DayMay 27, 2024

How to Analyze Student Growth Percentiles (SGP) Data

In the education world, student growth percentiles (SGP) are a useful metric to measure and communicate student performance. A student’s SGP score indicates how much they have grown compared to other students with similar previous test scores (their academic peers). This data can help educators, parents and other stakeholders understand whether a student has been growing more than, less than or about as expected.

SGP scores are calculated by comparing a student’s assessment scores across multiple years and dividing that number by the standard deviation of those scores. Students with higher growth percentages are considered to be making more progress than expected and are often identified as being “advanced.” Students with lower growth percentages are considered to be “underperforming” or in need of improvement. However, the calculation of SGP scores can be complex and may not always provide a clear picture of student progress.

The SGP package allows users to analyze this complex data using a variety of tools. It is designed to be used with the statistical software environment, R, which is available for free and runs on many operating systems. It is recommended that those interested in running SGP analyses spend some time familiarizing themselves with the software and its features. The sgpData spreadsheet, which includes the SGP scores for all of the students in a school or district, provides a simple way to view and analyze this data. The first column of sgpData, ID, provides the unique student identifier while the next 5 columns, SS_2013, SS_2014, SS_2015, and SS_2016, provide the scale scores associated with each student’s assessment in these five years. In some cases, a student does not have five years of assessment data and their SGP score will be missing.

To run SGP analyses, users must have a computer with the R software installed. This can be downloaded for free from the CRAN website for Windows, OSX or Linux. There are several resources available on CRAN that can be used to get started with R, including an online tutorial.

In addition to the SGP analysis tools, the package supports importing a variety of other educational datasets in wide format. These datasets are then able to be manipulated and visualized in the same manner as SGP data. Users are encouraged to consult the SGP vignette for more comprehensive documentation on how to use wide-format datasets with the SGP package. This information is also provided in a more concise form on the R help page for sgpData.