Young Children's Mathematical Learning From Intelligent Characters.

Clicks: 341
ID: 94167
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #2 of 7 articles by views in child development

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Children's math learning (N = 217; M  = 4.87 years; 63% European American, 96% college-educated families) from an intelligent character game was examined via social meaningfulness (parasocial relationships [PSRs]) and social contingency (parasocial interactions, e.g., math talk). In three studies (data collected in the DC area: 12/2015-10/2017), children's parasocial relationships and math talk with the intelligent character predicted quicker, more accurate math responses during virtual game play. Children performed better on a math transfer task with physical objects when exposed to an embodied character (Study 2), and when the character used socially contingent replies, which was mediated by math talk (Study 3). Results suggest that children's parasocial relationships and parasocial interactions with intelligent characters provide new frontiers for 21st century learning.
Reference Key
calvert2019youngchild Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Calvert, Sandra L;Putnam, Marisa M;Aguiar, Naomi R;Ryan, Rebecca M;Wright, Charlotte A;Liu, Yi Hui Angella;Barba, Evan;
Journal child development
Year 2019
DOI
10.1111/cdev.13341
URL
Keywords
secondary prevention amyloid alzheimer's disease outcome research clinical meaningfulness clinical trials methodology preclinical

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.