Improving Conceptual Understanding and Representation Skills Through Excel-Based Modeling

Kathy L. Malone, Christian D. Schunn, Anita M. Schuchardt

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


The National Research Council framework for science education and the Next Generation Science Standards have developed a need for additional research and development of curricula that is both technologically model-based and includes engineering practices. This is especially the case for biology education. This paper describes a quasi-experimental design study to test the effectiveness of a model-based curriculum focused on the concepts of natural selection and population ecology that makes use of Excel modeling tools (Modeling Instruction in Biology with Excel, MBI-E). The curriculum revolves around the bio-engineering practice of controlling an invasive species. The study takes place in the Midwest within ten high schools teaching a regular-level introductory biology class. A post-test was designed that targeted a number of common misconceptions in both concept areas as well as representational usage. The results of a post-test demonstrate that the MBI-E students significantly outperformed the traditional classes in both natural selection and population ecology concepts, thus overcoming a number of misconceptions. In addition, implementing students made use of more multiple representations as well as demonstrating greater fascination for science.

Original languageEnglish (US)
Pages (from-to)30-44
Number of pages15
JournalJournal of Science Education and Technology
Issue number1
StatePublished - Feb 1 2018

Bibliographical note

Publisher Copyright:
© 2017, Springer Science+Business Media, LLC.


  • Biology
  • Engineering
  • Modeling
  • Models
  • Representations


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