Date of Award

Spring 2019

Document Type

Thesis

Terms of Use

© 2019 Seetha Davis. All rights reserved. This work is freely available courtesy of the author. It may only be used for non-commercial, educational, and research purposes. For all other uses, including reproduction and distribution, please contact the copyright holder.

Degree Name

Bachelor of Arts

Department

Educational Studies Department

Abstract

Understanding sickness and engaging in preventative health behaviors necessitate abilities to reason causally and probabilistically. This set of studies addresses these cognitive processes in young children. Prior literature suggests that four-year-olds see causes of disease as determined (e.g., germ exposure necessarily causes illness) and cannot distinguish between causes of disease in terms of differing degrees of contagion (e.g., a germ-induced cough is equally contagious as a smoke-induced cough). In order to assess young children's probabilistic and causal reasoning abilities in the health domain, two studies were conducted. Study I investigated probabilistic thinking in adults and children in the health domain. Participants were presented with stories that either did or did not include preventative health behavior (e.g., washing one's hands to prevent spread of illness). The results suggested that, when presented with stories both containing and not containing preventative health behaviors, children can think probabilistic ally about illness transmission. Study 2 evaluated the utility of cognitive comparison in supporting children's causal reasoning. In contrast to prior literature, a novel comparison learning task facilitated children's understanding of different levels of contagion associated with various causes of illness. The results suggested that, overall, comparing two stories involving different causes of illness and different contagion outcomes facilitates differentiation between the level of contagion for various causes of illness. Taken together, these findings substantiate the utility of comparison learning in supporting young children to think about probabilistic causality in the health domain.

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