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Doodlebot: An Educational Robot for Creativity and AI Literacy

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Author(s)
Williams, Randi
•
Ali, Safinah
•
Alcantara, Raúl
•
Burghleh, Tasneem
•
Alghowinem, Sharifa
•
Breazeal, Cynthia
Date Issued
March 11, 2024
Publisher
ACM
Citation
Williams, Randi, Ali, Safinah, Alcantara, Raúl, Burghleh, Tasneem, Alghowinem, Sharifa et al. 2024. "Doodlebot: An Educational Robot for Creativity and AI Literacy."
Version
Final published version
Abstract
Today, Artificial Intelligence (AI) is prevalent in everyday life, with emerging technologies like AI companions, autonomous vehicles, and AI art tools poised to significantly transform the future. The development of AI curricula that shows people how AI works and what they can do with it is a powerful way to prepare everyone, and especially young learners, for an increasingly AI-driven world. Educators often employ robotic toolkits in the classroom to boost engagement and learning. However, these platforms are generally unsuitable for young learners and learners without programming expertise. Moreover, these platforms often serve as either programmable artifacts or pedagogical agents, rarely capitalizing on the opportunity to support students in both capacities. We designed Doodlebot, a mobile social robot for hands-on AI education to address these gaps. Doodlebot is an effective tool for exploring AI with grade school (K-12) students, promoting their understanding of AI concepts such as perception, representation, reasoning and generation. We begin by elaborating Doodlebot's design, highlighting its reliability, user-friendliness, and versatility. Then, we demonstrate Doodlebot's versatility through example curricula about AI character design, autonomous robotics, and generative AI accessible to young learners. Finally, we share the results of a preliminary user study with elementary school youth where we found that the physical Doodlebot platform was as effective and user-friendly as the virtual version. This work offers insights into designing interactive educational robots that can inform future AI curricula and tools.
Description
HRI ’24, March 11–14, 2024, Boulder, CO, USA
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial
https://creativecommons.org/licenses/by-nc/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/154052
DOI of Published Version
https://doi.org/10.1145/3610977.3634950
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