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Data and Art: Data Science in Elementary

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Colorado Convention Center, Bluebird Ballroom Lobby, Table 5

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Presenters

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STEAM Teacher
South Fayette Township School District
@MelissaUnger15
ISTE Certified Educator
Melissa Unger teaches elementary STEAM and computer science at the South Fayette School District near Pittsburgh, Pennsylvania. Winner of the 2021 Carnegie Science Center Most Inspiring Educator award, and a 2023 finalist for the Pennsylvania Teacher of the Year, Melissa is passionate about STEM education and providing all students the opportunity to be creators, designers, and coders.
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South Fayette School District
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Technology Literacy Teacher 3-5
South Fayette Intermediate School
@SFIS_STEAMlab
Shad Wachter teaches technology literacy to students in grades 3-5 at South Fayette Intermediate School in McDonald, PA. Since 1999, he has been a band director, technology assistant, STEAM teacher and technology literacy teacher. Always willing to share his experiences and learn from others, Shad has presented at various regional, state, national, and international conferences. He also has provided professional development in teaching computational thinking to young coders, most recently to schools in rural Kentucky. His curriculum is comprised of keyboarding, digital citizenship, block based computer programming, and desktop publishing. He considers himself to be an innovation integrator.

Session description

Learn how to introduce K-5 students to data science! By engaging in school-wide activities, creating graphs, and analyzing their results, South Fayette students are becoming "data artists" as they begin to acknowledge how data impacts their lives and the many ways they can represent data using art.

Purpose & objective

Participants will leave this poster presentation with a deeper understanding of what Data Science can look like at the K-5 level, as well as with a knowledge of resources that they can use (books for teachers and for students, and materials developed for South Fayette students that can be modified to fit different contexts). After attending this presentation, participants will be able to identify times in their school day where students/teachers are already collecting data and how those instances can be expanded upon to include conversations about data science.

To engage participants, I will have both photos/videos of data science work being done at South Fayette Elementary, and also, physical samples of students' projects so that participants can see what K-5 students are capable of achieving with data science.

Explanations of how students move from gathering to analyzing data, and then representing data through visual art will be detailed for participants. A timeline of what this process looks like through out the year at different grade levels will be provided, as well as examples of how we are evaluating students for understanding.

This presentation will be considered a success if participants leave the conversation interested in learning more about data science at the elementary level and if they can begin to identify areas in their school routines where data science could be introduced.

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Outline

The main focal points of my poster session will be:

1. Focusing on how data science is introduced at different elementary grade levels and what that might look like with concrete examples of activities.
2. Explaining how students go from gathering data to analyzing it, with attention to how students can use data to draw specific conclusions.
3. Showing students' visual representations made using data and combining it with physical art.

I will speak with each attendee, but they will also have access to QR codes that lead to students' projects/reflections, and some of our classroom materials (handouts).

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Supporting research

Boaler, J. (2015). Mathematical mindsets [EPUB]. Jossey Bass Wiley.

Boaler, Jo. (2022). Seeing Is Achieving: The Importance of Fingers, Touch, and Visual Thinking to Mathematics Learners. 10.7551/mitpress/13593.003.0015.

LaMar, Tanya & Boaler, Jo. (2021). The importance and emergence of K-12 data science. Phi Delta Kappan. 103. 49-53. 10.1177/00317217211043627.

Murphy Paul, Annie. “The Coding Revolution.” Scientific American Aug. 2016:42-49. Online and Print.

Rondinelli, Bille, Dr., and Aileen M. Owens. “Computational Thinking.” AASA May 2017: 23-27. Print and Online.

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Session specifications

Topic:
Computer science & computational thinking
Grade level:
PK-5
Skill level:
Beginner
Audience:
Teachers, Curriculum/district specialists, Library media specialists
Attendee devices:
Devices not needed
Participant accounts, software and other materials:
None
Subject area:
Computer science, STEM/STEAM
ISTE Standards:
For Students:
Knowledge Constructor
  • Students plan and employ effective research strategies to locate information and other resources for their intellectual or creative pursuits.
Computational Thinker
  • Students collect data or identify relevant data sets, use digital tools to analyze them, and represent data in various ways to facilitate problem-solving and decision-making.
Creative Communicator
  • Students communicate complex ideas clearly and effectively by creating or using a variety of digital objects such as visualizations, models or simulations.