Fostering parent–child dialog through automated discussion suggestions
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11257_2016_Article_9176.pdf
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1.01 MB
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770c237adbab8c8aef03cbc545676d49
Author(s)
Boteanu, Adrian
Chernova, Sonia
Nunez, David Scott
Breazeal, Cynthia Lynn
Date Issued
July 2016
Journal
User Modeling and User-Adapted Interaction
Publisher
Springer Netherlands
Citation
Boteanu, Adrian, Sonia Chernova, David Nunez, and Cynthia Breazeal. “Fostering Parent–child Dialog through Automated Discussion Suggestions.” User Modeling and User-Adapted Interaction 26, no. 5 (July 22, 2016): 393–423.
Version
Author's final manuscript
Abstract
The development of early literacy skills has been critically linked to a child’s later academic success. In particular, repeated studies have shown that reading aloud to children and providing opportunities for them to discuss the stories that they hear is of utmost importance to later academic success. CloudPrimer is a tablet-based interactive reading primer that aims to foster early literacy skills by supporting parents in shared reading with their children through user-targeted discussion topic suggestions. The tablet application records discussions between parents and children as they read a story and, in combination with a common sense knowledge base, leverages this information to produce suggestions. Because of the unique challenges presented by our application, the suggestion generation method relies on a novel topic modeling method that is based on semantic graph topology. We conducted a user study in which we compared how delivering suggestions generated by our approach compares to expert-crafted suggestions. Our results show that our system can successfully improve engagement and parent–child reading practices in the absence of a literacy expert’s tutoring.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1007/s11257-016-9176-8
