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    The Power of Data Standards
    Investigate data standards within the context of the Alpine Chipmunk and the Grinnell Study.
    2006

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    544

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    Sorting through the Data
    Meet Thomas McElrath, a insect collection manager at the Illinois Natural History Survey and beetle researcher. Tommy explains the value of data standards while discussing beetles and variations...
    255

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    Rescuing Data: Preserving Data for the Future
    Meet Diane Srivastava, director of the Canadian Institute for Ecology and Evolution, and learn how they sythesize and save biodiversity data.
    418

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    Interactions between Water, Earth’s Surface, and Human Activity
    This two-week (~10-hour) module focuses on water and its importance to humans, both as a limited resource and in shaping Earth's surface.
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    Teacher Guide: Math and Statistics
    Topics include measures of average (mean, median, and mode), variability (range and standard deviation), uncertainty (standard error and 95% confidence interval), Chi-square analysis, student...
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    Food, Energy and Water Learning Modules (FEWLM) Workbooks
    FEWLM is a low-cost inquiry-based interdisciplinary STEM prototypical curriculum built on Next Generation Science Standards, systems thinking and informed engineering design pedagogy.
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    Box of Lessons: A Toolkit for Introducing Students to Biomolecular Structure and Function
    This is a poster describing a collection of open educational resources that were developed by faculty participating in the Molecular CaseNet Faculty Mentoring Network in Spring 2022. The collection...
    418

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    A "Box of Lessons" for Exploring Biomolecular Structure and Function
    Biomolecular structure and function is emphasized as a core concept in a variety of community determined educational standards for biology and chemistry. Most curricula introduce students to the...
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    Advances in Genome Sequencing with Nathan Olson
    In this Lunch with a Scientist episode, we discuss Genome Sequencing and Bioinformatics with National Institute of Standards and Technology (NIST) biologist Nate Olson, Ph.D.
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    Data is the New Science - Modified and combined with Following the Data Module
    In this module, students will be introduced to some emerging biodiversity data resources. They will be asked to think critically about the strengths and utility of these data resources and apply...
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    NSF Final Outcomes Report: Using the Lived Experiences and Narratives of Black Heritage and African American Gullah/Geechee to Learn Science Concepts
    This resource is a public report that provides final outcomes from the NSF funded project award # 1928832. The resources included in this report are outcomes from the catalyst project titled:...
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    562

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    Human Dimensions in Amphibian Conservation: Addressing Threats
    This module introduces students to the theme of human dimensions in conservation and provides them with an opportunity to engage in practices related to social science research.
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    523

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    NEON_PDSI
    Users access and manipulate drought data and visualize these data to learn about historical drought patterns.
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    Data Ethics
    Data ethics and the use of digital data
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    640

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    Remote sensing data processing – NEON airborne data
    Concepts of remote sensing and data logistics, and NEON remote sensing data are introduced. Students learn how to apply spatial data processing and visualization skills using R coding program to...
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    Data Visualization
    This is an introduction to the idea of data visualization and the importance of presenting data for understanding.
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    668

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    Introductory Data Science Pipeline Activity – Yellow Fever and Global Precipitation
    Students follow the steps of a tiny data science project from start to finish. They are given a research question "Are the number of cases of yellow fever associated with global average...
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    Data Management in Excel and R using National Ecological Observatory Network's (NEON) Small Mammal Data
    Students use small mammal data from the National Ecological Observatory Network to understand necessary steps of data management from data collection to data analysis by re-organising excel sheets...
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