How to Create a Data SGP

Data sgp is the collective of aggregated student achievement and learning data collected over time. This data provides educators with a variety of tools to better understand how students perform over time. Educators can utilize this data for many purposes including shaping classroom practices, evaluating school/district performance and supporting wider research efforts. This data includes individual-level measures such as test scores and growth percentiles; aggregated information at the class, grade, school/district and demographic levels (e.g., gender, ethnicity, socioeconomic status) and more.

Statistical Growth Plots, or SGPs, leverage longitudinal student assessment data to produce statistical growth plots that measure students’ relative progress compared with academic peers. These SGPs are computed using a distribution from multiple years of compiled test data to minimize estimation errors inherent in single year analyses. The sgpData package installs exemplar WIDE and LONG formatted SGP data sets (sgpData_WIDE and sgpData_LONG) to help users set up their SGP analyses.

SGPs require a significant amount of data, so they may not be available for students with limited test histories. Additionally, the time dependent nature of SGP calculations makes them more susceptible to spurious correlations due to teacher or school characteristics and/or design of the baseline cohort used for the analysis. For these reasons, it is important to carefully consider how to create your data set before constructing an SGP.

A few simple steps can improve the quality of your SGPs: 1. Spend a minute formatting your stat category columnns (e.g., set to three decimals in the BA column and two in the other columns). This will make your data easier to read and understand.

2. Review the SGPs to ensure the aggregations are reasonable and the averages are meaningful. This is particularly important if you’re using SGPs for teacher evaluation. SGPs provide a number of ways to evaluate teacher effectiveness, but it is important that the averages you generate are sensible and that they represent reasonable amounts of data.

3. If your SGPs are displaying inconsistent results, investigate why. It’s likely a problem with your data or your formulas. In some cases, you’ll need to change your calculation methods or rerun the SGPs.

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