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Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
Published on: August 28, 2021
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Young Children's Mathematical Learning From Intelligent Characters
Sandra L Calvert1, Marisa M Putnam1, Naomi R Aguiar1
1Georgetown University.
Child Development
|November 21, 2019
Summary
Children
Area of Science:
- Educational Psychology
- Human-Computer Interaction
- Developmental Psychology
Background:
- Intelligent character games are increasingly used in early childhood education.
- The role of social meaningfulness and social contingency in children's learning from these characters is not fully understood.
- Parasocial relationships (PSRs) and parasocial interactions (PSIs) are key components of social engagement with media characters.
Purpose of the Study:
- To examine how social meaningfulness (PSRs) and social contingency (PSIs, e.g., math talk) influence children's math learning in an intelligent character game.
- To investigate the impact of embodied characters and socially contingent replies on children's math performance and transfer of learning.
Main Methods:
- Three studies were conducted with 217 children (mean age 4.87 years).
- Children's parasocial relationships and math talk with an intelligent character were assessed.
- Performance was measured through virtual game play accuracy and speed, and a math transfer task with physical objects.
Main Results:
- Children's parasocial relationships and math talk with the intelligent character predicted faster and more accurate math responses.
- Exposure to an embodied character improved performance on a math transfer task.
- Socially contingent replies from the character, mediated by math talk, also enhanced math transfer.
Conclusions:
- Parasocial relationships and parasocial interactions with intelligent characters can significantly enhance children's math learning and transfer.
- Embodied characters and responsive interactions represent promising avenues for developing effective educational technologies for young children.
- Findings suggest new frontiers for 21st-century learning by leveraging social dynamics in human-AI educational contexts.
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