Improving Conceptual Understanding and Representation Skills Through Excel-Based Modeling

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

Research output: Contribution to journalArticle

2 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 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
Volume27
Issue number1
DOIs
StatePublished - Feb 1 2018

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Curricula
biology
Ecology
curriculum
ecology
Education
science
Students
engineering
Design of experiments
research and development
education
Teaching
student
instruction
school
Bioengineering

Keywords

  • Biology
  • Engineering
  • Modeling
  • Models
  • Representations

Cite this

Improving Conceptual Understanding and Representation Skills Through Excel-Based Modeling. / Malone, Kathy L.; Schunn, Christian D.; Schuchardt, Anita.

In: Journal of Science Education and Technology, Vol. 27, No. 1, 01.02.2018, p. 30-44.

Research output: Contribution to journalArticle

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