One of the positions I applied for when pursuing a career transition from classroom teacher to Data Scientist gave me this school data assignment. It was open-ended, with the scenario being a general request from a school principal for data analysis to help find meaning in the given data. These data were the previous year’s summative assessment results in ELA and Math, as well as the first two quarters of the current year’s diagnostic assessments in ELA and Math. The data included levels for each that corresponded between tests, so this was the variable on which I chose to focus. Also included were raw scores and percentiles, however these would not have been useful in this analysis.
The assignment also included a request for subgroups within the data. Student information that was given included “SPED,” “Non-SPED,” “Gifted,” “Non-Gifted,” and grade levels from 3rd through 8th grades. After an initial overview of schoolwide trends, I looked at overall and grade-level trends in the Non-SPED, Non-Gifted subgroup. Due to sample sizes, I chose to only include overall trends for the SPED subgroup and included comments rather than percentages and visualizations for the Gifted subgroup.
On the whole, I was satisfied with my analysis. The timeframe for completion was relatively brief and the available data did not allow for meaningful analysis of additional subgroups.