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The following Speakers will be presenting at various times throughout the week at the Summer Workshop. Check back often for updates. 


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Keynote Speaker

Lou Gross

university of tennessee knoxville

Sunday, July 23

7:30 pm

Description:

Louis J. Gross is a James R. Cox and Alvin and Sally Beaman Distinguished Professor of Ecology and Evolutionary Biology and Mathematics and Director of The Institute for Environmental Modeling at The University of Tennessee, Knoxville. He was Founding Director of the National Institute for Mathematical and Biological Synthesis, a National Science Foundation-funded center to foster research and education at the interface between math and biology. He completed a B.S. degree in Mathematics at Drexel University and a Ph.D. in Applied Mathematics at Cornell University, and has been a faculty member at UTK since 1979. His research focuses on applications of mathematics and computational methods in many areas of ecology, including disease ecology, landscape ecology, spatial control for natural resource management, photosynthetic dynamics, and the development of quantitative curricula for life science undergraduates. He led the effort at UT to develop an across trophic level modeling framework to assess the biotic impacts of alternative water planning for the Everglades of Florida.

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Hybrid Labs: Integrating Experiments and Computational Models to Support Scientific Reasoning

Julia Gouvea

Julia Gouvea

tufts logo

Monday, July 24

9:15 am

Description:

In this talk I will describe a "hybrid" approach to introductory biology laboratories in which students integrate organismal experiments with population-level simulations. I will present data to illustrate how students are using simulations to inform their experimental designs and interpret their experimental results. As students move back and forth between the two approaches they engage in reasoning about the biological system: integrating across levels and considering the stability and context-sensitivity of their claims. I argue that hybrid labs have the potential to transform both what students do in introductory labs as well as how they think about what it means to do science.

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Creating an inclusive learning environment

Ahna Skop

ahna skop

uw madison logo

Tuesday, July 25

9:15 am

Description:

Have you ever wondered what it is like to grow up in a family of artists and then end up a scientist? What does thinking like an artist offer the scientist? Can the blending of art and science encourage a more diverse population of students to pursue science, and improve the public understanding of science? Ahna will give you an exciting glimpse into her life and how she has impacted science, education and the public with her two passions: science and art. 

http://genetics564.weebly.com/

http://skoplab.weebly.com/

https://stemdiversity.wisc.edu/

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Conceptual Modeling in Undergraduate Biology: Revealing Thinking to Inform Learning

Tammy Long

tammy long

msu logo

Wednesday, July 26

9:15 am

Description:

Research in the learning sciences tell us that effective instruction engages students in the activities, cognitive behaviors, and ways of thinking exemplified by practitioners in a discipline. Although few would argue the relevance of models and modeling in the practice of biology, many perceive the implementation of model­based instruction in undergraduate classrooms as a formidable challenge. Large class sizes, diverse preparation of students, resource constraints, and limited training in model-based pedagogy are just some of the barriers cited by faculty as reasons for avoiding modeling practice in their courses.

In this presentation, we will: (1) describe a ‘no-tech’ conceptual modeling approach we have used as a way to teach, learn, and assess students’ understanding about biological systems, (2) provide an overview of the theory and evidence underpinning our approach, and (3) discuss research findings that are informing our understanding of how students are learning biology through modeling.

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Calling Bullshit: A Gateway to Quantitative Literacy

Carl Bergstrom

bergstrom

university of washington logo

Thursday, July 27

9:15 am

Description:

The world is awash in bullshit. Politicians are unconstrained by facts. Science is conducted by press release. Higher education rewards bullshit over analytic thought. Startup culture elevates bullshit to high art. Advertisers wink conspiratorially and invite us to join them in seeing through all the bullshit — and take advantage of our lowered guard to bombard us with bullshit of the second order. The majority of administrative activity, whether in private business or the public sphere, seems to be little more than a sophisticated exercise in the combinatorial reassembly of bullshit 

We're sick of it. It's time to do something, and as educators, one constructive thing we know how to do is to teach people. So we designed a course entitled “Calling Bullshit in the Age of Big Data”. Therein we aim to help students navigate our bullshit-rich environment by teaching them to identify bullshit, see through it, and defuse it with effective analysis and argumentation. The course was not only a huge hit on campus, but went viral among teachers and students nationwide. In this talk I will present an overview of the course and describe what we learned from teaching it. 

http://callingbullshit.org

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Frameworks for fusing data assimilation into undergraduate quantitative biology education

John Zobitz

zobitz

augsburg

Thursday, July 27

1:30 pm 

Description:

Data validates and challenge key assumptions and paradigms for process-based, statistical, and phenomenological models of biological systems. Data assimilation is one approach that systematically "fuses" both biological data with mathematical models, providing a cohesive framework for analysis of biological data. My objective of this presentation is threefold: (1) introduce concepts and terminology of data assimilation, (2) convince you that data assimilation develops both breadth and depth of mathematical knowledge, thereby providing translatable skills for biologists in this era of "big data biology" and (3) illustrate where data assimilation can be meaningfully integrated into undergraduate mathematics courses to support quantitative biology undergraduate education.

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