Virginia Tech
Preschoolers' Mathematical Language Learning during Book Reading with an AI Voice Agent
Abstract
dc:description.abstractDigital 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.
Degree
thesis:*- Name thesis:degree_name
- Doctor of Philosophy
- Level thesis:degree_level
- doctoral
- Discipline thesis:degree_discipline
- Human Development
- Department dc:contributor.department
- Adult Learning and Human Resource Development
- Grantor dc:publisher
- Virginia Tech
- Year dc:date.issued
- 2024
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Kim, Jisun
- Chair dc:contributor.committeechair
-
- Choi, Koeun
- Committee members dc:contributor.committeemember
-
- Bell, Martha Ann
- Hornburg, Caroline Byrd
- Smith, Cynthia Lea
Subjects
dc:subject × 4Rights
dc:rights- Statement dc:rights
-
- In Copyright
- Licence dc:rights.uri
- Language dc:language.iso
- en
Identifiers
dc:identifier.*- Dc Identifier Other
- vt_gsexam:41264
- OAI identifier oai:identifier
- oai:vtechworks.lib.vt.edu:10919/120866