The following sessions will be offered on Monday, July 24. Sessions will be 2 hour long, hands on introductions to resources and pedagogical approaches. There will be three rounds of sessions (10:30am, 2:00pm, 6:30pm) and many of the presenters will be available throughout the week.
Avida-ED: An artificial life platform for teaching evolutionary principles and how to "do" science
Date & Time:
Monday, July 24th
Participants in this session will learn how to implement the artificial life platform, Avida-ED (avida-ed.msu.edu), in their classrooms. We’ll begin by describing the Avida-ED curriculum that we implemented in an Introductory Cell and Molecular Biology course at Michigan State. Avida-ED was used primarily in the teaching lab, in parallel with a bacterial antibiotic resistance experimental research stream, allowing students to draw connections between Avidian evolution and the evolution of antibiotic resistance in microbial populations. Using Avida-ED. participants will complete a short set of exercises, each focused on teaching particular evolutionary concepts, that we used to familiarize students with Avida-ED. We’ll then describe independent Avida-ED research projects carried out by our students using Avida-ED. These activities will provide the basis of a discussion about how workshop participants might implement Avida-ED lessons and/or research projects in their own courses. We’ll also present education research results showing how Avida-ED use relates to student learning of evolutionary concepts and science process skills.
For more information about Avida-ED click here.
Integrative Cases for Evolution Education
Date & Time:
Monday, July 24th
Many teachers find evolution difficult topic to teach and many students find evolution a difficult topic to learn. Part of this difficulty stems from the complexity of the evolutionary process that requires knowledge spanning across biological subdisciplines to fully understand. In 2012, the Evo-Ed (http://www.evo-ed.org) project was launched, introducing resources to help educators teach evolution using integrative examples of trait evolution. Pre- and post-course assessments indicated that students who learned evolution in this context were more able to explain the molecular basis of mutation, describe how mutations lead to phenotypic change and make mechanistic links between genotypes and phenotypes. In this interactive BioQUEST workshop session, participants will learn about the integrative cases of trait evolution. By the end of the session, participants will be able to implement one or more integrative case in a classroom setting. Stemming from this session, we hope to identify faculty who are interested in helping to build new cases and/or build investigative problem spaces for one or more of the cases.
For more information about Evo-Ed click here.
The ESTEEM collection: Computational tools to support modeling and analysis of biological systems at the introductory level and beyond.
Date & Time:
Monday, July 24th
In this session, I will introduce the Biological ESTEEM Collection, an online suite of Excel-based modules that facilitate mathematical exploration of a wide range of biological concepts. These modules are designed to guide early learners step-by-step through the reasoning that underlies a particular model or analysis, while advanced users can modify the default calculations to better reflect the actual features of a given biological system. Today, we will focus on two modules: (1) Island Biogeography, in which students determine which biotic and/or abiotic factors best predict species diversity in discrete habitat patches; and (2) SIR BuildIt, in which students first model the spread of a generic infectious disease, then refine the model to reflect more precisely the properties of a specific disease of their choice.
Using R in the Classroom
Do you use R for research but are overwhelmed by the idea of teaching it in the undergraduate classroom? This workshop will focus on the benefits and challenges of using the statistical software R in undergraduate biology or biostatistics courses. We will discuss topics such as: How can you teach software without sacrificing content? Should R be taught as a statistical tool or is that ignoring its power as a programming language?
In this workshop, we will go through a hands-on example of incorporating R in an undergraduate introductory biology or biostatistics course, first collecting data in a ‘beanbag biology’ exercise that promotes intuitive understanding of statistical distributions, then using R to visualize, explore, and analyze the data. We will then discuss some of the pedagogical and implementation issues, and also share a variety of materials for teaching with R, using an introductory biostatistics course and a simple infectious disease modeling seminar as focal courses.
This session will be most helpful for current R users, people who are already somewhat comfortable in R, or people who know other programming languages/command line software and are willing to familiarize themselves with R ahead of time. If you are brand new to R, please consider taking Jason William’s Data Carpentry session before this one.
Workshop session page: https://qubeshub.org/groups/teaching_r/siworkshop
Data Nuggets: Bringing authentic research and data in the classroom to unearth students’ quantitative and inquiry skills
Data Nuggets are targeted classroom activities focused on developing quantitative skills for K-16 students. They bring cutting edge science and data into the classroom, helping students develop a deeper understanding of quantitative reasoning in the context of science. In addition, scientists can use Data Nuggets to share their research with broad audiences. Each Data Nugget includes a dataset from real contemporary research for students to graph, interpret, and use when constructing an explanation.
In this session, participants will learn strategies to best utilize this valuable classroom resource and have the opportunity to develop a Data Nugget of their own. With a focus on climate change data, we will provide access to an online source of freely available published data that can be used in classroom inquiry projects. We will guide participants through development of a Data Nugget with this dataset, modelling a classroom experience where students ask their own questions, use data to support their claim, and create a report to communicate their findings. Data Nuggets produced during this session will be hosted on our website (http://datanuggets.org/search-current-data-nuggets/) and on QUBES Hub (https://qubeshub.org/groups/datanuggets). Alternatively, participants are invited to bring data from their own research. If you choose to write a Data Nugget from your own research, please come prepared with the data selected, analyzed, and a research question in mind. We will be available throughout the Summer Institute to assist participants in revising and refining their Data Nuggets.
Beagle Investigations Return with Darwinian Data
Date & Time:
Monday, July 24th
The Galapagos Islands have been an important natural laboratory for evolution research for over 175 years. The archipelago contains over 40 islands that very in size, habitats and inhabitants. The islands are home to the Galapagos finches (a.k.a. Darwin's finches) which stand as one of the most widely recognized examples of research in evolutionary biology. The 13 species of finches have subtle variations in their beak morphology and behavior that reflect their divergence and ecological specialization.
Too often the Galapagos Finches are presented as a canonical example of evolution without providing students with the opportunity to engage with data or the types of reasoning that biologists use to make sense of their similarities and differences. This problem space provides a collection of introductory materials and data resources designed to support students as they reason about the evolutionary relationships between the species.
BIOMAAP: Biology Students Math Anxiety and Attitudes Program
The current quantitative reasoning skills of our students, and their willingness to engage withnew quantitative content, can be key roadblocks in teaching modeling in the undergraduate biology classroom. Students’ mathematics anxiety and lack of confidence can lead to decreased performance, in a cycle where students with negative math experiences are then reluctant to engage with new quantitative content, leading to further negative experiences. Fortunately, explicit strategies to increase student comfort with quantitative content can help students successfully engage with the use of mathematical models in biology. Much of the recent biology education reform has emphasized conveying the value of quantitative skills to our students (i.e. the central role computation, statistics, and modeling play in modern scientific discovery), in the hopes that this will increase student motivation. However, student motivation is not dependent solely on valuing the task. The other key component is expectancy: how likely is one to succeed at this task?
In this workshop, participants will experience a variety of short, easily adoptable materials to address mathematics attitudes in biology students by increasing students’ expectations of success. These materials were developed for the NSF-funded Biology Students Math Anxiety and Attitudes Program (BIOMAAP). The general approaches include fostering a growth mindset, using metacognition (thinking about their own process of doing math) to refine student efforts, avoiding stereotype threat, and developing foundational numeracy skills. We will also provide a brief background on the different approaches and current evidence of their effectiveness. The materials are targeted at introductory undergraduate biology courses, but are not biology-content-specific and are thus appropriate for a range of introductory and upper division undergraduate courses. Materials include both out-of-class and in-class activities that can be led by an instructor or peer mentor, and actively engage students in reducing their own mathematics anxiety and improving their attitudes toward mathematics.
An Invitation to Modeling: Exploring the process of science through the process of modeling
Do you teach Hardy Weinberg Equilibrium? Do your students understand how this model is used to explore biological concepts? We, as an interdisciplinary group of biologists, mathematicians, and education researchers, have been using this model, ubiquitous in biology curricula, as an example of how to introduce biology students to the process of modeling. In this session, we will lead participants through a HWE hands-on activity that we have developed to make the process of modeling explicit, helps the students connect and reflect upon what they learn in math and biology courses, and gives it context that enriches learning. From this, we hope that participants will suggest further ways that this modeling framework can enrich the teaching of other models in biology.
To the Double Helix and Beyond: Exploring DNA Structure and Function in 3D
The double helical model of the structure of DNA (Deoxyribonucleic acid), published in 1953, revolutionized biology. Watson and Crick developed this model by integrating key experimental findings from chemistry, physics and biology. The model immediately suggested mechanisms for genetic information storage and use of the genetic blueprint of life, leading to the central dogma of biology. Today, using interdisciplinary approaches we continue to explore and understand the subtleties of DNA structure and function that enable storage of information, exquisite regulation of individual genes in response to various signals from within and outside the cells, and much much more. Understanding DNA structure and function has also inspired scientists to engineer and design new molecules that do not exist in nature.
This workshop will begin with a hands-on demonstration of how Watson and Crick developed the double helical model of DNA and take the story forward to the first few X-ray structures of DNA. In the remainder of the workshop participants will interactively explore the structures of DNA and its various complexes using the RCSB Protein Data Bank website (www.rcsb.org), tools, and resources to learn about DNA structure and function. In addition to visualizing structures online, participants will also make paper models of DNA that they can use for teaching and discussions about DNA. Educational materials, and the foundations for various case studies will be made available. We hope to encourage faculty to develop case studies and/or exercises that teachers and students around the world can use to learn about nucleic acids and proteins in 3D.
For more information about DNA and related Educational resources go to pdb-101.rcsb.org and search for DNA in the top search-box.
HHMI BioInteractive offers a wealth of resources for teaching how to analyze data. Our particular strength is in combining engaging media that tell compelling science stories with ready to use data analysis activities using real data. If you need to teach fundamental statistical analysis, you will find many tools at our main website including Excel spreadsheet tutorials, a guide to basic statistics, and an interactive tutorial for developing an intuitive understanding of sampling, normal distribution, and standard error of the mean. Our advanced resources are also available from HHMI BioInteractive QUBES page, that was developed by the Faculty Mentoring Network from last year. Some of our resources can be found on our partner sites at Science in the Classroom and The National Center for Case Study Teaching in Science. At the end of our session, we invite you to discuss ideas for how to make our resources fit introductory biology courses better, and suggestions on what content we can develop to fill a need.
“Beanbag” biology: feelings count!
Example exercise: Infection in a cup
Date & Time:
Monday, July 24th
While we all agree that math and quantitative thinking is critical for biology majors, biology curricula at most institutions remain resolutely math-free. The reason is often the lifelong fear or distaste for mathematics of many biology majors, which is often intentionally reinforced by biology faculty. Much of this fear and distaste arises from the abstract nature of mathematics, and the challenge of building the intuition of how mathematics applies to biology. Based on the long history of BioQuest and my own experience, I have found that the best steps for helping biologists develop an understanding of the role of math in biology include: (1) physical manipulatives, (2) computer simulations, (3) derivation of mathematical relationships from core principles, and (4) analysis of real data sets (Jungck et al. 2010). This workshop will focus solely on the first element, physical manipulatives. Manipulatives help learners break through prior fears and then develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology. Adding manipulatives to quantitative teaching is the biological equivalent of a laboratory portion of the course.
Two main concerns that are often voiced as challenges to implementing the use of manipulatives is that the tasks are often game-like, and some students will consider the tasks to be beneath them. Additionally, the use of physical props seems antiquated in comparison to modern computer gaming. However, it is interesting that neither of these concerns is applied to the labs that are frequently used to teach introductory biology! There the tried and true methods for teaching the scientific method, the core concepts of biology, etc., include the use of some of the exact same experiments today that emeriti professors did in their undergraduate days!
This workshop will focus on teaching the use of manipulatives by working through the exercises. Additionally, there will be discussion about the appropriate courses and sections that each could be applied. Finally, we will conclude with a discussion of the mathematics needed for each exercise and how these topics can be provided to the math faculty for use in the required mathematic classes.
Jungck, J. R., Gaff, H., & Weisstein, A. (2010). Mathematical manipulative models: In defense of “beanbag biology” CBE Life Sciences Education, 9, 201–211.
Evolution in Action: Using Models to Explore the Molecular Basis of Insecticide Resistance
Date & Time:
Monday, July 24th
This workshop will use a variety of models (available for loan from the MSOE Model Lending Library) to explore how random variations within a gene result in a phenotype of insecticide resistance in mosquitoes. We will use a case study approach that will enforce a conceptual understanding of a variety of topics in the context of preventing the spread of Zika virus:
- polar nature of water
- protein structure
- how proteins fold
- enzymes, substrates and inhibitors
- enzyme specificity
- stability and variability of DNA
- degenerate nature of the genetic code
- introduction to bioinformatics
- basics of enzyme kinetics
- natural selection
We will explore these topics as we discuss the use of insecticides that target acetylcholinesterase, the enzyme that recycles the neurotransmitter acetylcholine. We will also utilize molecular landscapes created by David S. Goodsell to place the molecular machines we discuss in the context of their location within the body. Throughout the workshop we will address the value of hands-on, minds-on physical models in uncovering student conceptions and taking them to the next level of understanding, as well as effective ways of incorporating models in the classroom.
For more information about the Center for BioMolecular Modeling, go to: http://cbm.msoe.edu/
Students Modeling Like Scientists
Date & Time:
Monday, July 24th
At last summer's Lowering the Activation Energy: Making Quantitative Biology more Accessible meeting, Jeremy Wojdak’s and Erin Bodine’s presented a workshop on modeling with Netlogo. Netlogo has been around for quite some time but I think the focus Vision and Change and the AP Biology Curriculum Framework provides a new and exciting instructional design space to explore. Perhaps the most difficult challenge in biology education is getting our students to ask questions instead of simply accumulating facts. Thinking about models and working with models is a particularly effective strategy to help students develop the skill of asking scientific questions.
From Epstein, Joshua M. "Why model?." Journal of Artificial Societies and Social Simulation 11.4 (2008): 12:
"Models can surprise us, make us curious, and lead to new questions. This is what I hate about exams. They only show that you can answer somebody else's question, when the most important thing is: Can you ask a new question? It's the new questions (e.g., Hilbert's Problems) that produce huge advances, and models can help us discover them."
This workshop we will continue the work started last summer to examine how Netlogo classroom applications can address the challenges defined in Vision and Change and the AP Biology Curriculum Framework. We will explore models that can help students to develop deeper content understandings in each of the five Vision and Change Core Concepts along with the analogous 4 Big Ideas in the AP Biology Curriculum. Modeling is particularly well suited to helping students develop both content understanding and scientific thinking skills. We will work on strategies and lessons where students will learn to model like scientists either by reporting model results in a manner similar to reporting experimental results or by analyzing reported model results and reconciling these results with empirical data.
The goals for this workshop include:
- Describe the educational benefits of agent-based model simulation as well as the importance of agent based models to scientific inquiry.
- Demonstrate a beginning familiarity working with agent-based models in Netlogo along with the ability to utilize the special tools built into Netlogo that facilitate scientific inquiry.
- Develop strategies and plans through participant discussion to implement Netlogo instruction in both laboratory settings and during content instruction for each of the four Big Ideas in Biology.
- Collect and analyze data from a Netlogo simulation use the behavioral tools and a spreadsheet.
- Identify other models from the extensive Netlogo Model library that may have an application in their classroom.