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This study was grounded in the spatial computational thinking model developed by the 3D Weather project funded by the NSF STEM+C program. The model reflects a discipline-based perspective towards computational thinking and captures the spatial nature of computational thinking in meteorology and the reliance of computational thinking on spatial thinking for geospatial analysis. The research was conducted among nineteen teachers attending the summer workshop offered by the project in its third project year to prepare them for teaching spatial computational thinking with IDV (Integrated Data Viewer, downloadable at https://www.unidata.ucar.edu/software/idv/) visualization of weather data. Quantitative survey data were collected measuring these teachers’ meteorology content knowledge, spatial computational thinking, self-efficacy for teaching spatial computational thinking, and epistemic cognition of teaching meteorology. The data were analyzed to examine the effects of the workshop in terms of these variables and the correlations among them were also explored. 

Funded by the NSF STEM+C program, the 3D Weather project developed instructional modules of using IDV visualization of weather data to help middle and high school students to develop spatial computational thinking. This paper reports the research on the professional development provided to 15 teachers by the 3D Weather project in the second project year.