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The QUBES platform hosts hundreds of teaching materials, reference materials, and cloud-based software free to use and adapt using open Creative Commons licenses.

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    DataCamp
    DataCamp: The Easiest Way to Learn Data Science Online

    Keywords: statisticsRcurriculumdata visualizationdata scienceonline learningcoursemachine learningpythonlab protocol

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    Visualizing Global CO2 Emissions
    Using CO2 emissions data, students will learn how to visualize data with Tableau Public. The teaching materials are suitable for upper-level undergraduate courses on data analysis and research...

    Keywords: data visualizationResource Typeclimate change dataTableau

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    Database Construction and Sampling
    Creating your own database is an excellent way for students to learn the trials and tribulations of data collection and management. Construction of three simple databases using a spreadsheet is...

    Keywords: databasesdata managementdata collectiondata ethicsdata integrity

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    Speed Data Science
    Data visualization is a foundational data science skill. One way to help students begin to learn about data visualization is to tap in to their innate creative instincts. This activity can be used...

    Keywords: data visualizationdata science educationlife sciences

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

    Keywords: data in the classroomdata standardsdigitized natural history collectionsBLUE Fall 2019 FMNGrinnell

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    Communicating with Data: Digital Data Resources
    Students access, clean, configure, and standardize a dataset and create a relevant and scientifically valid data visualization to communicate science.

    Keywords: data in the classroomdata visualizationdigital resourcesbiodiversity informaticsbiodiversity collections

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    UW Data Science for Social Good program
    The UW Data Science for Social Good (DSSG) program partners eScience Data Scientists and Student Fellows from across the country with Project Leads from academia, government, and the private sector...
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    DataONE Module 03: Data Management Planning
    Benefits of a data management plan (DMP), DMP components, tools for creating a DMP, NSF DMP information, and a sample DMP.

    Keywords: moduledatain-class activityHandoutproblem setdata managementDataONEPresentation

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    Data Management using National Ecological Observatory Network's (NEON) Small Mammal Data with Accompanying Lesson on Mark Recapture Analysis
    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 estimating small mammal...

    Keywords: data managementspreadsheetssmall mammals community dynamicsNEONCapture mark-recaptureResource TypeNational Ecological Observatory Network

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    National Ecological Observatory Network: A Data Source For Your Classroom
    Poster on the National Ecological Observatory Network and using NEON data and resources in your classroom presented at the 2018 QUBES/BioQUEST Summer Workshop

    Keywords: fmnNEONSummer Workshop 2018

    1438

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    Data Science Replication of Covid-19 Wastewater Tracking
    Students are asked to use data science skills (such as pivot tables and linear regression) to replicate Covid-19 wastewater monitoring data provided by the CDC NWSS (National Wastewater...

    Keywords: public healthdata science skills trainingEnvironmental Data ScienceEpidemiology Infectious Diseases

    108

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    Changes in Lake Ice: Ecosystem Response to Global Change
    Data Set included in included in Teaching Issues and Experiments in Ecology (TIEE) Volume 3

    Keywords: Resources @ ESA - TIEE

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    National Ecological Observatory Network: A Data Source For Your Classroom
    Poster on NEON resources for use in research and education presented at the 2019 BioQUEST & QUBES Summer Workshop.

    Keywords: faculty mentoring networksNEONNational Ecological Observatory Network

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    Serenity now! Keep calm and do science with real data in the classroom
    Session presented at NABT 2018 in San Diego, CA

    Keywords: NABTdata scienceeducational technologytool:serenitydata acumendata life cycle

    1514

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    137

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    Science “Fails”: A Bank of Historical Examples for Learning From Failure in Science
    Learning from failure is critically important to the processes of scientific inquiry, discovery, and invention. However, students are not routinely taught how to reflect on, learn from, and...

    Keywords: metacognitionScience process skillsLearning from failurepower and privilegestudent wellbeing

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    50 Years of Data Science
    This paper reviews some ingredients of the current “Data Science moment”, including recent commentary about data science in the popular media, and about how/whether Data Science is really...

    Keywords: statisticsbig datadata sciencemachine learning

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    Examining human impacts on tusk evolution in elephants using authentic research data
    In this activity students explore and analyze real, authentic research data paired with HHMI’s “Selection for Tuskless Elephants” video in a hands-on investigation of human impacts on elephant...
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    MS Excel Refresher - Lizards, iguanas, and snakes! Oh my! | Data Nuggets
    This resource, a MS Excel refresher, extends the level for this Data Nugget. Students are given an Excel workbook with the data and asked to graph and calculate diversity using Excel functions...

    Keywords: Resources @ Data NuggetsspreadsheetsRestoration EcologyUsing Excelgraphing in Excelformulas in ExcelApplied ecology

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    1-018-LogisticPopModel-ModelingScenario
    We offer artificial (toy) and historical data on limited growth population situations in the study of protozoa and lead students through several approaches to estimating parameters and determining...

    Keywords: data analysisparameter estimationlogisticCiliate protozoapopulationlimited growthparameciaGause

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    Why, when, and how to cite sources of biodiversity specimen data
    This short video and assessment explain why we as scientists should cite our data sources and how we can do this for sources of biodiversity specimen data.
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