ThinkUDL is a podcast about Universal Design for Learning where we hear from the people who are designing and implementing strategies in post-secondary settings with learner variability in mind.

Project EDDIE is beginning a new round of teaching material development to help connect large-scale sensor data into undergraduate classrooms. Join the community of authors creating materials that engage students with authentic data to improve quantitative reasoning and develop big-data skills.

The Smithsonian Institution Data Science Lab (datascience.si.edu) housed within the Office of the Chief Information Officer (SI-OCIO) in Washington, DC, is seeking two postdoctoral fellows to conduct independent research and digital humanities scholarship in collaboration with the United States Holocaust Memorial Museum and the Smithsonian American Women’s History Initiative.

The Data Science Lab was recently formed in response to the dramatic increase in all forms of digital data across the Smithsonian (19 museums, 9 research centers, and a zoo). We seek to build collaborations both across Smithsonian units, as well as universities and other institutions. Members of our group work on a variety of data-intensive research topics, including biodiversity genomics and machine learning applications of digitized museum collections.

Please see https://datascience.si.edu/digital-humanities-postdoctoral-fellowships for details, and email (SI-DataScience@si.edu) or tweet (@SIDataScience) with questions!

The Earth Lab Earth Analytics Education Initiative at the University of Colorado -- Boulder is building an innovative program that provides core in-market demand technical skills at the intersection of Earth and data science to undergraduate, graduate and professional students. The program includes formal courses, workshops, career development events with industry partners, paid undergraduate internships, an open online learning portal with global reach, and a professional certificate in Earth data analytics, one of the first of its kind in the country. We are committed to expanding the reach of Earth data science education for students across varying academic, professional, socio-economic and geographic dimensions to ensure broad accessibility to novel curriculum. All courses are offered through both online and traditional options, allowing students to participate in-person, online in real-time, or asynchronously by reviewing materials at their own pace. 

Series of blogs by Matt May, Adobe's head of inclusive design. 

Links to a Google slide presentation by CAST representatives on designing accessible Open Educational Resources. 

Several links to guides and lists of resources for accessible teaching from the DO-IT Center out of the University of Washington.

Suggestions for using visuals and references based in the principles of universal design. Practices are provided and hosted by DeafTEC.

A PDF with guidelines for creating dyslexia-friendly PowerPoint presentations from York St John University

NVDA is an open source software screen reader. Their site has information about its development, help guides, and a free download. 

Create a free account at CAST to access this book, Universal Design for Learning: Theory & Practice

Entry Point!, a signature program of the AAAS Project on Science, Technology and Disability, is a national effort to discover and develop talent among undergraduate and graduate students with disabilities who demonstrated a talent and interest in pursuing a STEM career. The primary goal of the project is to increase the diversity of the scientific and engineering workforce at the professional level.

The Foundation for Science and Disability (FSD) was founded in 1975 as a non-profit organization to promote the integration of scientists with disabilities into all activities of the scientific community and of society as a whole and to promote the removal of barriers that hinder success of students with disabilities in pursuit of scientific careers.  FSD is affiliated with AAAS and offers a graduate student grant program.

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.

Author: Gregg Hartvigsen

    "Taught at a workshop on network analysis using R at the national Institute for mathematical and Biological Synthesis at the University of Tennessee, Knoxville."

Published: February 18, 2014 by Columbia University Press

Summary: This book guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types.  Hartvigsen covers testing data for normality, defining and identifying outliers, and working with non-normal data.  Students are introduced to common one- and two-sample tests as well as one- and two-analysis of variance (ANOVA), correlation, and linear and non-linear regression analyses. Also included is a secion on advanced procedures and a chapter inroducing algorithms and the art of programming using R.

For a preview of this book, click here

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Author: Andrew P. Beckerman, Owen L. Petchey

    "Evolutionary Ecologists with over 20 years of combined experience using R for data analysis and visualization"

Published: July 22, 2012 by Oxford University Press

This book provides a fundamental introduction for biologists new to R.  While teaching how to import, explore, graph and analyze data, it keeps readers focussed on their ultimate goals-communicating their data in oral presentations, posters, papers, and reports.  It also provides a consistent workflow for using R that is simple, efficient, reliable, accurate, and reproducible.  The material in the book reproduces the engaging and sometimes humorous nature of the three-day course on which it is based.

For a preview of this book, click here

For purchase through Amazon

Author: Andy Hector

    " He currently convenes and teaches statistics on the Quantitative Methods for Biologsits course for undergraduates at the Universtiy of Oxford.  He has contributed to several publications on eccologal analysis."

Published: March 15, 2015 by Oxford University Press

Summary: This book provides a contemporary introduction to the classical techniques and modern ectensions of linear model analysis.  It emphasizes on estimation-based approach that accounts for recent criticisms of over-use of probability values and introduces the alternative approach using information criteria.  It is based on the use of the open-source R programming language for statistics and graphics that is rapidly becoming the lingua franca in many areas of science.  Statistics is introduced through worked analyses preformed in R using interesting data sets from ecology, evoluntionary biology, and environmental science.  Data sets and R scripts are available as supporting material.

For a preview of this book, click here

For chapter summaries, click here

For purchase through Amazon

QUBES site for the NWBC group. To learn more about NWBC.

Powerpoint slides used during the SABER West 2019 "Scaffolding Core Competency Learning Outcomes across the Undergraduate Biology Curriculum" workshop.

Reference sheet from the workshop. Adapted from 2011 Vision and Change report by Stasinos Stavrianeas.