By Jack M Wolf (University of Minnesota Division of Biostatistics), Kody DeGolier (University of Minnesota Division of Biostatistics), Marta Shore (University of Minnesota Division of Biostatistics)
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Statistical thinking includes the ability to answer one’s own research question through statistics. However, to do statistics, one needs access to the appropriate data and tools to address their research question. In the absence of statistical programming skills, students are often limited to data from pre-cleaned data sources and/or the results that have been created for them. In 2019 Minnesota updated 9th grade state science standards to emphasize human environmental impacts, providing the opportunity to develop new materials that emphasize thinking with data. We collaborated with local teachers in a large urban school district to design a RShiny applet based on data that we cleaned from Minnesota air quality monitoring sites. There, students can create their own plots and regression analyses to explore several variables (e.g., time, location, measures of human impact) and their relation to air quality. The applet was developed over the course of several months and first implemented in May 2021 for a week-long unit. In summer 2022, we expanded the app and integrated teachers’ feedback. We believe that this partnership offers a promising model for further collaboration between data science researchers and high school educators and students.