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Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
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Appendix A

Workshop Agenda

Foundations of Data Science for Students
in Grades K–12: A Workshop

All Times are EST.

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 K–12 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).

DAY 1: TUESDAY, SEPTEMBER 13, 2022

10:00–10:05 AM Welcome from the National Academies
Heidi Schweingruber, Director, Board on Science Education
Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
×
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
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
Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
×
the outcomes that we want for data science education. These could be student-level outcomes (e.g., developing 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.
Virtual Audience: We are not facilitating breakout groups. We invite you to share your ideas in this document: Virtual Outcomes. You are welcome to provide your name next to your suggestion, but it is not required. Ideas provided in this document will be incorporated into the next session and will also be available on the project page following the event.
1:45–2:45 PM Invited Commentary on Outcomes and Report Out from Working Groups
This session will explore the evidence on what we know about learning and critical data literacy (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.
Background Readings:
A Secret Agent. K–12 Data Science Learning
Through the Lens of Agency1
Critical Data Literacy: Creating a More Just World with Data2
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

___________________

1 Available at https://www.nationalacademies.org/event/09-13-2022/docs/DD667E469D0EC5DD91A7D85BC839A9852491A3CF9F15

2 Available at https://www.nationalacademies.org/event/09-13-2022/docs/D16254F310D01BBDA873920E4EFB8151F2D8334181AA

Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
×
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.
Background Reading: Tools to Support Data Analysis and Data Science in K–12 Education3
Moderator: Tim Erickson, Epistemological Engineering
Panelists:
  • Rolf Biehler, Paderborn University, Germany (virtual)
  • Chad Dorsey, Concord Consortium
  • Randy Kochevar, Education Development Center, Inc.
  • Victor Lee, Stanford Graduate School of Education
  • Andee Rubin, TERC
4:00–4:25 PM Townhall
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

DAY 2: WEDNESDAY, SEPTEMBER 14, 2022

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

___________________

3 Available at https://www.nationalacademies.org/event/09-13-2022/docs/DB48F8A34F71C395C3071BABFFD42AFFF06478824419

Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
×
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 wraparound resources needed for implementation.
Background Reading: Previewing the National Landscape of K–12 Data Science Implementation4
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
11:30 AM – 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

___________________

4 Available at https://www.nationalacademies.org/event/09-13-2022/docs/D688ED916E82498DA0E2171A109936D679FD5DE26556

Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
×
  • Josh Radinsky, University of Illinois at Chicago
  • Emmanuel Schanzer, Bootstrap
  • Lissa Soep, Vox Media, LLC (virtual)
12:30–1:30 PM Lunch
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
  • Anne 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
3:00–3:15 PM Funder Reflection
Nancy Lue, Valhalla Foundation
Joined by:
  • Ulrich Boser, Schmidt Futures
  • Lark Park, California Education Learning Lab (virtual)
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
Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
×
Page 79
Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
×
Page 80
Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
×
Page 81
Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
×
Page 82
Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
×
Page 83
Suggested Citation:"Appendix A: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K-12: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26852.
×
Page 84
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On September 13 and 14, 2022, the Board on Science Education at the National Academies of Sciences, Engineering, and Medicine held a workshop entitled Foundations of Data Science for Students in Grades K–12. Speakers and participants explored the rapidly growing field of K-12 data science education, by surveying the current landscape, surfacing what is known, and identifying what is needed to support student learning, develop curriculum and tools, and prepare educators. To support these conversations, four papers were commissioned and discussed during the workshop. This publication summarizes the presentations and discussion of the workshop.

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