Sunday, September 4, 2016

Petrosino and Others Invited to NSF Funded 2016 Youth Data Science Summit- University of California, Berkeley

Youth Data Science Summit 2016 Participants
On August 11-12 2016 the University of California, Berkeley’s Graduate School of Education and School of Information co-hosted the Youth Data Science Summit 2016. Funded by the NSF Cyberlearning and Future Learning Technologies program (award abstract #1541676), the Summit brought together researchers from different communities already active in this emerging field, to promote cross dialogue between those working in computer science/information visualization and in education. I was glad to have been part of this incredible meeting.

This meeting brought together researchers from different communities. Spaces were limited and acceptance was decided in consultation with the advisory board, with the goals of building a diverse group that represents many related fields relevant to youth, learning, and data science.

Confirmed Participants
Meryl Alper – Northeastern University
Toi Sin Arvidsson* – Columbia University
Dani Ben-Zvi – The University of Haifa, Israel
Cynthia Carter Ching – University of California, Davis
Catherine Cramer – New York Hall of Science
David Custer – Math Teacher/Department Chair at Decatur High School
Sayamindu Dasgupta* – Massachusetts Institute of Technology
Noel Enyedy – University of California, Los Angeles
Tim Erickson – eeps media
Kristin Fontichiaro – University of Michigan
Rogers Hall – Vanderbilt University
Jim Hammerman – STEM Education Evaluation Center (SEEC) at TERC
Katie Headrick Taylor – University of Washington
Jennifer Kahn* – Vanderbilt University
Ruth Kermish-Allen – Maine Mathematics and Science Alliance
Janet Kolodner – The Concord Consortium
Leilah Lyons – UIC/ New York Hall of Science
Fred Martin –  University of Massachusetts Lowell
Amelia McNamara – Smith College
Dawn Nafus – Intel
Deborah Nolan – University of California, Berkeley
Anthony Petrosino – University of Texas, Austin
Thomas Philip – University of California, Los Angeles
Laurie Rubel – City University of New York
Mayumi Shinohara* – Vanderbilt University
Lissa Soep – Youth Radio
David Weintrop* – Northwestern University
Advisory Board
Marti Hearst – University of California, Berkeley
Ruth Krumhansl – EDC, Inc / Oceans of Data Institute
Richard Lehrer – Vanderbilt University
Andee Rubin – TERC
Kathryn Lanouette* – University of California, Berkeley
Victor Lee – Utah State University
Tapan Parikh – University of California, Berkeley
Joseph Polman – University of Colorado, Boulder
Michelle Wilkerson – University of California, Berkeley
John Park* – University of Texas, Austin
Anthony Petrosino – University of Texas, Austin
*Graduate Students/ Candidates


The Cyberlearning and Future Learning Technologies Program funds efforts that will help envision the next generation of learning technologies and advance what we know about how people learn in technology-rich environments. Cyberlearning Capacity (CAP) Projects focus on expanding and strengthening the cyberlearning community and often include conferences, workshops, or short courses. This project focuses on a workshop exploring the application of data science to K-12 education. It is motivated by the importance that reasoning with data has in today's world.

The workshop is entitled Data Science, Learning and Youth: Connecting Research and Creating Frameworks. Its objective is to move the educational implications of Data Science to the forefront of conversations among the cyberlearning research community. A large number of undergraduate and post-graduate programs are presently focusing on imparting data skills and computational reasoning. This workshop will extend this focus to K-12 education. It will bring together established and emerging scholars interested in Data Science Education from fields including Learning Sciences, Human-Computer Interaction and Computer Science, Mathematics and Statistics Education, Science Education, and Community Engagement and Citizen Science, and practitioners from K-12 settings. This workshop will foster new interdisciplinary collaborations and expose researchers interested in Data Science Education to relevant communities, literatures, and projects. The short term goal is to enable these communities to synthesize emerging findings, frameworks, and theories and better understand what tools, activities, and environments can support Data Science literacy. Our long term goal is to foster the development of a unified research community interested in Data Science Education. Direct outcomes of the workshop will include concrete plans to produce articles and synthesis documents focused on Data Science Education during the year immediately following the workshop. These documents will speak to three broad and complementary audiences: researchers, through the proposal of a special issue of a scholarly journal; practitioners, through two practitioner-oriented articles focusing on mathematics and science education; and the broader Cyberlearning community, through an online Synthesis Statement to be hosted by the Center for Innovative Research in Cyberlearning (CIRCL) resource website.