Digital media technologies have been extensively utilized in children's daily lives and many researchers, educators, caregivers, and developers have been interested in finding ways to utilize these technologies in educational settings to facilitate early cognitive development. Among a wide range of media technologies, the accessibility of voice assistants and smart speakers powered by Artificial Intelligence (AI) has notably increased. However, there is a paucity of knowledge about how this advanced technology can be used to teach young children important mathematical concepts during shared book reading. The current study aimed to examine whether and under what circumstances shared book reading with an AI voice agent would enhance preschool-aged children's learning of mathematical language, a critical domain-specific language highly associated with early numeracy skills and vocabulary development.
Sixty-six participants who were recruited for home-visit and school-visit sessions were randomly assigned to one of three reading conditions to read a storybook with the AI voice agent three times: math storybook reading with dialogic questions, math storybook reading without dialogic questions, and non-math storybook reading with dialogic questions. The findings indicate that shared math storybook reading supports children's target mathematical language learning differently based on their initial understanding of numeracy skills. Children with higher levels of numeracy skills demonstrated greater benefits from simply listening to the story, whereas children with lower levels of numeracy skills showed a tendency to learn better when hearing questions and feedback from the AI voice agent. This study provides implications for the use of advanced technology involving social interaction to support children's learning of key mathematical language that can benefit from repeated reading. / Doctor of Philosophy / Digital media technologies have been widely used in children's daily lives and many researchers, educators, caregivers, and developers have been interested in finding ways to utilize these technologies in educational environments to support children's early cognitive development. Among a wide range of media technologies, more and more families with young children have access to smart speakers using voice assistant technology where users can talk to and give commands verbally. However, we do not know much about how this advanced technology can be used to teach young children important mathematical concepts during everyday activities. The goal of this study is to look at whether and in what condition shared book reading with an AI voice agent would support preschool-aged children's learning of mathematical language such as fewer, fewest, and a little bit which is critical in developing numeracy skills and vocabulary.
Sixty-six participants who were recruited for home-visit and school-visit sessions were randomly assigned to one of the three reading conditions to read a storybook with the AI voice agent three times: math storybook reading with dialogic questions, math storybook reading without dialogic questions, and non-math storybook reading with dialogic questions. The findings suggest that shared math storybook reading supports children's target mathematical language learning differently based on their initial understanding of numeracy skills. Children with higher levels of numeracy skills benefited more from simply listening to the story, whereas children with lower levels of numeracy skills showed a tendency to learn better when hearing questions and feedback from the AI voice agent. This study provides implications for the use of advanced technology involving social interaction to support children's learning of mathematical language that can benefit from repeated reading.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/120866 |
| Date | 06 August 2024 |
| Creators | Kim, Jisun |
| Contributors | Adult Learning and Human Resource Development, Choi, Koeun, Bell, Martha Ann, Hornburg, Caroline Byrd, Smith, Cynthia Lea |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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