2026-09-20T09:49:08Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1228942024-04-02T12:53:58Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Cynthia Breazeal.
Williams, Randi (Scientist in media arts and sciences)
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
2019-11-12T17:42:16Z
2019-11-12T17:42:16Z
2018
https://hdl.handle.net/1721.1/122894
1126790206
Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018
"June 2018." Cataloged from PDF version of thesis.
Includes bibliographical references (pages 97-104).
Today's children are growing up with artificial intelligence (AI) devices such as voice personal assistants, home robots, and internet connected "smart" toys. In previous research, we have seen that children lack understanding of how modern Al devices work, making it difficult for them to engage in reflective and constructive interactions with the Al-enabled technology (Druga, Williams, Breazeal, & Resnick, 2017). This thesis explores how young children explore and create with Al, and how such activities influence children's perceptions of Al and their attitudes about themselves as engineers. First, I discuss the design of PopBots -- the first hands-on toolkit developed for children ages 4-6 to explore and learn about Al. The social robot serves as both a programmable artifact as well as a window into understanding the machine learning algorithms. Accompanying this toolkit, I also developed a novel, developmentally-appropriate Preschool-Oriented Programming (POP) curriculum. The PopBots curriculum expands existing computational thinking curriculums by using creative learning activities to teach children three core Al concepts: rule-based systems, generative Al, and supervised machine learning. Next, I evaluated the PopBots toolkit and curriculum with 80 pre-K and Kindergarten aged children from local schools. I found that young children can understand most of the Al concepts presented in the toolkit, but sometimes developmental factors like grade and Theory of Mind skills made a difference. After completing the PopBots curriculum, children developed an understanding of robots as "learning" machines. They also gained confidence in their ability to build their own robots. Overall, this work provided a highly engaging opportunity for children to explore robotics, Al and programming -- and ultimately see Al-based technology as something they can play a role in not just using but also creating.
by Randi Williams.
S.M.
S.M. Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences
125 pages, 14 unnumbered pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Program in Media Arts and Sciences
PopBots : leveraging social robots to aid preschool children's artificial intelligence education
Pop Bots : leveraging social robots to aid preschool children's artificial intelligence education
Leveraging social robots to aid preschool children's artificial intelligence education
Thesis
application/pdf
2019-11-12T17:42:15Z
Publication
Master
Media
unknown
unknown
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<Abstract>Today's children are growing up with artificial intelligence (AI) devices such as voice personal assistants, home robots, and internet connected "smart" toys. In previous research, we have seen that children lack understanding of how modern Al devices work, making it difficult for them to engage in reflective and constructive interactions with the Al-enabled technology (Druga, Williams, Breazeal, & Resnick, 2017). This thesis explores how young children explore and create with Al, and how such activities influence children's perceptions of Al and their attitudes about themselves as engineers. First, I discuss the design of PopBots -- the first hands-on toolkit developed for children ages 4-6 to explore and learn about Al. The social robot serves as both a programmable artifact as well as a window into understanding the machine learning algorithms. Accompanying this toolkit, I also developed a novel, developmentally-appropriate Preschool-Oriented Programming (POP) curriculum. The PopBots curriculum expands existing computational thinking curriculums by using creative learning activities to teach children three core Al concepts: rule-based systems, generative Al, and supervised machine learning. Next, I evaluated the PopBots toolkit and curriculum with 80 pre-K and Kindergarten aged children from local schools. I found that young children can understand most of the Al concepts presented in the toolkit, but sometimes developmental factors like grade and Theory of Mind skills made a difference. After completing the PopBots curriculum, children developed an understanding of robots as "learning" machines. They also gained confidence in their ability to build their own robots. Overall, this work provided a highly engaging opportunity for children to explore robotics, Al and programming -- and ultimately see Al-based technology as something they can play a role in not just using but also creating.</Abstract>
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