Published August 2025 | Version v1
Thesis Open

Parent-Child Math Talk: How Expectations and Conversational Patterns Predict Fraction Learning

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  • 1. University of Chicago

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Description

Abstract Parental beliefs and interaction styles play a critical role in predicting children's early math development. This study examined how parents' expectancy-value beliefs and conversational behaviors during a brief parent–child math conversation predicted children's learning improvements in fraction understanding. A total of 105 parent–child dyads (child age: M = 5.83 years, SD = 0.69) participated in a structured online task that included a pretest, a fraction conversation using a provided prompt, a posttest, and a parent belief survey. Parent–child conversations were transcribed and coded for feedback types, question formats, and turn-taking balance (i.e., the relative distribution of speaking turns between parent and child, coded as balanced if both contributed roughly equally, and unbalanced if one speaker dominated). Regression analyses showed that parents' expectancy beliefs—their confidence in their child's math ability—significantly predicted children's learning improvement, even after controlling for pretest performance. In contrast, value beliefs—how important parents felt math was for their child—did not predict learning outcomes, though they were associated with a higher proportion of open-ended questions. None of the four feedback types (encouraging, confirmatory, corrective, elaborated) significantly predicted learning when considered simultaneously. These findings highlight the importance of separating expectancy and value beliefs and suggest that parental confidence in a child's abilities may relate to math outcomes more directly than value beliefs or specific interaction styles. Implications for future research on home learning environments and parent-led instruction are discussed. Keywords: parental expectations, expectancy-value theory, parent–child interaction, early math learning, feedback, fraction understanding

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oai:uchicago.tind.io:16038

UChicago Information

Division(s)
Social Sciences Division
Department(s)
MA Program in the Social Sciences (MAPSS)