FYI about this workshop next month:
https://www.nationalacademies.org/event/09-13-2022/foundations-of-data-science-for-students-in-grades-k-12-a-workshop-days-1-and-2. You will recognize many names, including that of co-chair, Nick Horton.
Steve
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BOARD ON SCIENCE EDUCATION | BOARD ON MATHEMATICAL SCIENCES AND ANALYTICS |COMPUTER SCIENCE AND TELECOMMUNICSTIONS
BOARD
Foundations of Data Science for Students in Grades K–12: A Workshop
September 13–14, 2022
Lecture Room, National Academy of Sciences: In-person and virtual
TUESDAY, SEPTEMBER 13, 2022 (All Times are ET)
Purpose To bring increasing visibility to the rapidly growing field of K-12 data science education, this workshop
will survey the current landscape of work, surface what is currently known, and identify additional
research to support student learning, curriculum and tools development, assessment, and the
preparation of educators. The workshop will bring together researchers and practitioners engaged in K12 data science education from a variety of contexts including formal and informal; designed and
emergent; elementary and secondary; and whose efforts include standalone curricula as well as
activities integrated within other content areas (e.g., STEM disciplines and the humanities).
9:15–10:00 AM Registration and Breakfast
Breakfast will be provided.
10:00–10:05 AM Welcome from the National Academies
Heidi Schweingruber, Director, Board on Science Education
10:05–10:20 AM Opening Remarks and Workshop Framing
Nicholas Horton (Co-chair), Amherst College
Michelle Hoda Wilkerson (Co-chair), University of California, Berkeley
10:20–11:20 AM A Vision for High Quality Data Science Education
This session will explore what defines a valuable learning experience for students, what research tells
us about successful vs. unsuccessful curricular intervention, and how those learnings can be articulated
into policy and practice.
Moderator:
Michelle Hoda Wilkerson, University of California, Berkeley
Panelists:
Rob Gould, University of California, Los Angeles
Josh Recio, Dana Center
Tricia Shelton, National Science Teaching Association
Alfred Spector, Massachusetts Institute of Technology (virtual)
Trena Wilkerson, Baylor University; National Council of Teachers of Mathematics
11:20–11:45 AM Networking Break
Coffee and light refreshments will be provided
CLICK HERE TO JOIN
SEPTEMBER 2022 | 2
Foundations of Data Science for Students in Grades K-12: A Workshop
11:45 AM–12:45 PM Where and How is Data Science Happening?
The goal of this session is to explore the research on the settings and contexts of K-12 data science
education with an emphasis on what data science looks like in these contexts and the connections with
informal contexts relevant to K-12 learners' lives.
Moderator:
Tammy Clegg, University of Maryland
Panelists:
Marshini Chetty, University of Chicago (virtual)
Kayla DesPortes, New York University
Rafi Santo, Telos Learning
Stephen Uzzo, New York Hall of Science
12:45–1:45 PM Working Lunch: What are the Outcomes that We Want?
Lunch will be provided.
During lunch, participants will be broken up into small groups to discuss the outcomes that we want for
data science education. These could be student-level outcomes (e.g., development of specific skills
and proficiencies, developing interest or disciplinary identity) or outcomes related to policy and practice
(e.g., access to opportunities, funding). As part of the discussion, also consider the research that is
needed to further what is known about these outcomes.
1:45–2:45 PM Report Out from Working Groups and Invited Commentary on Outcomes
This session will explore the evidence on what we know about learning and critical data literacy to
identify (and outcomes identified by participants) to consider what it is that we want students to be able
to do with data and identify how those intended outcomes can be measured.
Moderator:
Nicholas Horton, Amherst College
Presenters:
Ryan Seth Jones, Middle Tennessee State University
Jo Louie, Education Development Center, Inc.
Discussant:
Jo Boaler, Stanford University (virtual)
2:45–3:00 PM Break
Coffee and light refreshments will be provided
3:00–4:00 PM How are Tools and Resources Supporting Data Science Learning Experiences?
Through this session, there will be an exploration of the tools and data sets that exist or are needed to
support learning in acquiring data understanding and skills.
Moderator:
Tim Erickson, Epistemological Engineering
Panelists:
Rolf Biehler, Paderborn University, Germany (virtual)
Chad Dorsey, Concord Consortium
Randy Kochevar, Education Development Center
Victor Lee, Stanford Graduate School of Education
Andee Rubin, TERC
SEPTEMBER 2022 | 3
Foundations of Data Science for Students in Grades K-12: A Workshop
4:00–4:25 PM Townhall
What are the highest priorities for additional research?
4:25–4:30 PM Adjournment and Plan for Day 2
Michelle Hoda Wilkerson (Co-chair), University of California, Berkeley
Nicholas Horton (Co-chair), Amherst College
END OF DAY 1
WEDNESDAY, SEPTEMBER 14, 2022 (All Times are ET)
9:15–10:00 AM Registration and Breakfast
Breakfast will be provided
10:00–10:15 AM Welcome and Reflections on Day 1
Michelle Hoda Wilkerson (Co-chair), University of California, Berkeley
Nicholas Horton (Co-chair), Amherst College
10:15–11:15 AM Hearing from Practice: What is Happening in and Out of Schools?
This session will explore the reality on the ground in data science education, with a deep focus on the
specifics of designing student learning opportunities. Topics will include student learning progressions,
opportunities for different school subjects to impart data science topics, and the wrap-around resources
needed for implementation.
Moderator:
Zarek Drozda, Director, Data Science 4 Everyone, University of Chicago
Panelists:
Suyen Machado, University of California, Los Angeles
Stephanie Melville, San Diego Unified School District
Paul Strode, Fairview High School
Katie Headrick Taylor, University of Washington
11:15–11:30 AM Break
Coffee and light refreshments will be provided
11:30AM –12:30 PM How is Data Science Integrated in Content Areas?
This session will explore the ways in which data science has been integrated with other subjects
beyond mathematics. Panelists will share, through discussions of their own and related work,
approaches for integrating data science into the study of other subjects as they are explored across
settings including school-based and out-of-school contexts.
Moderator:
Camillia Matuk, New York University (virtual)
Panelists:
Rahul Bhargava, Northeastern University
Angela Calabrese Barton, University of Michigan
Joshua Radinksy, University of Illinois at Chicago
Emmanuel Schanzer, Bootstrap
SEPTEMBER 2022 | 4
Foundations of Data Science for Students in Grades K-12: A Workshop
Lissa Soep, Vox Media, LLC. (virtual)
12:30–1:30 PM Lunch
Lunch will be provided
1:30–2:30 PM What is the State of Teacher Preparation in Data Science?
The goal of this session is to examine issues on teachers' use of data and the preparation needed to
teach statistics/data science/computation for prospective teachers and practicing teachers in formal
and informal education settings.
Moderator:
Hollylynne Lee, North Carolina State University
Panelists:
Anna Bargagliotti, Loyola Marymount University
Stephanie Casey, Eastern Michigan University
Ann Leftwich, Indiana University Bloomington (virtual)
Gemma Mojica, North Carolina State University
Leticia Perez, WestEd
Joshua Rosenberg, University of Tennessee, Knoxville
2:30–3:00 PM Townhall
How can practice inform current and future research needs?
3:00–3:15 PM Funder Reflection
Nancy Lue, Valhalla Foundation
3:15–3:30 PM Final Reflections from Planning Committee
Nicholas Horton (Co-chair), Amherst College
Michelle Hoda Wilkerson (Co-chair), University of California, Berkeley
3:30 PM WORKSHOP ADJOURNS
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Steve Pierson
Director of Science Policy
American Statistical Association
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