Summary: Increasing user diversity is a key component of maintaining and expanding digital collections. Diverse users are more engaged, and engage in ways that are both novel and serendipitous - often creating uses for our data that the curators couldn't imagine. However, increasing our user base can also serve another goal - providing an entrance ramp for people who maintain views, locations, and life histories that are underrepresented in our ranks. Here my colleagues and I demonstrate how digital collections can help lower barriers to participation across multiple axes, including cost, location and disability status. Our goal in highlighting this is to show the broader impacts of our work, and how through helping people understand biological diversity we can help improve the diversity within our own community.

Presenter: Dr. Joshua Adam Drew from the Department of Ecology, Evolution and Environmental Biology, at Columbia University.

Summary: Increasing user diversity is a key component of maintaining and expanding digital collections. Diverse users are more engaged, and engage in ways that are both novel and serendipitous - often creating uses for our data that the curators couldn't imagine. However, increasing our user base can also serve another goal - providing an entrance ramp for people who maintain views, locations, and life histories that are underrepresented in our ranks. Here my colleagues and I demonstrate how digital collections can help lower barriers to participation across multiple axes, including cost, location and disability status. Our goal in highlighting this is to show the broader impacts of our work, and how through helping people understand biological diversity we can help improve the diversity within our own community.

Presenter: Dr. Joshua Adam Drew from the Department of Ecology, Evolution and Environmental Biology, at Columbia University.

Abstract:

Although bioinformatics is becoming increasingly central to research in the life sciences, bioinformatics skills and knowledge are not well integrated into undergraduate biology education. This curricular gap prevents biology students from harnessing the full potential of their education, limiting their career opportunities and slowing research innovation. To advance the integration of bioinformatics into life sciences education, a framework of core bioinformatics competencies is needed. To that end, we here report the results of a survey of biology faculty in the United States about teaching bioinformatics to undergraduate life scientists. Responses were received from 1,260 faculty representing institutions in all fifty states with a combined capacity to educate hundreds of thousands of students every year. Results indicate strong, widespread agreement that bioinformatics knowledge and skills are critical for undergraduate life scientists as well as considerable agreement about which skills are necessary. Perceptions of the importance of some skills varied with the respondent’s degree of training, time since degree earned, and/or the Carnegie Classification of the respondent’s institution. To assess which skills are currently being taught, we analyzed syllabi of courses with bioinformatics content submitted by survey respondents. Finally, we used the survey results, the analysis of the syllabi, and our collective research and teaching expertise to develop a set of bioinformatics core competencies for undergraduate biology students. These core competencies are intended to serve as a guide for institutions as they work to integrate bioinformatics into their life sciences curricula.

Course resources from the Genomics Education Partnership

Drew and Tripplett 

J Microbiol Biol Educ. 2008; 9(1): 3–11. 

Published online 2008 Dec 17. 

PMCID: PMC3577148

PMID: 23653818

This blog post by Parul Pandey has a nice description of the resources available around the Google "What-if Tool". 

What-If Tool is an interactive visual tool that is designed to investigate the Machine Learning models. Abbreviated as WIT, it enables the understanding of a Classification or Regression model by enabling people to examine, evaluate, and compare machine learning models. Due to its user-friendly interface and less dependency on complex coding, everyone from a developer, a product manager, a researcher or a student can use it for their purpose.

Be sure to see the essay titled, "Playing with AI Fairness" by David Weinberger which talks about using the What-if tool environment to "try on five different types of fairness". I found it to be an accessible introduction to the different approaches to making real world decisions with ML tools. 

A roadmap to recent developments in teaching data science

In this blog, we’re hoping to create a roadmap for faculty development that will ease the learning curve and help busy people incorporate new tools and approaches into their teaching.

Each day during the summer we intend to add a new entry on a given topic, along with a short overview of why it is interesting and how it can be applied to teaching. We intend to make the entries short, succinct, and easy to comprehend with the goal that they will motivate you to dive deeper. 

Read more about this blog ...

There is also an associated Google Group where some discussions are occurring. 

This is the handout from Kristin Jenkins' talk.

The MathJax Consortium is a joint venture of the American Mathematical Society (AMS) and the Society for Industrial and Applied Mathematics (SIAM) to advance mathematical and scientific content on the web.

Core Goals

The core of the MathJax project is the development of its state-of-the-art, open source, JavaScript platform for display of mathematics. Our key design goals are

• high-quality display of mathematics notation in all browsers
• no special browser setup required
• support for LaTeX, MathML and other equation markup directly in the HTML source.
• an extensible, modular design with a rich API for easy integration into web applications.
• support for accessibility, copy and paste and other rich functionality
• interoperability with other applications and math-aware search.

A workshop held on March 14-16, 2018, in Washington, DC explored the changing opportunities and risks of data management and use across disciplinary domains. The third workshop in a series, participants gathered to examine advisory principles for consideration when developing international research agreements, in the pursuit of highlighting promising practices for sustaining and enabling international research collaborations at the highest ethical level possible. The intent of the workshop was to explore, through an ethical lens, the changing opportunities and risks associated with data management and use across disciplinary domains—all within the context of international research agreements. This publication summarizes the presentations and discussions from the workshop.

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

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.

Guide from York St John University on making PowerPoints more accessible for people with dyslexia. 

A collection of suggestions for Universal Design approaches in various educational settings, from Pat Marsteller.

DeafTEC provides resources for high schools and community colleges that educate deaf and hard-of-hearing students in STEM-related programs.

These guidelines offer a set of concrete suggestions that can be applied to any discipline or domain to ensure that all learners can access and participate in meaningful, challenging learning opportunities.

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!