J., & Tripto, J. (2013). High school students’ understanding of the human body system. Research in Science Education, 43, 33–56. doi: 10.1007/s11165-011-9245-2
   Web of Science ®Google Scholar
• 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. doi: 10.1002/tea.20061
   Web of Science ®Google Scholar
• 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. doi: 10.1002/tea.20383
   Web of Science ®Google Scholar
• Bencze, J. L., Bowen, G. M., & Alsop, S. (2006). Teachers’ tendencies to promote student-led science projects: Associations with their views about science. Science Education, 90, 400–419. doi: 10.1002/sce.20124
   Web of Science ®Google Scholar
• Bezzi, A. (1999). What is this thing called geoscience? Epistemological dimensions elicited with the repertory grid and their implications for scientific literacy. Science Education, 83, 675–700. doi: 10.1002/(SICI)1098-237X(199911)83:6<675::AID-SCE3>3.0.CO;2-Q
   Web of Science ®Google Scholar
• Bradshaw, J. M., Ford, K. M., Adams-Webber, J. R., & Boose, J. H. (1993). Beyond the repertory grid: New approaches to constructivist knowledge acquisition tool development. International Journal of Intelligent Systems, 8, 287–333.
   Web of Science ®Google Scholar
• Brown, M. H., & Schwartz, R. S. (2009). Connecting photosynthesis and cellular respiration: Preservice teachers’ conceptions. Journal of Research in Science Teaching, 46(7), 791–812. doi: 10.1002/tea.20287
   Web of Science ®Google Scholar
• Chasman, D., Siahpirani, A. F., & Roy, S. (2016). Network-based approaches for analysis of complex biological systems. Current Opinion in Biotechnology, 39, 157–166. doi: 10.1016/j.copbio.2016.04.007
   PubMed Web of Science ®Google Scholar
• Chi, M. T. (2005). Commonsense conceptions of emergent processes: Why some misconceptions are robust. Journal of the Learning Sciences, 14(2), 161–199. doi: 10.1207/s15327809jls1402_1
   Web of Science ®Google Scholar
• Creswell, J. W. (2007). Qualitative inquiry and research design: Choosing among five approaches. Thousand Oaks, CA: Sage.
   Google Scholar
• 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. doi: 10.1002/tea.20186
   Web of Science ®Google Scholar
• Edwards, H. M., McDonald, S., & Young, S. M. (2009). The repertory grid technique: Its place in empirical software engineering research. Information and Software Technology, 51, 785–798. doi: 10.1016/j.infsof.2008.08.008
   Web of Science ®Google Scholar
• Efran, J. S., McNamee, S., Warren, B., & Raskin, J. D. (2014). Personal construct psychology, radical constructivism, and social constructionism: A dialogue. Journal of Constructivist Psychology, 27(1), 1–13. doi: 10.1080/10720537.2014.850367
   Web of Science ®Google Scholar
• Fensham, P. J. (2012). Preparing citizens for a complex world: the grand challenge of teaching socio-scientific issues in science education. In Science environment health, (pp. 7–29). Netherlands: Springer.
   Google Scholar
• Fowler, S. R., & Zeidler, D. L. (2016). Lack of evolution acceptance inhibits students’ negotiation of biology-based socioscientific issues. Journal of Biological Education, 50(4), 407–424. doi: 10.1080/00219266.2016.1150869
   Web of Science ®Google Scholar
• Goel, A. K., Gomez de Silva Garza, A., Grue, N., Murdock, J. W., Recker, M. M., & Govinderaj, T. (1996). Towards design learning environments – I: Exploring how devices work. Intelligent Tutoring Systems. Lecture Notes in Computer Science, 1086, 493–501. doi: 10.1007/3-540-61327-7_148
   Google Scholar
• Goel, A. K., Rugaber, S., & Vattam, S. (2009). Structure, behavior & function of complex systems: The SBF modeling language. AI for Engineering Design, Analysis and Manufacturing, 23, 23–35. doi: 10.1017/S0890060409000080
   Web of Science ®Google Scholar
• Goldstone, R. L., & Wilensky, U. (2008). Promoting transfer by grounding complex systems principles. Journal of the Learning Sciences, 17(4), 465–516. doi: 10.1080/10508400802394898
   Web of Science ®Google Scholar
• Greenwald, E., Segre, E., & Feinerman, O. (2015). Ant trophallactic networks: Simultaneous measurement of interaction patterns and food dissemination. Scientific Reports, 5, 509. doi: https://www.nature.com/articles/srep12496. doi: 10.1038/srep12496
   Web of Science ®Google Scholar
• Hmelo-Silver, C. E., & Azevedo, R. (2006). Understanding complex systems: Some core challenges. Journal of the Learning Sciences, 15, 53–61. doi: 10.1207/s15327809jls1501_7
   Web of Science ®Google Scholar
• Hmelo-Silver, C. E., Holton, D. L., & Kolodner, J. L. (2000). Designing to learn about complex systems. Journal of the Learning Sciences, 9(1), 247–298. doi: 10.1207/S15327809JLS0903_2
   Web of Science ®Google Scholar
• Hmelo-Silver, C. E., Jordan, R., Eberbach, C., & Sinha, S. (2016). Systems learning with a conceptual representation: A quasi-experimental study. Instructional Science, 1–20. doi: 10.1007/s11251-016-9392-y
   Web of Science ®Google Scholar
• 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. doi: 10.1080/10508400701413401
   Web of Science ®Google Scholar
• Hmelo-Silver, C. E., & Pfeffer, G. M. (2004). Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions. Cognitive Science, 28, 127–138. doi:10.1016/S0364-0213(03)00065-X doi: 10.1207/s15516709cog2801_7
   Web of Science ®Google Scholar
• Hunter, M. G., & Beck, J. E. (2000). Using repertory grids to conduct cross-cultural information systems research. Information Systems Research, 11(1), 93–101. doi: 10.1287/isre.11.1.93.11786
   Web of Science ®Google Scholar
• Illari, P. M., & Williamson, J. (2012). What is a mechanism? Thinking about mechanisms across the sciences. European Journal for Philosophy of Science, 2(1), 119–135. doi: 10.1007/s13194-011-0038-2
   Web of Science ®Google Scholar
• Jacobson, M. J. (2001). Problem solving, cognition, and complex systems: Differences between experts and novices. Complexity, 6(3), 41–49. doi: 10.1002/cplx.1027
   Google Scholar
• 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, doi: 10.1016/j.learninstruc.2017.03.007
   PubMedGoogle Scholar
• Jacobson, M. J., & 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. doi: 10.1207/s15327809jls1501_4
   Web of Science ®Google Scholar
• Jankowicz, D. (2004). The easy guide to repertory grids. Chichester: Wiley.
   Google Scholar
• Jordan, R. C., Gray, S., Sorensen, A. E., Pasewark, S., Sinha, S., & Hmelo-Silver, C. E. (2017). Modeling with a conceptual representation: Is it necessary? Does it work? Frontiers in ICT, 4, 235. doi: 10.3389/fict.2017.00007
   Google Scholar
• Kelly, G. A. (1955). The psychology of personal constructs (Vol. 1). New York, NY: Norton and Co.
   Google Scholar
• Kelly, G. A. (1969). Personal construct theory and the psychotherapeutic interview. In B. Maher (Ed.), Clinical psychology and personality: The selected papers of George Kelly (pp. 224–232). New York, NY: Wiley.
   Google Scholar
• Keynan, A., Ben-Zvi Assaraf, O., & Goldman, D. (2014). The repertory grid as a tool for evaluating the development of students’ ecological system thinking abilities. Studies in Educational Evaluation, 41, 90–105. doi: 10.1016/j.stueduc.2013.09.012
   Web of Science ®Google Scholar
• Kitano, H. (2002). Systems biology: A brief overview. Science, 295(5560), 1662–1664. doi: 10.1126/science.1069492
   PubMed Web of Science ®Google Scholar
• Ladyman, J., Lambert, J., & Wiesner, K. (2013). What is a complex system? European Journal for Philosophy of Science, 3, 33–67. doi: 10.1007/s13194-012-0056-8
   Web of Science ®Google Scholar
• Latta, G. F., & Swigger, K. (1992). Validation of the repertory grid for use in modeling knowledge. Journal of the American Society for Information Science, 43, 115–129. doi:10.1002/(SICI)1097-4571(199203)43:2<115::AID-ASI2>3.0.CO;2-I
   Web of Science ®Google Scholar
• Lesh, R. (2006). Modeling students modeling abilities: The teaching and learning of complex systems in education. Journal of the Learning Sciences, 15(1), 45–52. doi: 10.1207/s15327809jls1501_6
   Web of Science ®Google Scholar
• Li, N., & Black, J. (2016). Inter-level scaffolding and sequences of representational activities in teaching a chemical system with graphical simulations. Journal of Science Education and Technology, 25(5), 715–730. doi: 10.1007/s10956-016-9626-4
   Web of Science ®Google Scholar
• 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. doi: 10.1002/tea.20297
   Web of Science ®Google Scholar
• Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25. doi: 10.1086/392759
   Web of Science ®Google Scholar
• Marbach-Ad, G., & Stavy, R. (2000). Students’ cellular and molecular explanations of genetic phenomena. Journal of Biological Education, 34(4), 200–205. doi: 10.1080/00219266.2000.9655718
   Web of Science ®Google Scholar
• Marieb, E. N., & Hoehn, K. (2012). Human anatomy & physiology. Boston, MA: Pearson.
   Google Scholar
• NGSS Lead States. (2013). Next generation science standards: For states, by states. Washington, DC: National Academy Press.
   Google Scholar
• Plate, R. (2010). Assessing individuals’ understanding of nonlinear causal structures in complex systems. System Dynamics Review, 26(1), 19–33. doi: 10.1002/sdr.432
   Web of Science ®Google Scholar
• Prediger, S., & Lengnink, K. (2003). Development of personal constructs about mathematical tasks – a qualitative study using repertory grid methodology. Presented in the proceedings of the 27th annual meeting of the International Group for the Psychology of Mathematics Education (PME), Hawaii 2003.
   Google Scholar
• Randall, D. J., Burggren, W. W., French, K., & Eckert, R. (2002). Eckert animal physiology: Mechanisms and adaptations. New York, NY: W.H. Freeman and Co.
   Google Scholar
• Rates, C. A., Mulvey, B. K., & Feldon, D. F. (2016). Promoting conceptual change for complex systems understanding: Outcomes of an agent-based participatory simulation. Journal of Science Education and Technology, 25(4), 610–627. doi: 10.1007/s10956-016-9616-6
   Web of Science ®Google Scholar
• 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, 247. doi: 10.3389/fpubh.2014.00260
   PubMedGoogle Scholar
• Richardson, K. A., Cilliers, P., & Lissack, M. (2001). Complexity science: A ‘gray’ science for the ‘stuff in between’. Emergence, 3(2), 6–18. doi: 10.1207/S15327000EM0302_02
   Google Scholar
• Rosenbaum, M., & Leibel, R. L. (2016). Models of energy homeostasis in response to maintenance of reduced body weight. Obesity, 24, 1620–1629. doi: 10.1002/oby.21559
   PubMed Web of Science ®Google Scholar
• Rozenszajn, R., & Yarden, A. (2015). Exposing biology teachers’ tacit views about the knowledge that is required for teaching using the repertory grid technique. Studies in Educational Evaluation, 47, 19–27. doi: 10.1016/j.stueduc.2015.06.001
   Web of Science ®Google Scholar
• Smith, J., Abdala, A., Borgmann, A., Rybak, I., & Paton, J. (2013). Brainstem respiratory networks: Building blocks and microcircuits. Trends in Neurosciences, 36(3), 152–162. doi: 10.1016/j.tins.2012.11.004
   PubMed Web of Science ®Google Scholar
• Southard, K., Wince, T., Meddleton, S., & Bolger, M. S. (2016). Features of knowledge building in biology: Understanding undergraduate students’ ideas about molecular mechanisms. CBE-Life Sciences Education, 15(1), ar7. doi: 10.1187/cbe.15-05-0114
   PubMed Web of Science ®Google Scholar
• Stewart, M. (2012). Joined up thinking? Evaluating the use of concept-mapping to develop complex system learning. Assessment & Evaluation in Higher Education, 37(3), 349–368. doi: 10.1080/02602938.2010.534764
   Web of Science ®Google Scholar
• Tanner, K. D. (2012). Promoting student metacognition. CBE – Life Sciences Education, 11, 113–120. doi: 10.1187/cbe.12-03-0033
   PubMed Web of Science ®Google Scholar
• Taylor, A., & Jones, G. (2009). Proportional reasoning ability and concepts of scale: Surface area to volume relationships in science. International Journal of Science Education, 31(9), 1231–1247. doi: 10.1080/09500690802017545
   Web of Science ®Google Scholar
• Taylor, A., & Jones, M. G. (2013). Students’ and teachers’ application of surface area to volume relationships. Research in Science Education, 43(1), 395–411. doi: 10.1007/s11165-011-9277-7
   Web of Science ®Google Scholar
• Todd, A., & Romine, W. L. (2017). Empirical validation of a modern genetics progression web for college biology students. International Journal of Science Education, 1–18. doi: 10.1080/09500693.2017.1296207
   Web of Science ®Google Scholar
• Tripto, J., Ben-Zvi Assaraf, O., & Amit, M. (2013). Mapping what they know: Concept maps as an effective tool for assessing students’ systems thinking. American Journal of Operations Research, 3, 245–258. doi: 10.4236/ajor.2013.31A022
   Google Scholar
• Tripto, J., Ben-Zvi Assaraf, O., Snapir, Z., & Amit, M. (2016a). How is the body’s systemic nature manifested amongst high school biology students? Instructional Science, 1–26. doi: 10.1007/s11251-016-9390-0
   Web of Science ®Google Scholar
• Tripto, J., Ben-Zvi Assaraf, O., Snapir, Z., & Amit, M. (2016b). The ‘What is a system’ reflection interview 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. doi: 10.1080/09500693.2016.1150620
   Web of Science ®Google Scholar
• 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. doi: 10.1080/09500690701237780
   Web of Science ®Google Scholar
• Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep, or a firefly: Learning biology through constructing and testing computational theories – An embodied modeling approach. Cognition and Instruction, 24(2), 171–209. doi: 10.1207/s1532690xci2402_1
   Web of Science ®Google Scholar
• Wilson, C. D., Anderson, C. W., Heidemann, M., Merrill, J. E., Merritt, B. W., Richmond, G., … Parker, J. M. (2006). Assessing students’ ability to trace matter in dynamic systems in cell biology. Cell Biology Education, 5(4), 323–331. doi: 10.1187/cbe.06-02-0142
   Google Scholar
• Yoon, S. (2008). Using memes and memetic processes to explain social and conceptual influences on student understanding about complex socio-scientific issues. Journal of Research in Science Teaching, 45(8), 900–921. doi: 10.1002/tea.20256
   Web of Science ®Google Scholar
• Yoon, S. A., Anderson, E., Koehler-Yom, J., Evans, C., Park, M., Sheldon, J., & Klopfer, E. (2016). Teaching about complex systems is no simple matter: Building effective professional development for computer-supported complex systems instruction. Instructional Science, 1–23. doi: 10.1007/s11251-016-9388-7
   Web of Science ®Google Scholar
• Zangori, L., & Koontz, J. A. (2017). Supporting upper-level undergraduate students in building a systems perspective in a botany course. Journal of Biological Education, 7, 1–13. doi: 10.1080/00219266.2016.1257502
   Google Scholar
• Zeidler, D. L., & Sadler, T. D. (2008). The role of moral reasoning in argumentation: Conscience, character and care. In S. Erduran, & M. Pilar Jimenez-Aleixandre (Eds.), Argumentation in science education: Perspectives from classroom-based research (pp. 201–216). New York: Springer.
   Google Scholar
• Zion, M., Michalsky, T., & Mevarech, Z. R. (2005). The effects of metacognitive instruction embedded within an asynchronous learning network on scientific inquiry skills. International Journal of Science Education, 27, 957–983. doi: 10.1080/09500690500068626
   Web of Science ®Google Scholar