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   https://doi.org/10.1109/TVCG.2022.3209457  

   Padilla, Lace ; Fygenson, Racquel ; Castro, Spencer C. ; Bertini, Enrico ( January 2022 , IEEE Transactions on Visualization and Computer Graphics)

   The prevalence of inadequate SARS-COV-2 (COVID-19) responses may indicate a lack of trust in forecasts and risk communication. However, no work has empirically tested how multiple forecast visualization choices impact trust and task-based performance. The three studies presented in this paper (N=1299) examine how visualization choices impact trust in COVID-19 mortality forecasts and how they influence performance in a trend prediction task. These studies focus on line charts populated with real-time COVID-19 data that varied the number and color encoding of the forecasts and the presence of best/worst-case forecasts. The studies reveal that trust in COVID-19 forecast visualizations initially increases with the number of forecasts and then plateaus after 6–9 forecasts. However, participants were most trusting of visualizations that showed less visual information, including a 95% confidence interval, single forecast, and grayscale encoded forecasts. Participants maintained high trust in intervals labeled with 50% and 25% and did not proportionally scale their trust to the indicated interval size. Despite the high trust, the 95% CI condition was the most likely to evoke predictions that did not correspond with the actual COVID-19 trend. Qualitative analysis of participants' strategies confirmed that many participants trusted both the simplistic visualizations and those with numerous forecasts. This work provides practical guides for how COVID-19 forecast visualizations influence trust, including recommendations for identifying the range where forecasts balance trade-offs between trust and task-based performance. 

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3. Weathering the virtual storm: Using computational thinking to make a forecast. Massicotte, J., Staudt, C., & McIntyre, C. (2021). Weathering the virtual storm: Using computational thinking to make a forecast. Science Scope. 44(5): 18–27.

   Massicotte, J. ( January 2021 , DN science scope)

   null (Ed.)

   The Concord Consortium and our partners have developed a free seven-lesson middle school curriculum unit as part of our Precipitating Change project (Staudt, Moher, and Massicotte 2019). Students actively employ computational thinking skills and science and mathematics understanding as they collect and analyze data, run and refine weather models, and make and evaluate predictions while doing tasks similar to those of a professional meteorologist. 

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