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ERIC Number: EJ1164840
Record Type: Journal
Publication Date: 2018-Feb
Pages: 15
Abstractor: As Provided
ISSN: ISSN-1059-0145
Improving Conceptual Understanding and Representation Skills through Excel-Based Modeling
Malone, Kathy L.; Schunn, Christian D.; Schuchardt, Anita M.
Journal of Science Education and Technology, v27 n1 p30-44 Feb 2018
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.
Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: High Schools
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF), Division of Research on Learning in Formal and Informal Settings (DRL)
Authoring Institution: N/A
Grant or Contract Numbers: 1027629