People's attitudes toward mathematics are multifaceted. Across four studies, we found that children and adults have different attitudes about mathematics when asked specifically about whole numbers, as opposed to fractions. The vast majority of children and adults reported negative attitudes toward fractions despite having positive attitudes toward whole numbers. Across both children and adults, the difference in fraction and whole-number attitudes was present across levels of math achievement, indicating that it was not just participants who were worse at math whose attitudes differed by number type. These findings may have important implications for how children and adults engage with numerical information when presented as fractions. KEYWORDSAttitudes; fractions; individual differences; integrated theory of whole number and fractions development; mathematics attitudes; mathematics education; whole number bias PEOPLE ENCOUNTER FRACTIONS in many everyday contexts. Reasoning with fractions and other ratios underlies common tasks including measuring and scaling (e.g., when calculating a discount, measuring a length, or following a recipe) and is often necessary for complex decision making (e.g., evaluating health-risk information at the doctor's office or comparing interest rates at the bank). Furthermore, fractions are an essential facet of the development of mathematical skills. Fraction proficiency uniquely predicts concurrent academic achievement in the sixth and eighth grades (Torbeyns, Schneider, Xin, & Siegler, 2015), students' readiness to learn Algebra I (the "gatekeeper" to higher mathematics; Booth & Newton, 2012), and high school mathematics achievement (over and above early whole number skills and general cognitive ability, Siegler et al., 2012). Despite their importance, fractions are difficult for children to master (e.g., Siegler,

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Understanding fraction magnitudes is important for achievement and in daily life. However, adults’ fraction reasoning sometimes appears to reflect whole number bias and other times reflects accurate reasoning. In the current experiments, we examined how contextual factors and individual differences in executive functioning (Experiment 1), knowledge of fraction equivalence (both experiments), and strategy use (Experiment 2) influenced adults’ fraction reasoning. Adults were only biased by fraction components when reasoning about fractions as holistic magnitudes was difficult: when estimating under a time constraint, when estimating fractions with large components, or when comparing fractions close in decimal distance. However, adults’ knowledge of fraction equivalence moderated the effects of whole number components on their fraction estimation performance: when modeled at low levels of equivalence knowledge, adults were biased by fraction components when estimating. Adults with more knowledge of fraction equivalence were able to reason about fractions as holistic magnitudes through adaptive strategy choices.

At the onset of the coronavirus disease (COVID-19) global pandemic, our interdisciplinary team hypothesized that a mathematical misconception—whole number bias (WNB)—contributed to beliefs that COVID-19 was less fatal than the flu. We created a brief online educational intervention for adults, leveraging evidence-based cognitive science research, to promote accurate understanding of rational numbers related to COVID-19. Participants from a Qualtrics panel (N = 1,297; 75% White) were randomly assigned to an intervention or control condition, solved health-related math problems, and subsequently completed 10 days of daily diaries in which health cognitions and affect were assessed. Participants who engaged with the intervention, relative to those in the control condition, were more accurate and less likely to explicitly mention WNB errors in their strategy reports as they solved COVID-19-related math problems. Math anxiety was positively associated with risk perceptions, worry, and negative affect immediately after the intervention and across the daily diaries. These results extend the benefits of worked examples in a practically relevant domain. Ameliorating WNB errors could not only help people think more accurately about COVID-19 statistics expressed as rational numbers, but also about novel future health crises, or any other context that involves information expressed as rational numbers.