Keeping Data Science Broad: Workshop on Negotiating the Digital and Data Divide

Many research universities are already developing comprehensive data science programs at the undergraduate and graduate levels. As the movement to develop data science programs grows, a gap appears to be forming that separates the research institutions from primarily undergraduate-focused institutions (i.e. teaching institutions, community colleges, minority-serving institutions, etc.), which are mostly absent and unheard in the movement to develop data science programs. The workshop on Negotiating the Digital and Data Divide will explore the Data Divide issue by bringing together stakeholders from teaching institutions, community colleges, tribal colleges, and minority serving institutions experiencing the divide, and will discuss challenges related to capacity building and capability. These discussions will also address developing data literacy and Data Science acumen; training data science practitioners, and translational data science. A mixed-format of virtual participation in webinars and a 2-day in-person workshop event will allow this workshop to maximize the in-person time spent on discussion and to ensure that participants come to the table well informed of the potential challenges and issues. The goal of the workshop is to enable researchers and educators to understand and to begin to address questions on how to best prepare institutions to teach the data science students of 2025 and to prepare them for the “data-intensive” and “data-enabled” society, economy, and job market of 2025 and beyond.




COMMUNITY INPUT

The workshop itself is by Invitation-Only, but please feel free to join us for the open webinars (described below) and provide your perspective on these important topics. Also, contribute to the discussion and consensus report by completing the community input form below.

COMMUNITY INPUT LINK




There will be two pre-workshop webinars (open to the public) that will cover:

Data Science Education in Traditional Contexts | Aug 31, 2017| 12:00-1:30 PM EST

This webinar will highlight universities, teaching institutions, community colleges, and minority-serving institutions that have implemented data science education undergraduate programs as case studies for workshop participants to consider and compare to their own contexts.

Watch Live HERE!

Webinar Panelists: http://bit.ly/2w5se3S

Paul Anderson - College of Charleston

Gene Ray - Kennesaw State University

Mary Rudis - Great Bay Community College

Karl Schmitt - Valparaiso University

Pei Xu - Auburn University

Alternative Avenues for Development of Data Science Education Capacity | Sept 22, 2017| 12:00-1:30 PM EST

This webinar will highlight efforts that build data science education capacity outside of the context of tradition curricular program development. This may include integration of data science into courses and curricula outside of the traditional CS/math/stats context (i.e. Arts and Humanities), expansion of capacity by integration of third party or shared resources (i.e. MOOCs and open source educational resources) into curricula, and additional educational options outside of traditional courses (i.e. Faculty training, Data Science for Social Good Programs, and Bootcamps).

Watch Live HERE!

Lior Shamir - Lawrence Technical University

Tracy Teal - Data Carpentry

Stephen Uzzo - New York Hall of Science

Al Herron - The Breakfast Group

Sarah Stone - Data Science for Social Good



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