Abstract
Evidence suggests computer simulations serve as effective supplements in traditional science instruction. In this section, we highlight seven considerations for embedding simulations in instruction in meaningful ways. We emphasize the specific aim of embedding simulations to provide learner supports required by inquiry-based and problem-based learning approaches to science education. These approaches are more open ended and learner driven which poses a unique set of challenges to educators and learners. In prior sections of this brief, we have set the stage for simulations to address these challenges. Here we suggest that for simulations to function scaffolds, educators, designers, and researchers must consider: attending to opportunities for transfer during curriculum design, connecting simulations to classroom exercises purposefully, developing learners’ scientific process skills through the manipulation of variables, addressing science misconceptions, fading scaffolds to best support learning, supporting assessment for and of learning, and building teacher knowledge.
The original version of this chapter was revised. The erratum to this chapter is available at: DOI 10.1007/978-3-319-24615-4_7
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-24615-4_7
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References
Buckley, B. C., & Quellmalz, E. S. (2013). Supporting and assessing complex biology learning with computer-based simulations and representations. In D. F. Treagust & C.-Y. Tsui (Eds.), Multiple representations in biological education (pp. 247–267). Netherlands: Springer. Retrieved from http://link.springer.com/chapter/10.1007/978-94-007-4192-8_14.
de Jong, T., Linn, M. C., & Zacharia, Z. C. (2013). Physical and virtual laboratories in science and engineering education. Science, 340(6130), 305–308. doi:10.1126/science.1230579.
De Klerk, S., Veldkamp, B. P., & Eggen, T. J. H. M. (2015). Psychometric analysis of the performance data of simulation-based assessment: A systematic review and a Bayesian network example. Computers & Education, 85, 23–34. doi:10.1016/j.compedu.2014.12.020.
Dillenbourg, P., Järvelä, S., & Fischer, F. (2009). The evolution of research on computer-supported collaborative learning. In N. Balacheff, S. Ludvigsen, T. De Jong, A. Lazonder, S. Barnes, & L. Montandon (Eds.), Technology-enhanced learning (pp. 3–19). Netherlands: Springer. Retrieved from http://link.springer.com/chapter/10.1007/978-1-4020-9827-7_1.
Driver, R., Rushworth, P., Squires, A., & Wood-Robinson, V. (2013). Making sense of secondary science: Research into children’s ideas. London: Routledge.
Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. (2007). Scaffolding and Achievement in Problem-Based and Inquiry Learning: A Response to Kirschner, Sweller, and Clark (2006). Educational Psychologist, 42(2), 99–107. doi:10.1080/00461520701263368.
Honey, M., & Hilton, M. (Eds.). (2011). Learning science through computer games and simulations. Committee on Science Learning: Computer Games, Simulations, and Education. Board on Science Education, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.
Pea, R. D. (2004). The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity. The Journal of the Learning Sciences, 13(3), 423–451.
Renken, M. D., & Nunez, N. (2010). Evidence for improved conclusion accuracy after reading about rather than conducting a belief-inconsistent simple physics experiment. Applied Cognitive Psychology, 24(6), 792–811. doi:10.1002/acp.1587.
Rutten, N., Van Joolingen, W. R., & Van Der Veen, J. T. (2012). The learning effects of computer simulations in science education. Computers and Education, 58(1), 136–153. doi:10.1016/j.compedu.2011.07.017.
Tabak, I. (2004). Synergy: A complement to emerging patterns of distributed scaffolding. The Journal of the Learning Sciences, 13(3), 305–335.
van Joolingen, W. R., De Jong, T., & Dimitrakopoulou, A. (2007). Issues in computer supported inquiry learning in science. Journal of Computer Assisted Learning, 23(2), 111–119. doi:10.1111/j.1365-2729.2006.00216.x.
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Otrel-Cass, K., Girault, I., Renken, M., Chiocarriello, A., Peffer, M. (2016). Considerations for Integrating Simulations in the Science Classroom. In: Simulations as Scaffolds in Science Education. SpringerBriefs in Educational Communications and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-24615-4_6
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DOI: https://doi.org/10.1007/978-3-319-24615-4_6
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