Improving conceptual understanding and representation skills through Excel-based modeling

Kathy Malone, Anita Schuchardt, Christian Schunn

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

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 commonmisconceptions in both concept
areas as well as representational usage. The results of a posttest
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
Pages (from-to)30-44
JournalJournal of Science Education and Technology
DOIs
Publication statusPublished - Jan 2018

Keywords

  • modeling
  • multiple representation

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