A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology

Robert Mayes; David Owens; Joseph Dauer; Kent Rittschof

doi:doi:10.11648/j.acm.20221101.11

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A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology

Robert Mayes, David Owens, Joseph Dauer, Kent Rittschof

Published in Applied and Computational Mathematics (Volume 11, Issue 1)

Received: 20 August 2021 Accepted: 9 October 2021 Published: 18 January 2022

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Abstract

Biology is becoming more quantitative. If we are to support the future of quantitative biology, then the next generation of biologists must be prepared to consistently integrate quantitative reasoning into subject matter that has traditionally been considered through a qualitative lens. We introduce a quantitative reasoning framework and discuss the importance of quantitative modeling in biology. The framework includes the Quantitative Act as a support for Quantitative Modeling and Quantitative Interpretation. The QM BUGS diagnostic instrument was developed to assesses undergraduate biology students’ abilities to create and apply models employing pre-calculus mathematics. A brief discussion of our research findings based on implementation of the instrument include the lack of student ability to develop quantitative models. We present items from the instrument as examples of the Quantitative Act elements: variable quantification through identifying variable and attributes, measurement, variation, quantitative literacy, and context. We also provide items representing quantitative modeling and quantitative interpretation. We then view quantitative biology from K-12 and collegiate perspectives, including instructional practices for teaching quantitative biology, motivating problem contexts that afford quantification, instructional strategies of repetition, scaffolding, peer teaching and learning, direct instruction and teacher moves on the K-12 level, as well as identifying five competencies for the next generation of biologists which require QA abilities.

Published in	Applied and Computational Mathematics (Volume 11, Issue 1)
DOI	10.11648/j.acm.20221101.11
Page(s)	1-17
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Quantitative, Biology, Modeling, Interpretation

References

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Robert Mayes, David Owens, Joseph Dauer, Kent Rittschof. (2022). A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology. Applied and Computational Mathematics, 11(1), 1-17. https://doi.org/10.11648/j.acm.20221101.11

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Robert Mayes; David Owens; Joseph Dauer; Kent Rittschof. A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology. Appl. Comput. Math. 2022, 11(1), 1-17. doi: 10.11648/j.acm.20221101.11

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Robert Mayes, David Owens, Joseph Dauer, Kent Rittschof. A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology. Appl Comput Math. 2022;11(1):1-17. doi: 10.11648/j.acm.20221101.11

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@article{10.11648/j.acm.20221101.11,
  author = {Robert Mayes and David Owens and Joseph Dauer and Kent Rittschof},
  title = {A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology},
  journal = {Applied and Computational Mathematics},
  volume = {11},
  number = {1},
  pages = {1-17},
  doi = {10.11648/j.acm.20221101.11},
  url = {https://doi.org/10.11648/j.acm.20221101.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acm.20221101.11},
  abstract = {Biology is becoming more quantitative. If we are to support the future of quantitative biology, then the next generation of biologists must be prepared to consistently integrate quantitative reasoning into subject matter that has traditionally been considered through a qualitative lens. We introduce a quantitative reasoning framework and discuss the importance of quantitative modeling in biology. The framework includes the Quantitative Act as a support for Quantitative Modeling and Quantitative Interpretation. The QM BUGS diagnostic instrument was developed to assesses undergraduate biology students’ abilities to create and apply models employing pre-calculus mathematics. A brief discussion of our research findings based on implementation of the instrument include the lack of student ability to develop quantitative models. We present items from the instrument as examples of the Quantitative Act elements: variable quantification through identifying variable and attributes, measurement, variation, quantitative literacy, and context. We also provide items representing quantitative modeling and quantitative interpretation. We then view quantitative biology from K-12 and collegiate perspectives, including instructional practices for teaching quantitative biology, motivating problem contexts that afford quantification, instructional strategies of repetition, scaffolding, peer teaching and learning, direct instruction and teacher moves on the K-12 level, as well as identifying five competencies for the next generation of biologists which require QA abilities.},
 year = {2022}
}

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TY  - JOUR
T1  - A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology
AU  - Robert Mayes
AU  - David Owens
AU  - Joseph Dauer
AU  - Kent Rittschof
Y1  - 2022/01/18
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Author Information

Robert Mayes

Middle and Secondary Education, Georgia Southern University, Statesboro, United States
David Owens

Middle and Secondary Education, Georgia Southern University, Statesboro, United States
Joseph Dauer

School of Natural Resources, University of Nebraska, Lincoln, United States
Kent Rittschof

Curriculum, Foundations, and Reading, Georgia Southern University, Statesboro, United States

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Robert Mayes, David Owens, Joseph Dauer, Kent Rittschof. (2022). A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology. Applied and Computational Mathematics, 11(1), 1-17. https://doi.org/10.11648/j.acm.20221101.11

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Robert Mayes; David Owens; Joseph Dauer; Kent Rittschof. A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology. Appl. Comput. Math. 2022, 11(1), 1-17. doi: 10.11648/j.acm.20221101.11

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Robert Mayes, David Owens, Joseph Dauer, Kent Rittschof. A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology. Appl Comput Math. 2022;11(1):1-17. doi: 10.11648/j.acm.20221101.11

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@article{10.11648/j.acm.20221101.11,
  author = {Robert Mayes and David Owens and Joseph Dauer and Kent Rittschof},
  title = {A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology},
  journal = {Applied and Computational Mathematics},
  volume = {11},
  number = {1},
  pages = {1-17},
  doi = {10.11648/j.acm.20221101.11},
  url = {https://doi.org/10.11648/j.acm.20221101.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acm.20221101.11},
  abstract = {Biology is becoming more quantitative. If we are to support the future of quantitative biology, then the next generation of biologists must be prepared to consistently integrate quantitative reasoning into subject matter that has traditionally been considered through a qualitative lens. We introduce a quantitative reasoning framework and discuss the importance of quantitative modeling in biology. The framework includes the Quantitative Act as a support for Quantitative Modeling and Quantitative Interpretation. The QM BUGS diagnostic instrument was developed to assesses undergraduate biology students’ abilities to create and apply models employing pre-calculus mathematics. A brief discussion of our research findings based on implementation of the instrument include the lack of student ability to develop quantitative models. We present items from the instrument as examples of the Quantitative Act elements: variable quantification through identifying variable and attributes, measurement, variation, quantitative literacy, and context. We also provide items representing quantitative modeling and quantitative interpretation. We then view quantitative biology from K-12 and collegiate perspectives, including instructional practices for teaching quantitative biology, motivating problem contexts that afford quantification, instructional strategies of repetition, scaffolding, peer teaching and learning, direct instruction and teacher moves on the K-12 level, as well as identifying five competencies for the next generation of biologists which require QA abilities.},
 year = {2022}
}

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TY  - JOUR
T1  - A Quantitative Reasoning Framework and the Importance of Quantitative Modeling in Biology
AU  - Robert Mayes
AU  - David Owens
AU  - Joseph Dauer
AU  - Kent Rittschof
Y1  - 2022/01/18
PY  - 2022
N1  - https://doi.org/10.11648/j.acm.20221101.11
DO  - 10.11648/j.acm.20221101.11
T2  - Applied and Computational Mathematics
JF  - Applied and Computational Mathematics
JO  - Applied and Computational Mathematics
SP  - 1
EP  - 17
PB  - Science Publishing Group
SN  - 2328-5613
UR  - https://doi.org/10.11648/j.acm.20221101.11
AB  - Biology is becoming more quantitative. If we are to support the future of quantitative biology, then the next generation of biologists must be prepared to consistently integrate quantitative reasoning into subject matter that has traditionally been considered through a qualitative lens. We introduce a quantitative reasoning framework and discuss the importance of quantitative modeling in biology. The framework includes the Quantitative Act as a support for Quantitative Modeling and Quantitative Interpretation. The QM BUGS diagnostic instrument was developed to assesses undergraduate biology students’ abilities to create and apply models employing pre-calculus mathematics. A brief discussion of our research findings based on implementation of the instrument include the lack of student ability to develop quantitative models. We present items from the instrument as examples of the Quantitative Act elements: variable quantification through identifying variable and attributes, measurement, variation, quantitative literacy, and context. We also provide items representing quantitative modeling and quantitative interpretation. We then view quantitative biology from K-12 and collegiate perspectives, including instructional practices for teaching quantitative biology, motivating problem contexts that afford quantification, instructional strategies of repetition, scaffolding, peer teaching and learning, direct instruction and teacher moves on the K-12 level, as well as identifying five competencies for the next generation of biologists which require QA abilities.
VL  - 11
IS  - 1
ER  -

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