WIP: Bridging the Data Gap - Introducing Unplugged Data Science

This innovative practice paper outlines a design-based research study to enhance data science literacy in students using an unplugged approach. With the rapid growth of data and its impact on daily life, there's a need for new educational methods to help students understand and use data effectively. Data science involves math, statistics, computation, AI, and machine learning, but teaching these concepts can be challenging without access to computers or the internet, potentially widening educational inequities. Inspired by unplugged computer science education, this study supports data science education in unplugged classrooms. Initial research focused on creating and testing two learning units on data visualization and summarization using innovative activities and reflection prompts. Analyzing students' work from a pilot with ten eleventh-graders in a low-income public school in a Global South country, the study aims to understand how these activities support data visualization skills and identify limitations. Future work will develop and implement lesson plans to promote data and AI literacy, aiming to make data science education more inclusive across diverse backgrounds.

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Publication Details

Published
2024-10-13
DOI
https://doi.org/10.1109/fie61694.2024.10893521
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00

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article

WIP: Bridging the Data Gap - Introducing Unplugged Data Science

Jennifer L. Chiu, Camilo Vieira, Mariana Arboleda
Artificial Intelligence in Healthcare
article

WIP: Bridging the Data Gap - Introducing Unplugged Data Science

Jennifer L. Chiu, Camilo Vieira, Mariana Arboleda
article en

Abstract

This innovative practice paper outlines a design-based research study to enhance data science literacy in students using an unplugged approach. With the rapid growth of data and its impact on daily life, there's a need for new educational methods to help students understand and use data effectively. Data science involves math, statistics, computation, AI, and machine learning, but teaching these concepts can be challenging without access to computers or the internet, potentially widening educational inequities. Inspired by unplugged computer science education, this study supports data science education in unplugged classrooms. Initial research focused on creating and testing two learning units on data visualization and summarization using innovative activities and reflection prompts. Analyzing students' work from a pilot with ten eleventh-graders in a low-income public school in a Global South country, the study aims to understand how these activities support data visualization skills and identify limitations. Future work will develop and implement lesson plans to promote data and AI literacy, aiming to make data science education more inclusive across diverse backgrounds.

Virginia Department of Education (US), Universidad del Norte (CO), University of Virginia (US)
University of Virginia
Openalex Percentile: Top 62%
Artificial Intelligence in Healthcare
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