Preschool children vary tremendously in their numerical knowledge and these individual differences strongly predict later mathematics achievement. To better understand the sources of these individual differences, we measured a variety of cognitive and linguistic abilities motivated by previous literature to be important and then analyzed which combination of these variables best-explained individual differences in actual number knowledge. Through various data-driven Bayesian model comparison and selection strategies on competing multiple regression models, our analyses identified five variables of unique importance to explaining individual differences in preschool children’s symbolic number knowledge: knowledge of the count list, non-verbal approximate numerical ability, working memory, executive conflict processing, and knowledge of letters and words. Further our analyses revealed that knowledge of the count list, likely a proxy for explicit practice or experience with numbers, and non-verbal approximate numerical ability were much more important to explaining individual differences in number knowledge than general cognitive and verbal abilities. These findings suggest that children bring a diverse set of number-specific, general cognitive and language abilities that are involved in children’s learning of mathematics knowledge, and further suggest that number-specific abilities overshadow more general ones in their contribution to children’s early learning of symbolic numbers.
Bayesian model comparison for compartmental models with applications in positron emission tomography
