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  1. The Human Microbiome Biodiversity  in Health and Disease

    The Human Microbiome Biodiversity in Health and Disease

    2021-02-18 00:40:41 | Teaching Materials | Contributor(s): Angela Peña-Gonzalez, Emily Weigel | doi:10.25334/C094-BX29

    The students will analyze the human gut and vaginal microbiomes in healthy and diseased states using diversity of bacteria as determined by 16SrRNA sequence.

  2. Big Data, Graphs, and Prediction

    Big Data, Graphs, and Prediction

    2021-02-17 14:53:13 | Teaching Materials | Contributor(s): Jennifer Lyon Adler, David Simon, Emmanuel des-Bordes, Joseph Esquibel, mary miller, Pradip Raj Aryal, Vickie Flanders | doi:10.25334/6QDH-4T19

    In this activity, students are introduced to graphing and modeling data in a step-wise fashion. Real data of covid-19 deaths over time are used to incrementally ask students to fit the data to several models and discuss which model fits best.

  3. Lichens in Diverse Landscapes: EREN-NEON Flexible Learning Project

    Lichens in Diverse Landscapes: EREN-NEON Flexible Learning Project

    2021-02-12 22:18:19 | Teaching Materials | Contributor(s): Leah Dudley | doi:10.25334/JTBQ-3392

    This project makes use of publicly-available datasets on lichen presence and abundance and wet deposition, paired with geospatial data on air quality, tree canopy cover, and locally collected field data, to better understand how lichens respond to changes

  4. Why Cells Change Weight: Demonstrating Linear Regression Through an Osmosis Experiment

    Why Cells Change Weight: Demonstrating Linear Regression Through an Osmosis Experiment

    2021-02-10 16:21:46 | Teaching Materials | Contributor(s): Ashley Lamb Galloway, Stefanie L Holmes, Ashley Morgan, Mary Ann Sexton | doi:10.25334/1RT8-WF54

    In this activity, students will perform an experiment utilizing dialysis tubing to create cellular models to demonstrate the linear relationship between cell weight and time in varying tonicities. Videos and data sets (of faculty results) are provided for

  5. The Evolution (and Coevolution) of Flowering Plants Virtual Classroom

    The Evolution (and Coevolution) of Flowering Plants Virtual Classroom

    2021-02-05 23:41:35 | Teaching Materials | Contributor(s): Anna Monfils, Debra Linton | doi:10.25334/RT9Q-4V46

    In this lab, you will explore the diversity of flower and fruit adaptations that have evolved to accomplish pollination and seed dispersal and you will investigate the coevolution of angiosperms and their pollinators.

  6. HF Bates Mid Year Progress Report

    HF Bates Mid Year Progress Report

    2021-02-02 17:21:59 | Teaching Materials | Contributor(s): Robin Taylor | doi:10.25334/7HG6-2A86

    Mid-year highlights of the Hewlett Foundation Grant Award to Bates College: Supporting more equitable and sustainable open education across STEM

  7. STEM OER Accessibility Framework and Guidebook

    STEM OER Accessibility Framework and Guidebook

    2021-01-25 20:16:44 | Teaching Materials | Contributor(s): Cynthia Jimes, Amee Evans Godwin, Sean Fox, Anastasia Karaglani, Nick Lobaito | doi:10.25334/ERXF-AH09

    This framework, developed by ISKME in partnership with SERC, provides a practical reference for curators and authors of STEM OER, with 23 accessibility criteria, or elements, to reference as they curate, design and adapt materials to be accessible.

  8. Biostatistics using R: A Laboratory Manual

    Biostatistics using R: A Laboratory Manual

    2021-01-23 00:32:53 | Teaching Materials | Contributor(s): Raisa Hernández-Pacheco, Alexis A Diaz | doi:10.25334/EWZM-NS95

    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language to biology majors.

  9. Data Management in Excel and R using National Ecological Observatory Network's (NEON) Small Mammal Data

    Data Management in Excel and R using National Ecological Observatory Network's (NEON) Small Mammal Data

    2021-01-13 22:15:54 | Datasets | Contributor(s): Marguerite Mauritz, Sarah McCord | doi:10.25334/N1K0-HM25

    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 in an R-compatible format and doing basic analysis in R

  10. The Ames Test

    The Ames Test

    2021-01-08 14:40:35 | Teaching Materials | Contributor(s): Nathan Goodson-Gregg, Elizabeth A. De Stasio | doi:10.25334/P18R-F263

    Introduction to the Ames Test, published as GSA Learning Resource

  11. Yeti or not: Do they exist?

    Yeti or not: Do they exist?

    2020-12-31 22:20:57 | Teaching Materials | Contributor(s): Keith Johnson, Adam Kleinschmit, Jill Rulfs, William (Bill) Morgan | doi:10.25334/GDSW-P773

    Through this 4-part bioinformatics case study, students will be led through the forensic analysis of putative Yeti artifacts based on published findings.

  12. Closing the Gap in the Open Educational Resources (OER) Life Cycle for Using Research Data in the Ecology Classroom

    Closing the Gap in the Open Educational Resources (OER) Life Cycle for Using Research Data in the Ecology Classroom

    2020-12-30 17:56:21 | Teaching Materials | Contributor(s): Kristine Grayson, Kaitlin Bonner, Arietta Fleming-Davies, Ben Wu, Raisa Hernández-Pacheco | doi:10.25334/YCJ8-W154

    Poster presented at the 2018 meeting of the Ecological Society of America on gaps in the curriculum cycle for open educational resources (OER) and our work supporting sharing and adaptation of data-centric teaching resources for ecology classrooms

  13. Reflective Writing Tools: Building Skills and Habits of Thinking in Becoming a Scientist

    Reflective Writing Tools: Building Skills and Habits of Thinking in Becoming a Scientist

    2020-12-25 05:06:18 | Teaching Materials | Contributor(s): Sally Molloy, William Davis, Elizabeth Moy, GC Jernstedt, Melinda Harrison, Vinayak Mathur, Matthew David Mastropaolo | doi:10.25334/2PD1-NT03

    Reflective writing tools are intended to help students better connect current learning experiences to prior learning, engage the role of emotion in current and future learning, and assess learning experiences to improve future learning.

  14. Investigating Evidence for Climate Change (Project EDDIE) with CO2 and 13CO2 data: adapted for R

    Investigating Evidence for Climate Change (Project EDDIE) with CO2 and 13CO2 data: adapted for R

    2020-12-23 23:08:55 | Teaching Materials | Contributor(s): Marguerite Mauritz | doi:10.25334/ZTBT-CF45

    This is an adaptation to work in R of Investigating Evidence for Climate Change (Project) by Hage, M. 2020. Students will investigate geologic and modern evidence for global temperature and atmospheric CO2 change using ice-core data and Mauna Loa records.

  15. Chapter 11: Correlation and regression analyses

    Chapter 11: Correlation and regression analyses

    2020-12-23 19:28:18 | Teaching Materials | Contributor(s): Raisa Hernández-Pacheco, Alexis A Diaz | doi:10.25334/GWFH-C377

    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language. Chapter 11 introduces correlation and regression analyses.

  16. Chapter 10: Two-way analysis of variance

    Chapter 10: Two-way analysis of variance

    2020-12-23 19:25:08 | Teaching Materials | Contributor(s): Raisa Hernández-Pacheco, Alexis A Diaz | doi:10.25334/HYHZ-GX44

    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language. Chapter 10 introduces the two-way analysis of variance.

  17. Chapter 9: One-way analysis of variance

    Chapter 9: One-way analysis of variance

    2020-12-23 19:23:15 | Teaching Materials | Contributor(s): Raisa Hernández-Pacheco, Alexis A Diaz | doi:10.25334/5892-ZK23

    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language. Chapter 9 introduces the one-way analysis of variance.

  18. Chapter 8: Comparing two means: the t-test

    Chapter 8: Comparing two means: the t-test

    2020-12-23 19:21:27 | Teaching Materials | Contributor(s): Raisa Hernández-Pacheco, Alexis A Diaz | doi:10.25334/TZXB-HY86

    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language. Chapter 8 introduces the Student's t-test.

  19. Chapter 7: The normal distribution

    Chapter 7: The normal distribution

    2020-12-23 19:18:47 | Teaching Materials | Contributor(s): Raisa Hernández-Pacheco, Alexis A Diaz | doi:10.25334/V6P0-A283

    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language. Chapter 7 introduces the normal distribution.

  20. Chapter 6: Population proportions and the binomial distribution

    Chapter 6: Population proportions and the binomial distribution

    2020-12-23 19:16:57 | Teaching Materials | Contributor(s): Raisa Hernández-Pacheco, Alexis A Diaz | doi:10.25334/XK24-NT12

    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language. Chapter 6 introduces the binomial distribution.