Unraveling latent cognitive, metacognitive, strategic, and affective processes underlying children's problem-solving using Bayesian cognitive modeling.

ABSTRACT: Children exhibit remarkable variability in their mathematical problem-solving abilities, yet the cognitive, metacognitive and affective mechanisms underlying these individual differences remain poorly understood. We developed a novel Bayesian model of arithmetic problem-solving (BMAPS) to uncover the latent processes governing children's arithmetic strategy choice and efficiency. BMAPS inferred cognitive parameters related to strategy execution and metacognitive parameters related to strategy selection, revealing key mechanisms of adaptive problem solving. BMAPS parameters collectively explained individual differences in problem-solving performance, predicted longitudinal gains in arithmetic fluency and mathematical reasoning, and mediated the effects of anxiety and attitudes on performanc

SUBMITTER: Mistry PK 

PROVIDER: S-EPMC11838325 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature