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NIMBioS Working Group:

Quant Bio@Community College

Teaching photo.

Topic: Developing new solutions to improve student quantitative biology skills: A focus on community colleges

Meeting dates: April 26-28, 2018; October 25-27, 2018

Organizers:
Jillian Miller, Mathematics, Roane State Community College
Stacey Kiser, Biology, Lane Community College
Kristin Jenkins, Director, BioQUEST
Ahrash Bissell, Director of Strategic Partnerships, EdReady Manager, The NROC Project, Monterey Institute for Technology and Education

Objectives: Biology is becoming an increasingly quantitative discipline, and preparing students to succeed requires more emphasis on quantitative skills and quantitative reasoning, the ability to apply quantitative skills in a biological context. Acquiring strong quantitative biology skills presents a challenge to all students, but students starting at community colleges face additional barriers we cannot ignore. Over 40 percent of undergraduates are enrolled at community colleges, with disproportionate numbers of students typically underrepresented in STEM starting their college careers at the community colleges. Over half of community college students are referred to remedial math courses, and spending time in remedial courses reduces significantly a student's chance to complete a degree. New models for providing remediation in a more effective and less problematic way are being developed, including interdisciplinary remediation by placing remedial skills units in introductory courses like biology. It is challenging to develop and implement interdisciplinary models in part because biology faculty are, in general, poorly prepared to teach mathematical concepts beyond the methods they themselves are familiar with, and mathematics faculty are ill-equipped to teach mathematics in a biological context. To develop resources that will help faculty and students learn quantitative biology skills will require the combined effort of practitioners from math and biology education. The goal of this working group is to synthesize educational research on quantitative biology and remedial mathematics education at community colleges, apply this information to identify core quantitative biology skills and develop supporting educational and professional development resources for both two- and four-year biology faculty.

Mtg # Dates Agenda Summary Photo Evaluation
1 April 26-28, 2018 pdf TBA Link TBA
2 October 25-27, 2018 TBA TBA TBA -

Group photo.
Meeting 1 participants. Back row (l to r): Vedham Karpakakunjaram, Stacey Kiser, Louis Gross, Suzanne Lenhart, Claudia Neuhauser (virtual), Ahrash Bissell, Christianne Nieuwsma, Melissa Aikens, Lisa Corwin. Seated (l to r): Jillian Miller, Sondra LoRe, Kristin Jenkins, Greg Wiggins, Tony Weisstein.


NIMBioS Working Groups are chosen to focus on major scientific questions at the interface between biology and mathematics. NIMBioS is particularly interested in questions that integrate diverse fields, require synthesis at multiple scales, and/or make use of or require development of new mathematical/computational approaches. NIMBioS Working Groups are relatively small (up to 10 participants), focus on a well-defined topic, and have well-defined goals and metrics of success. Working Groups will meet up to 3 times over a two-year period, with each meeting lasting up to 2.5 days.

A goal of NIMBioS is to enhance the cadre of researchers capable of interdisciplinary efforts across mathematics and biology. As part of this goal, NIMBioS is committed to promoting diversity in all its activities. Diversity is considered in all its aspects, social and scientific, including gender, ethnicity, scientific field, career stage, geography and type of home institution. Questions regarding diversity issues should be directed to Dr. Ernest Brothers, the NIMBioS Associate Director for Diversity Enhancement (diversity@nimbios.org). You can read more about our Diversity Plan on our NIMBioS Policies web page. The NIMBioS building is fully handicapped accessible.


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NSF logo. NIMBioS is supported by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
 
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