Natural Resources, School of
ORCID IDs
Joseph Dauer http://orcid.org/0000-0002-8971-0441
Robert Mayes http://orcid.org/0000-0003-2726-2409
Kent Rittschof http://orcid.org/0000-0003-3213-7266
Date of this Version
2021
Citation
International Journal of Science Education (2021) 43(10): 1,685–1,707
doi: 10.1080/09500693.2021.1928325
Abstract
Quantitative modelling plays an important role as biology increasingly deals with big data sets, relies on modelling to understand system dynamics, makes predictions about impacts of changes, and revises our understanding of system interactions. An assessment of quantitative modelling in biology was administered to students (n = 612) in undergraduate biology courses at two universities to provide a picture of student ability in quantitative reasoning within biology and to determine how capable those students felt about this ability. A Rasch analysis was used to construct linear measures and provide validity evidence for the assessment and to examine item statistics on the same scale as student ability measures. Students overall had greater ability in quantitative literacy than in quantitative interpretation of models or modelling. There was no effect of class standing (freshmen, sophomore, etc.) on student performance. The assessment showed that students who participated felt confidence in their ability to quantitatively model biological phenomena, even while their performance on ability questions were low. Collectively modelling practices were correlated with students’ metamodelling knowledge and not correlated with students’ modelling capability confidence. Biology instructors who incorporate the process of modelling into their courses may see improved abilities of students to perform on quantitative modelling tasks.
Included in
Natural Resources and Conservation Commons, Natural Resources Management and Policy Commons, Other Environmental Sciences Commons
Comments
Copyright © 2021, Informa UK Limited, trading as Taylor & Francis Group. Used by permission.