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Supporting Representational Competence in High School Biology With Computer-Based Biomolecular Visualizations

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Wilder, A. & Brinkerhoff, J. (2007). Supporting Representational Competence in High School Biology With Computer-Based Biomolecular Visualizations. Journal of Computers in Mathematics and Science Teaching, 26(1), 5-26. Chesapeake, VA: AACE.
Retrieved from http://www.editlib.org/p/21126.

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Journal Information

JCMST

Journal of Computers in Mathematics and Science Teaching
ISSN 0731-9258
Volume 26, Issue 1, January 2007
Association for the Advancement of Computing in Education (AACE)  Chesapeake, VA

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Authors

Anna Wilder, Jonathan Brinkerhoff, University of New Mexico, United States

Abstract

This study assessed the effectiveness of computer-based biomolecular visualization activities on the development of high school biology students' representational competence as a means of understanding and visualizing protein structure/function relationships. Also assessed were students' attitudes toward these activities. Sixty-nine students enrolled in three sections of freshman biology used Chemscape Chime software to interactively view 3-D representations of the protein hemoglobin as part of a 10-week instructional unit. Students were also provided with written directions and guiding questions for viewing, manipulating and interpreting the visualizations. After completing the instruction, students' posttest scores revealed statistically significant gains in representational competence. Additional evidence including analysis of posttest responses, student interviews, attitude survey results and weekly activity surveys suggest that computer-based biomolecular visualization instruction was an effective curriculum component supporting the development of representational competence. However, students performed poorly on translation tasks involving graphs. Evidence based on student interviews and attitude survey ratings indicated neutral to mildly positive attitudes toward use of the Chemscape Chime software and computer-based biomolecular visualizations.

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