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Supporting and Assessing Complex Biology Learning with Computer-Based Simulations and Representations

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Multiple Representations in Biological Education

Part of the book series: Models and Modeling in Science Education ((MMSE,volume 7))

Abstract

Biology learning is, by its very nature, complex. Living systems are composed of systems nested within systems, each of which has components that interact to produce the emergent behavior of that system and interact in the next larger system. Living system components can be as small as ions and can participate in systems as large as the biosphere of Earth. This chapter summarizes a body of research conducted on the use of computer-based simulations and representations for instruction and assessment in human body systems, genetics, and ecosystems. The strategic use of these representations for fostering and assessing model-based learning, reasoning, and inquiry are discussed, as are the tasks that students can perform with these representations and the evidence that can be gathered when students perform these tasks. This chapter also presents a theoretical framework that integrates model-based learning with evidence-centered design and describes how it is used to guide the design of simulation-based representations in assessment. This framework has the potential to transform the experiences and outcomes of biology learning by enabling learners to develop richly connected, useful, and extensible understandings of living systems.

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Acknowledgments

The author gratefully acknowledges the colleagues and funding that have made this work possible. The Science for Living project was supported by the Apple Classroom of Tomorrow and the Carnegie Corporation. The BioLogica project was funded by grants from the National Science Foundation and IERI. The Calipers projects are funded by grants from the National Science Foundation, whereas the large-scale field test was supported by the US Department of Education. Any opinions, findings, and conclusions or recommendations expressed in this chapter are those of the author and do not necessarily reflect the views of the funders.

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Authors and Affiliations

  1. Science, Technology, Engineering and Mathematics, WestEd, 400 Seaport Court, Suite 222, Redwood City, CA, 94063, USA

    Barbara C. Buckley & Edys S. Quellmalz

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  1. Barbara C. Buckley
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  2. Edys S. Quellmalz
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Correspondence to Barbara C. Buckley .

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Editors and Affiliations

  1. Science and Mathematics Education Centre, Curtin University, Kent Street, Bentley, Perth, 6102, West Australia, Australia

    David F. Treagust

  2. Science and Mathematics Education Centre, Curtin University, Glenveagh Dr, Mt Roskill 30, Auckland, 1041, New Zealand

    Chi-Yan Tsui

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Buckley, B.C., Quellmalz, E.S. (2013). Supporting and Assessing Complex Biology Learning with Computer-Based Simulations and Representations. In: Treagust, D., Tsui, CY. (eds) Multiple Representations in Biological Education. Models and Modeling in Science Education, vol 7. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4192-8_14

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