NIQB Resources

This page has links to various resources that may be useful to teams as they develop quantitative reasoning modules for the four-course biology sequence.

NIQB-IUSE Executive Summary

In 2018, the University of Maryland, Baltimore County (UMBC) and our community college collaborators were awarded a grant through the National Science Foundation (NSF) Division of Undergraduate Education’s (DUE) Improving Undergraduate Science Education (IUSE) Program (project timeline October 1, 2018 – September 30, 2023). The community college collaborators on this initiative include UMBC’s top sending institutions for transfer students: Anne Arundel Community College (AACC), Community College of Baltimore County (CCBC), Howard Community College (HCC), and Montgomery College (MC). The five institutions participating in this initiative will be collectively known as the NIQB IUSE Consortium.

The proposed work leverages the partnership between these institutions that was established under the STEM Transfer Success Initiative (1), funded by the Bill & Melinda Gates Foundation, as well as previous and current work conducted as part of the HHMI-funded NEXUS project (2) and the STEM BUILD at UMBC Initiative (3), funded by the NIH.

The proposed work involves the establishment of three scholarly communities, where membership will consist of faculty and stakeholders from the NIQB IUSE Consortium. These communities, and specific objectives of the proposed work, include:

1. The Curricular Alignment Team: faculty from each institution (up to 4 biology and 1 math) will comprehensively review curricula within the introductory core biology sequence (Introductory Biology I: Cells and Molecules; Introductory Biology II: Ecology and Evolution; Genetics; and Cell Biology). This team will identify areas for action across the core sequence, with emphasis on transfer student progression from the 2-year to 4-year institution. This team will also identify barriers to content mastery within biology, with particular emphasis on quantitative reasoning (QR) skills, and determine content areas for the development of active learning QR modules in biology.

2. Nexus Institute in Quantitative Biology (NIQB): faculty from each institution will work collaboratively to develop/revise, implement, assess and disseminate (DRIAD process) quantitative reasoning modules related to content in the 4-course core biology sequence. As part of this community, a 3-day summer NIQB institute will be held (location rotates among the five institutions involved), with work continuing during the academic year on the DRIAD process during regular meetings. The day prior to the 3-day institute, the annual IUSE Symposium will take place. This symposium will be a venue to showcase to members of the NIQB IUSE community the developed and assessed QR modules as well as the impact of the QR modules on student success in biology across the consortium.

3. Faculty Development Community (FDC): faculty/professional development leads at each of the NIQB IUSE Consortium institutions will develop and assess an inter-institutional certificate program that focuses on evidence-based pedagogical approaches, to include the QR modules developed as part of the NIQB community, within biology. The certificate program will include academic year workshops, peer observations, feedback opportunities, and administration recognition.

Given these communities and specific aims, the overarching research questions of the proposed work are:

1. Is the proposed, multi-pronged, inter-institutional model of creating the scholarly communities outlined above an effective way to promote change? Specifically, does this model promote curricular awareness between institutions and result in development of QR modules that are widely adapted/adopted and successfully implemented across participating institutions?

2. Will adding modules to corresponding biology courses at the community college collaborators increase gains in QR skills and decrease the achievement gap previously documented2 in introductory biology curricula between direct entry and transfer students?

3. To what extent can increasing the amount of QR in biology courses enhance students’ abilities to use quantitative skills to address biological problems? Does increasing exposure to QR modules positively impact student retention and success in advanced coursework?


References:

1. Jewett, et al. (2018). Awareness, Analysis, and Action: Curricular Alignment for Student Success in General Chemistry. J Chem Ed 95: 242

2. Hoffman, et al. (2016). Development and Assessment of Modules to Integrate Quantitative Skills in Introductory Biology Courses. CBE-Life Sciences Education 15: ar14

3. LaCourse, et al. (2017). Think 500, not 50! A scalable approach to student success in STEM. BMC Proceedings 11: 24

Previously Developed Modules

The modules listed here were developed through funding from the Howard Hughes Medical Institute as part of the National Experiment in Undergraduate Science Education (NEXUS) grant number 52007126. Questions should be directed towards Jeff Leips (leips@umbc.edu), Kathleen Hoffman (khoffman@umbc.edu), and Sarah Leupen (leupen@umbc.edu).

Diffusion: Delivering O2 and Glucose as Fast as Possible!

  • Unit conversion, power functions, linear models
  • Speedy diffusion of oxygen and carbon dioxide into and out of organisms, especially large or endothermic organisms

Cell Structure and Function: How to Escape a Jaguar

  • Power functions, linear models, t-test
  • Amplification that can occur in cellular signaling pathways

Photosynthesis

  • Unit conversions, setting up equations, scientific notation, simple manipulations based on the stoichiometry of chemical equations
  • Photosynthesis in both a real-world context and as conceptually integrated with cellular respiration, as well as with industrial CO2 production

Mendelian Genetics and Chromosome Theory

  • Basic arithmetic, probability, Chi-Square test
  • Calculate and predict the genotype and phenotype frequencies resulting from monohybrid and dihybrid crosses

Ecology: Biodiversity and Species Area Relationships

  • Basic arithmetic, logical reasoning, graph/data interpretation
  • Species-area relationships using log-log graphs and power functions

Do Rare Males Have A Mating Advantage? Using Mathematical Modeling to Explore Sexual Selection - Evolutionary Ecology Application

  • Mathematical modeling in a biological context, linear models, regression models
  • Frequency dependent sexual selection of fin color in cichlid fish

Population Genetics I: Natural Selection and Allele Frequencies (Breeding Bunnies)

  • Probability, Chi-Square test
  • Explore the influence of natural selection on allele frequencies

Population Genetics II: The Effect of Gene Flow and Genetic Drift on the Efficiency of Natural Selection in Evolution (Migrating Bunnies)

  • Probability, Chi-Square test
  • Influence of gene flow and genetic drift on the efficiency of the process of adaptation by natural selection

Assessing the Effectiveness of Drug Treatments Using Mathematical Modeling

  • Mathematical models in biological context (linear and regression models)
  • Data on size of colorectal tumor and drug efficacy

Animal Physiology: Size and Surface Area in Animal Physiology

  • Basic arithmetic and power functions
  • Fundamental relationship between size, surface area, volume, and function of animal systems

Useful Articles

Article on developing quantitative biology curricula

  • Aikens and Dolan (2014). Teaching quantitative biology: goals, assessments, and resources. Molecular Biology of the Cell 25: 3478

Article describing previous development and implementation of NEXUS project QR modules at UMBC

  • Hoffman, et al. (2016). Development and Assessment of Modules to Integrate Quantitative Skills in Introductory Biology Courses. CBE - Life Sciences Education. 15: ar14

Scientific Foundations for Future Physicians, the document used during the NEXUS project as a guide for development of quantitative competencies

  • Association of American Medical College’s and Howard Hughes Medical Institute (2009). Scientific Foundations for Future Physicians. American Association of Medical Colleges, Washington, DC

Article describing a strategy to develop students' quantitative writing abilities

  • Ruscetti, et al. (2018). Improving quantitative writing one sentence at a time. PLoS ONE 3: e0203109

Article on inclusive teaching

  • Killpack and Melon (2016). Toward Inclusive STEM Classrooms: What Personal Role Do Faculty Play? CBE - Life Sciences Education. 16: es3.1
  • Dewsbery and Brame (2019) . Inclusive Teaching. CBE-Life Sciences Education. 18: fe2

Revised Bloom's Taxonomy Action Verbs

  • Source: Anderson and Krathwohl (2001). A taxonomy for learning, teaching, and assessing. Abridged Edition. Boston, MA: Allyn and Bacon.