
NSF Org: |
DBI Division of Biological Infrastructure |
Recipient: |
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Initial Amendment Date: | June 18, 2020 |
Latest Amendment Date: | June 18, 2020 |
Award Number: | 2019088 |
Award Instrument: | Standard Grant |
Program Manager: |
Amanda Simcox
asimcox@nsf.gov (703)292-8165 DBI Division of Biological Infrastructure BIO Directorate for Biological Sciences |
Start Date: | December 15, 2020 |
End Date: | October 31, 2022 (Estimated) |
Total Intended Award Amount: | $74,897.00 |
Total Awarded Amount to Date: | $74,897.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
401 TERRY AVE N SEATTLE WA US 98109-5263 (206)732-1200 |
Sponsor Congressional District: |
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Primary Place of Performance: |
401 Terry Avenue North Seattle WA US 98109-5263 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): |
UBE - Undergraduate Biology Ed, IUSE |
Primary Program Source: |
04002021DB NSF Education & Human Resource |
Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.074 |
ABSTRACT
This RCN-UBE project seeks to network community college educators and systems biologists to promote biological data literacy amongst community college students. The volume, velocity, and variety of biological data has increased dramatically. As a result, current and future careers in biology are now highly dependent on quantitative skills such as sophisticated mathematical modeling, ?big data? analysis, and computer simulation. The implication for education is that all biology students need educational experiences that build biological data literacy. However, due to the rapidly evolving nature of skills needed to interact with increased volume, velocity and variety of data, many STEM educators lack contemporary data literacy skills. Even fewer have training on how to use data in the classroom in a way that is accessible to students and helps them build data literacy skills. This lack of training is more pronounced for community college faculty who do not regularly interact with researchers who develop and use these skills. This project pilots an approach that has the potential to significantly improve undergraduate STEM teaching and learning not only by increasing faculty comfort with systems biology approaches, but also by network participants directly engaging diverse undergraduates in cutting-edge methods in their introductory courses. This approach could serve as a model for future collaborations between research institutes and primarily undergraduate institutions that seek to increase minority recruitment, engagement, retention, and success along STEM pathways.
This project will bring together systems biologists and community college faculty to engage in professional learning experiences that draw on the expertise of both populations. Community college faculty will engage in a week of deep learning of quantitative biology skills supported by the members of the network who are quantitative biology researchers. The full network will then create curricular resources that engage students in data literacy modules to complement classroom based undergraduate research and assist students in building the skills to interpret large multidimensional datasets founded in authentic research contexts. The network will partner to implement these resources in community college courses that serve a broad range of students including populations traditionally underrepresented in STEM fields. The project will improve the preparation of community college students by increasing achievement and learning of quantitative biology research methods and improve undergraduate biology learning environments by enhancing undergraduate faculty teaching of quantitative biology research methods. Further the project outcomes will generate instructional strategies and curricular resources founded in contemporary quantitative biology research and an expanded network of undergraduate biology faculty and scientists at research institutes engaging students in classroom-based quantitative biology research.
This project is being jointly funded by the Directorate for Biological Sciences, Division of Biological Infrastructure, and the Directorate for Education and Human Resources, Division of Undergraduate Education as part of their efforts to address the challenges posed in Vision and Change in Undergraduate Biology Education: A Call to Action (http://visionandchange/finalreport/).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The Networking Systems Biologists with Community College (CC) Educators Project launched in Spring 2021 with the recruitment of 11 CC faculty members from 7 Washington state campuses and 2 scientists from ISB to participate in an 80 hour professional learning experience.
During the first half of the work project staff facilitated ISB scientists to lead CC faculty through a course focused on using quantitative research tools to explore microbiome data. Faculty learned about methods used to analyze large datasets and ways to answer questions involving the large amounts of data involved in looking at complicated biological systems.
For the second half of the work, the project team, CC faculty, and ISB scientists worked together to create modules for each of the three core introduction biology courses taught across Washington?s CC system. One group developed a molecular biology module focusing on the big dataset analysis of microbiomes. Students read a paper looking at analysis of a microbiome dataset and then analyze some additional data from the paper. Another group developed an ecology lab in which students access microbiome data for patients before, during and after antibiotic use and use a Google colab notebook built specifically for student analysis of the data. The animal systems group used BLAST analysis of some proteins to create several phylogenies and used the principle of parsimony to determine which is the most likely explanation. Each module was designed to be implementable in an online format.
During the 2021-22 academic year, participant faculty implemented the activities in online, hybrid, and in person settings. As of August 2022,10 of the participating faculty members have implemented at least one of the 3 designed activities, impacting approximately 300-400 students.
Nine faculty shared their experiences implementing the designed activities and how the experience more broadly impacted their teaching. Faculty expressed overwhelmingly positive reports about the implementation and high confidence in supporting students to develop quantitative biology skills.
Faculty reported that an additional 300 students who were in courses where the activities were not implemented were positively impacted by the increased knowledge of the CC faculty. Specifically, 5 of 9 faculty said their students spent more time? interpreting the biological meaning of results? and ?describing how quantitative reasoning helps biologists understand the natural world?.
Students report engaging in learning activities that help build quantitative literacy. Furthermore, students report gaining quantitative literacy skills related to these activities and exposure to biological data. Students report the most growth in more advanced quantitative skills such as using data to defend and refute claims. Part of the impetus for incorporating current research into these courses was to increase engagement and the relevance of biology to these student?s lives and current scholarship. This seems to have translated as 67% of students felt the topics covered in the course were interesting to them; 72% felt the topics were based on real-world problems, and 59% felt the course helped them build skills that are relevant to other parts of their life.
Based on evaluation data and the experiences of the project team, the following successes and/or challenges have emerged and impacted the design of future programs:
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Learning Timeline: The COVID pandemic revealed the importance and increased accessibility of virtual professional development. Participants in the Project shared that the burnout and the concentrated structure of the project was intense and negatively impacted their learning; they expressed a desire to have more time between the intense learning experiences.
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Professional development structure - As observed by the project team and reported by the participants, one of the most successful components of our professional development was journal clubs, where faculty participants read an article and then discussed the article with one of the authors. This allowed faculty to dive into current research, and helped faculty and scientists develop relationships and connections and engage in meaningful dialogue that varied from science to pedagogy.
Cohort Structure - The cohort for the Incubator Project was 10 faculty, 2 scientists, and project leadership. The structure favored a flow of information from the scientists to the faculty, and placed a significant burden on the scientists as the ?knowledge holders?. A more balanced cohort will relieve some of the burden on the scientists and create opportunities for structured discussions in which all sides hold knowledge that will benefit the group.
Last Modified: 02/02/2023
Modified by: Jennifer Eklund
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