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    Wikipedia in the Science Classroom
    Despite research suggesting that writing-to-learn exercises (WTL) in the classroom are associated with increased student learning, WTL is still not widely implemented in science courses. To provide...
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    Design Your Own Flow Cytometry Experiment: A Four-Week Inquiry Laboratory
    Due to its importance to the field, flow cytometry should be one of the hallmark methods a student learns in the lab portion of an undergraduate immunology course. Flow cytometry is a classic lab...
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    Data Ethics
    Data ethics and the use of digital data
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    Introduction to Python for Data Science Course
    Free Introduction to Python for Data Science Course at DataCamp
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    Phenology publications
    Collection of modifications to TIEE phenology module from Data Discovery FMN

    Keywords: phenology

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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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    Yeast Cell Growth
    Numbers Count resource using Excel for data analysis
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    Data from: Agent-based and Individual-based Modeling: A Practical Introduction, Chapter 5, Section 5.5 [Elevation]
    Elevation data input file for Section 5.5 (tab-separated plain text).
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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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    Earth Analytics in Python Course
    Earth analytics is an intermediate, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of...
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    Summer 2019 Biobytes
    This series includes the four Biobytes that were piloted at the 2019 BioQUEST / QUBES Summer Workshop titled, “Evolution of Data in the Classroom: From Data to Data Science”.
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    Statistical Exploration of Climate Data
    In this module the students will learn some basic concepts in statistical thinking about data, with emphasis on exploratory data analysis.
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    Morphological and Molecular Analysis of Plant Phylogeny and Diversity
    In this lab, students perform phylogenetic analyses on morphological and molecular data, and compare.
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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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    A new approach to course-based research using a hermit crab-hydrozoan symbiosis
    There are few feasible models for marine-focused inquiry laboratory activities, a notable shortcoming for instructors seeking to engage their students in meaningful, course-based research...
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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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    Harnessing the Power of the Immune System: Influenza Vaccines
    Because most people have been infected by and/or immunized against influenza, students should know how the immune system responds to the infection and how vaccines protect against disease. Vaccines...
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    3-017-StackedCoffeeFiltersFalling-ModelingScenario
    Data on free falling 2, 4, 6, and 8 stacked coffee filters is offered. Students form a model using a resistance term proportional to velocity, velocity squared, or velocity to some general power....
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    Serenity now! Keep calm and do science with real data in the classroom
    Session on using real data in the classroom with Serenity, a platform-independent browser-based interface to data science tools for the classroom.
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    A Beginner's Guide To Sampling Rockpools
    In this guide, we'll teach you how to sample rockpools, collect data, make visuals from data, and interpret data in order to see if any correlations exist.
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