QUBES: a community focused on supporting teaching and learning in quantitative biology

Donovan, Sam S; Eaton, Carrie Diaz; Gower, Stith T.; Jenkins, Kristin; LaMar, M. Drew; Poli, DorothyBelle; Sheehy, Robert; Wojdak, Jeremy M.

doi:10.1080/23737867.2015.1049969

Cited by 25 publications

(23 citation statements)

References 2 publications

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“…Discussions of the importance of these competencies have not been matched by action; undergraduate life science education in the United States (and other nations) has been slow to integrate quantitative literacy into the curriculum (AAAS, ; Andrews, Runyon, & Aikens, ). Notable recent attempts, however, include the Supporting Faculty in Quantitative Undergraduate Biology Education and Synthesis (QUBES) project, a million‐dollar project funded by the U.S. National Science Foundation (Donovan et al, ). QUBES involves five interdependent initiatives designed to promote the integration of quantitative skills across the life sciences curriculum.…”

Section: Discussionmentioning

confidence: 99%

How strongly does statistical reasoning influence knowledge and acceptance of evolution?

et al. 2019

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A large body of research has examined students' conceptions of evolution and their relationships to acceptance of evolution. Proficiency in statistical and probabilistic reasoning has long been considered to be an essential feature of evolutionary reasoning, yet almost no empirical work has explored these putative connections. The RaPro instruments have recently been developed to measure statistical reasoning in the contexts of mathematics (RaProMath) and evolution (RaProEvo). Our study provides additional validation of these instruments using Rasch analysis and quantifies the contribution of statistical reasoning to both understanding and accepting evolution. We recruited a large sample (N = 564) of undergraduate students enrolled in an introductory biology course at a large public research university in the United States. Students completed a suite of published instruments that assessed statistical reasoning, evolutionary understanding, and evolutionary acceptance. Our findings indicate that validity inferences derived from RaPro scores generalized to the new sample, and that proficiency in statistical reasoning explained 28% of the variance in evolutionary knowledge and 19% of the variation in evolutionary acceptance. The inclusion of demographic variables into the model significantly increased the explained variance in acceptance. Notably, the variance in evolution acceptance explained by statistical reasoning was comparable to that of thinking dispositions or evolutionary knowledge reported in the literature. This work provides the first large-scale evidence of the role of statistical reasoning in evolutionary knowledge and acceptance and motivates future work to explore how statistical literacy should be integrated into evolution education efforts.

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Section: Discussionmentioning

confidence: 99%

How strongly does statistical reasoning influence knowledge and acceptance of evolution?

et al. 2019

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“…All interested parties are welcome to participate. Unlike a digital repository, QUBES infrastructure is designed for collaboration and informal sharing of ideas and resources and for partners with existing digital repositories to further disseminate good work into biology education networks (Donovan et al , 2015). We encourage the community at large to become an active part of this conversation around biology education.…”

Section: A Network Of Networkmentioning

confidence: 99%

Summit of the Research Coordination Networks for Undergraduate Biology Education

Eaton

Allen

Anderson

et al. 2016

LSE

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“…We would also like to thank Deborah Hughes-Hallett for her insights. Organization of this co-authorship and working group between meetings would not have been possible without QUBES Hub supported by NSF Awards #DBI 1346584, DUE 1446269, DUE 1446258, and DUE 1446284 [13,46] and our QUBES communications student, Timothy Beaulieu. Table A1.…”

Section: Fundingmentioning

confidence: 99%

A “Rule-of-Five” Framework for Models and Modeling to Unify Mathematicians and Biologists and Improve Student Learning

Eaton¹,

Highlander

Dahlquist³

et al. 2019

PRIMUS

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Despite widespread calls for the incorporation of mathematical modeling into the undergraduate biology curriculum, there is lack of a common understanding around the definition of modeling, which inhibits progress. In this paper, we extend the "Rule-of-Four," initially used in calculus reform efforts, to a "Rule-of-Five" framework for models and modeling that is inclusive of varying disciplinary definitions of each. This unifying framework allows us to both build on strengths that each discipline and its students bring, but also identify gaps in modeling activities practiced by each discipline. We also discuss benefits to student learning and interdisciplinary collaboration.

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QUBES: a community focused on supporting teaching and learning in quantitative biology

Cited by 25 publications

References 2 publications

How strongly does statistical reasoning influence knowledge and acceptance of evolution?

How strongly does statistical reasoning influence knowledge and acceptance of evolution?

Summit of the Research Coordination Networks for Undergraduate Biology Education

A “Rule-of-Five” Framework for Models and Modeling to Unify Mathematicians and Biologists and Improve Student Learning

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