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  • Title: ➤  How Do Visual Models Affect Accuracy And Use Of Whole Number Bias Strategies When Adults Solve COVID-19 Math Problems?
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Our previous study (Thompson et al., under review), tested a brief online intervention focused on teaching adults how to calculate the case fatality rate of COVID-19 vs. the flu. Those in the intervention condition were more likely to answer a transfer problem correctly as compared to the control condition. Further, those in the control condition reported using a strategy aligned with the whole number bias when solving this transfer problem. In the current study, we are investigating whether various visual models (number lines, risk models, or icon arrays) facilitate more accurate COVID-19 problem solving than no visual model at all. Further, we will investigate the relation between COVID-19 problem-solving accuracy, use of whole number bias strategies, perceived COVID-19 likelihood and worry for themselves and other people, and perceived COVID-19 severity. This study was supported in part by U.S. Department of Education Institute of Education Sciences Grants R305A160295 and R305U200004 to C.A. Thompson at Kent State University.

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