Analyzing change in students' gene-to-evolution models in college-level introductory biology


Journal Article

Research in contemporary biology has become increasingly complex and organized around understanding biological processes in the context of systems. To better reflect the ways of thinking required for learning about systems, we developed and implemented a pedagogical approach using box-and-arrow models (similar to concept maps) as a foundational tool for instruction and assessment in an Introductory Biology course on genetics, evolution, and ecology. Over the course of one semester, students iteratively constructed, evaluated, and revised "Gene-to-Evolution" (GtE) models intended to promote understanding about the connections linking molecular-level processes with population-level outcomes. In practice, a successful GtE model contextualizes information provided in a case study and explains how genetic-level variation originates at the molecular level, is differentially expressed among individuals, and is acted upon by the environment to produce evolutionary change within a population. Our analyses revealed that students' ability to construct biologically accurate models increased throughout the semester. Model complexity peaked near mid-term then subsequently declined. This suggests that, with time, students were building more parsimonious models, shedding irrelevant information, and improving in their ability to apply accurate and appropriate biological language to explain relationships among concepts. Importantly, we observed the greatest relative gains in model correctness among students who entered the course with lower mean GPA. In an analysis comparing performance among achievement tritiles, lower-performing students effectively closed the achievement gap with the highest performing students by the end of the semester. Our findings support the effectiveness of model-based pedagogies for science teaching and learning, and offer a perspective on pedagogical application of modeling strategies to foster systems thinking and knowledge structuring in college-level biology. Copyright © 2013 Wiley Periodicals, Inc.

Full Text

Duke Authors

Cited Authors

  • Dauer, JT; Momsen, JL; Speth, EB; Makohon-Moore, SC; Long, TM

Published Date

  • August 1, 2013

Published In

Volume / Issue

  • 50 / 6

Start / End Page

  • 639 - 659

Electronic International Standard Serial Number (EISSN)

  • 1098-2736

International Standard Serial Number (ISSN)

  • 0022-4308

Digital Object Identifier (DOI)

  • 10.1002/tea.21094

Citation Source

  • Scopus