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Summer 2019 Biobytes

this is a series.

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Movement: Nature's Flying Machines

Might use this in ecology.

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Avida-ED Experimental Evolution Project

Outline to a research project based on Avida-ED's digital organisms

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CHORDS Portal: Seamless Real-Time Data Streaming

CHORDS is a real-time data service for the geosciences that provides an easy-to-use system to acquire, navigate, and distribute real-time data via cloud services and the Internet. CHORDS aims to lower the barrier to these services, especially for small instrument teams, and broaden access to real-time data for the geosciences community.

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3D Printed Automated Weather Station (PAWS)

Accurate and reliable real-time monitoring and dissemination of observations of surface weather conditions is critical for a variety of societal applications.

The US National Weather Service (NWS) International Activities Office (IAO) in partnership with University Corporation for Atmospheric Research (UCAR)/National Center for Atmospheric Research (NCAR) and funded by the United States Agency for International Development (USAID) Office of Foreign Disaster Assistance (OFDA) has started an initiative to develop and deploy low-cost weather instrumentation in sparsely observed regions of the world.

Instrumentation is being designed using innovative new technologies such as 3D printers, Raspberry Pi computing systems, and wireless communications.

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Curriculum: Calling Bullshit-The Art of Skepticism in a Data Driven World

Course developed by Carl T. Bergstrom and Jevin West. The aim of the course is to teach you how to think critically about the data and models that constitute evidence in the social and natural sciences.

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B(ui)LDS: Biological, Universal, and Inclusive Learning in Data Science

An EDSIN partner focused on the exchange of ideas and resources supporting biological and environmental data science education, grounded in practices of universal design for learning and inclusive pedagogy. As part of our commitment to accessible, affordable student-driven education that connects learners to a larger world outside of their classrooms, and inspires them to be transformative; we promote the creation and use of Open Educational Resources (openly licensed learning materials), and the incorporation of Open Pedagogy and Open Science into our teaching practices.

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Actually, Data Science CAN Be Accessible: Barriers to inclusion of people with disabilities in the data science workforce pipeline and ideas for lowering them

Presentation by EDSIN member Drew Hasley that draw on personal experience as a student and professional with a severe visual impairment and knowledge gained from colleagues and friends during ongoing efforts in the area of accessible teaching in quantitative biology. This was a keynote presentation at the 2019 EDSIN conference.

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Inclusive Pedagogy for Life Science Education Tagging Ontology

Inclusive pedagogy for life science education tagging ontology developed by EDSIN members Carrie Diaz Eaton, Sharon Rivera, and Bryan Dewsbury

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Brian Dewsbury's Resources on Inclusion

A list of material in various platforms that help to inform developing thoughts on the ways in which social structure affects the nature of teaching and learning.

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Ontology for UDL and Related Content

This is a description of tagging ontology that can be used for Universal Design for Learning (UDL) resources created by EDSIN member Drew Hasley

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STEM Inclusive Teaching Practices Webinar Series: Episode One

Episode One was a conversation with Bryan Dewsbury (University of Rhode Island) one of the authors of the CBE-LSE Inclusive Pedagogy guide moderated by Carrie Diaz Eaton. We talked with him about inclusive teaching practices, and he answered questions about implementation in the STEM classroom. We appreciate that all of our personal and professional lives have been disrupted by the pandemic, so we will also spend time talking about how to think about inclusion in the times of COVID-19.

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Universal Design for Learning Guidelines

The UDL Guidelines are a tool used in the implementation of Universal Design for Learning, a framework to improve and optimize teaching and learning for all people based on scientific insights into how humans learn. Learn more about the Universal Design for Learning framework from CAST. The UDL Guidelines can be used by educators, curriculum developers, researchers, parents, and anyone else who wants to implement the UDL framework in a learning environment. These guidelines offer a set of concrete suggestions that can be applied to any discipline or domain to ensure that all learners can access and participate in meaningful, challenging learning opportunities.

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B(ui)LDS: Biological, Universal, and Inclusive Learning in Data Science

We are a community for the exchange of ideas and resources supporting biological and environmental data science education, grounded in practices of universal design for learning and inclusive pedagogy. As part of our commitment to accessible, affordable student-driven education that connects learners to a larger world outside of their classrooms, and inspires them to be transformative; we promote the creation and use of Open Educational Resources (openly licensed learning materials), and the incorporation of Open Pedagogy and Open Science into our teaching practices.

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Center for Scientific Collaboration and Community Engagement

The Center for Scientific Collaboration and Community Engagement (CSCCE) is a research and training center to support and study the emerging field of scientific community engagement.

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AGU Ethics and Equity Center

The AGU Ethics and Equity Center provides resources to educate, promote and ensure responsible scientific conduct and establish tools, practices, and data for organizations to foster a positive work climate in science. They can help you meet your ethics goals, whether you are an individual scientist looking for resources or professional ethics development, a leader looking to implement best practices at your organization, or an institution wanting to update your code of conduct. The Center is led by AGU.

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Academic Data Science Alliance

The Academic Data Science Alliance (ADSA) was launched in May 2019 to provide an independent national resource network for academic data science leaders, practitioners, and educators to connect and exchange ideas, and to advance the uptake of data science best practices in higher education. ADSA seeks to support university researchers in their efforts to learn, use, and teach data-intensive tools and responsible applications. Our ultimate goal is to bring about the institutional changes needed to integrate data science into university research and training. By building networks of academic data science practitioners (including faculty, students, staff, and administrators), ADSA enables better sharing of knowledge, ideas, and lessons learned.

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CSCCE blog posts and tip sheets on Diversity, Equity, and Inclusion

Diversity, Equity and Inclusion (DEI) should be central considerations when planning and supporting any scientific community. The Center for Scientific Collaboration and Community Engagement's (CSCCE) resources on this topic include blog posts and tip sheets (i.e., inclusive marketing, member recruitment, childcare at scientific meetings, decolonizing international research collaborations) to help you to nurture more inclusive communities. 

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Scientific Meetings for All

A publication in EOS on inclusive scientific meetings that features the 2019 EDSIN conference.

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NSF INCLUDES Coordination Hub

Presenter: Gary Silverstein, Westat and Coordination Hub Team

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National Ecological Observatory Network: Data & Infrastructure to Understand Changing Ecosystems

Presenter: Megan A. Jones, Battelle/NEON  

Abstract: NEON, the National Ecological Observatory Network, is an NSF-funded large science facility, operated by Battelle, is designed to collect extensive ecological and environmental data from across the U.S. for the next 30 years. A primary product of NEON is freely available, open access data for use by the scientific research community as well as by students and others who will explore the petabytes of information that will be available during the lifetime of the Observatory. Using NEON data, however, may not be an easy task for researchers, faculty, and students who are not familiar with “big data” access, management and analytic methods. Many ecologists are transitioning to using data science and big data methods including programming-based data management and analysis, complex data portals and APIs that provide access to lots of different types of data, and diverse analytical methods beyond those classically used in their individual research area. Furthermore, ecological data is usually messy in the sense that variability and uncertainty are important components of data analysis and interpretation. Given these challenges, how do we accelerate the use of big data in ecological research and education? How to we create equitable opportunities for data and resource access to all interested individuals? How do we engage communities that have not traditionally been drawn to careers in ecology but for which data science focused careers may provide new opportunities?

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Summary of the National Academies Report on Data Science for Undergraduates

Presenter: Louis Gross, University of Tennessee  

Abstract: Under the auspices of the National Academies, a Committee developed a consensus report regarding means to enhance undergraduate programs in the emerging discipline of data science. Building upon advice from a variety of on-line and in-person interactions with a broad spectrum of experts, the report provides a collection of findings and recommendations for initiating, developing and evaluating programs that prepare students for careers in data science as well as encouraging methods for all undergraduates to be exposed to basic concepts in this field. I will summarize the suggestions made regarding development of data acumen, incorporation of real-world examples, enhancing teamwork and communication, ethical considerations, and assessment and evaluation of data science programs. I will emphasize the potential for such programs to broaden participation in quantitative science and the benefit of utilizing environmental data and examples that align with the interests of diverse students.

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Make Student Thought Process Visible Using Video Recording

Presenter: Hong Qin, University of Tennessee at Chattanooga

Abstract: Dr. Qin presents his experience of integrate screen-recording to enhance student learning experience of computational biology. Students were required to screen-recording their process of solving computational problems. These screen-recordings can be used to identify the learning hurdles of students and improve student learning experiences.

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Understanding the Dynamics of Socio-Epidemiological Systems

Presenter: Carlos Castillo-Chavez

Abstract: The spread of fads, scientific ideas and the growth and stability of communities can also be understood as contagions. In this talk, I would focus on contagion in all its glory, including its role on building communities of mentors and understanding the role that initial conditions should play in our definition of meritocracy.

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Asset Mapping: A Simple Tool for Recruiting & Retaining Underrepresented Populations in STEM

Presenters: Adrienne Smith, Cynosure Consulting and Rebecca Zulli Lowe, Cynosure Consulting

Abstract: Asset maps serve as a simple, yet impactful tool for helping underrepresented groups connect with important people, programs, and resources that would support their recruitment and retention in STEM. In contrast to a traditional deficit-focused mindset, asset mapping was born out of an approach that seeks out existing strengths and works to build capacity by leveraging current resources as a foundation for further innovation. At the end of this talk, individuals will walk away with a list of steps that they can use to develop a comprehensive map that could be distributed immediately to current and future STEM (including high school seniors). These steps include identifying current assets within an array of existing categories (e.g., tutoring centers, individual faculty mentors, local chapters of STEM associations) designed to help mappers think expansively about existing supports. Additional steps involve reviewing contact lists and asking others to assist in the identification of assets, performing internet searches of the school/organization website looking for key words, and reading through the university directory to highlight offices that work on diversity issues or support the individuals targeted. The assets can be plotted directly onto a campus map and supplied to underrepresented groups, so they are aware of and can locate the resources and supports available to them. Additionally, the formation of the maps can be a beneficial exercise for departments to use to assess their own assets and strategically plan for the development of new assets.

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