Infusing quantitative approaches throughout the biological sciences curriculum

Thompson, Katerina V.; Cooke, Todd J.; Fagan, William F.; Gulick, Denny; Levy, Doron; Nelson, Karen; Redish, Edward F.; Smith, Robert F.; Presson, Joelle C.

doi:10.1080/0020739x.2013.812754

Cited by 31 publications

(25 citation statements)

References 20 publications

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“…In response to these calls, there have been efforts to better integrate math into biology curricula. Such reforms include incorporating the teaching of quantitative skills (e.g., via modules or in-class research experiences) into biology courses ( Robeva et al , 2010 ; Speth et al , 2010 ; Thompson et al , 2010 ; Colon-Berlingeri and Burrowes, 2011 ; Madlung et al , 2011 ; Wightman and Hark, 2012 ; Makarevitch et al , 2015 ; Hoffman et al , 2016 ), redesigning mathematics courses for biology majors to include biology examples ( Edelstein-Keshet, 2005 ; Metz, 2008 ; Chiel et al , 2010 ; Duffus and Olifer, 2010 ; Watkins, 2010 ; Rheinlander and Wallace, 2011 ; Thompson et al , 2013 ), and designing fully integrated math–biology courses and majors ( Depelteau et al , 2010 ; de Pillis and Adolph, 2010 ; Duffus and Olifer, 2010 ; Hoskinson, 2010 ; Usher et al , 2010 ; Thompson et al , 2013 ; Hester et al , 2014 ). The goal of such reforms is to ensure that students develop quantitative skills that will prepare them for careers in the field of modern biology.…”

Section: Introductionmentioning

confidence: 99%

“…However, one challenge to quantitative biology education reform is negative student attitudes toward math ( Colon-Berlingeri and Burrowes, 2011 ; Thompson et al , 2013 ). For example, if students have a negative attitude toward math, they may resist learning math or avoid professors who emphasize math or courses in which more math is incorporated ( Colon-Berlingeri and Burrowes, 2011 ).…”

Section: Introductionmentioning

confidence: 99%

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The Math–Biology Values Instrument: Development of a Tool to Measure Life Science Majors’ Task Values of Using Math in the Context of Biology

Andrews

Runyon

Aikens

2017

LSE

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Math–Biology Values Instrument: Development of a Tool to Measure Life Science Majors’ Task Values of Using Math in the Context of Biology

Andrews

Runyon

Aikens

2017

LSE

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“…Also, there have been concerted efforts to improve quantitative skills of life‐science students over time (Thompson et al. ). Thus, we expected PVA quality to increase over time.…”

Section: Discussionmentioning

confidence: 99%

A critical appraisal of population viability analysis

Chaudhary

Oli

2019

Conservation Biology

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Population viability analysis (PVA) is useful in management of imperiled species. Applications range from research design, threat assessment, and development of management frameworks. Given the importance of PVAs, it is essential that they be rigorous and adhere to widely accepted guidelines; however, the quality of published PVAs is rarely assessed. We evaluated the quality of 160 PVAs of 144 species of birds and mammals published in peer-reviewed journals from 1990 to 2017. We hypothesized that PVA quality would be lower with generic programs than with custom-built programs; be higher for those developed for imperiled species; change over time; and be higher for those published in journals with high impact factors (IFs). Each included study was evaluated based on answers to an evaluation framework containing 32 questions reflecting whether and to what extent the PVA study adhered to published PVA guidelines or contained important PVA components. All measures of PVA quality were generally lower for studies based on generic programs. Conservation status of the species did not affect any measure of PVA quality, but PVAs published in high IF journals were of higher quality. Quality generally declined over time, suggesting the quantitative literacy of PVA practitioners has not increased over time or that PVAs developed by unskilled users are being published in peer-reviewed journals. Only 18.1% of studies were of high quality (score >75%), which is troubling because poor-quality PVAs could misinform conservation decisions. We call for increased scrutiny of PVAs by journal editors and reviewers. Our evaluation framework can be used for this purpose. Because poor-quality PVAs continue to be published, we recommend caution while using PVA results in conservation decision making without thoroughly assessing the PVA quality.Resumen: El análisis de viabilidad poblacional (AVP) esútil para el manejo de especies en peligro. La gama * Address correspondence to V. Chaudhary, email chaudharyv@ufl.edu Article impact statement: Wildlife managers must exercise caution while using PVA results for conservation planning because poor quality PVA continue to be published in peer-reviewed journals.

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“…Supporting students' modeling abilities likely requires a concerted effort over multiple class periods, courses, and years. We are unaware of research on longitudinal changes in students' modeling ability at the postsecondary level, possibly because broad integration of modeling into biology curricula is rare (see Thompson et al 2013 for quantitative integration). Longitudinal studies into integrative curricula can provide critical feedback to instructors about student modeling abilities over time and inform how to introduce critical skills like mathematically relating relationships, how and when to revise models, and using models to fuel science discovery.…”

Section: Discussionmentioning

confidence: 99%

Changes in students’ mental models from computational modeling of gene regulatory networks

et al. 2019

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Background: Computational modeling is an increasingly common practice for disciplinary experts and therefore necessitates integration into science curricula. Computational models afford an opportunity for students to investigate the dynamics of biological systems, but there is significant gap in our knowledge of how these activities impact student knowledge of the structures, relationships, and dynamics of the system. We investigated how a computational modeling activity affected introductory biology students' mental models of a prokaryotic gene regulatory system (lac operon) by analyzing conceptual models created before and after the activity. Results: Students' pre-lesson conceptual models consisted of provided, system-general structures (e.g., activator, repressor) connected with predominantly incorrect relationships, representing an incomplete mental model of gene regulation. Students' post-lesson conceptual models included more context-specific structures (e.g., cAMP, lac repressor) and increased in total number of structures and relationships. Student conceptual models also included higher quality relationships among structures, indicating they learned about these context-specific structures through integration with their expanding mental model rather than in isolation. Conclusions: Student mental models meshed structures in a manner indicative of knowledge accretion while they were productively reconstructing their understanding of gene regulation. Conceptual models can inform instructors about how students are relating system structures and whether students are developing more sophisticated models of system-general and system-specific dynamics.

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Infusing quantitative approaches throughout the biological sciences curriculum

Cited by 31 publications

References 20 publications

The Math–Biology Values Instrument: Development of a Tool to Measure Life Science Majors’ Task Values of Using Math in the Context of Biology

The Math–Biology Values Instrument: Development of a Tool to Measure Life Science Majors’ Task Values of Using Math in the Context of Biology

A critical appraisal of population viability analysis

Changes in students’ mental models from computational modeling of gene regulatory networks

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