Individual differences and contextual influences on children’s attention to numerosity

Image credit: Mazzocco & Bye (2022)


The Attention to Number task (AtN; Chan & Mazzocco, 2017) is an experimental matching task. It involves choosing which of four options best matches a target stimulus, and which remaining options also match the target. By pitting different combinations of features against each other across trials, we previously showed that the relative frequency with which individuals’ select a numerosity-based matches is (a) higher among adults than preschoolers; and among children and adults it is (b) lower overall relative to matches based on more salient features (i.e., color or shape) and (c) lower when numerosity is pitted against more (vs. less) salient) competing features (Mazzocco et al., 2020). Here we pursued three goals: We replicated our original AtN findings with a more ethnically- and socioeconomically-diverse sample of children than reported previously, with a main effect of Salience on frequency of numerosity-based matches. We examined if developmental differences begin to emerge in primary school, by testing for effects of Age and Salience on frequency of numerosity-based matches among 5- to 8-year-olds, among whom main effects of Salience emerged without a main effect or interactions with Age. Finally, we modified the AtN task to maximize children’s opportunity to nominate numerosity-based matches, and found that prior results continue to replicate. Thus our attempts to diminish effects of context failed: the AtN continues to reveal how visual context influences children’s tendency to attend to numerosity, and the developmental differences in attention to numerosity on the AtN are not evident in the early school years.
Part of symposium organized by Jo Van Hoof (Chair): ‘The role of spontaneous mathematical focusing tendencies in early numerical development’.

2022-06-01 10:00
Antwerp, Belgium
Jeffrey K. Bye
Jeffrey K. Bye
Lecturer, Educational Psychology

Researching how people think about math & data. Teaching CogSci & programming.