Using data sgp, students can learn about their own growth in comparison to the average student growth for their grade, subject area and academic peers. This information can then be used to help teachers and students understand their progress, and to identify areas where further improvement is needed.

Students can view their individual student growth percentiles, as well as the growth of their academic peers, on the sgpData_PERCENTILE page. This page also allows users to quickly create student growth percentile reports for a single student. These reports can be printed or exported for sharing with families and students. The sgpData_PERCENTILE pages are accessible by selecting the “sgpData” tab from the menu on any SGP report screen.

SGPs are calculated on a scale from 1-99, with higher numbers indicating greater relative growth. For example, a score of 75 indicates that the student’s growth is in the top 75 percent of their academic peers.

In addition to SGPs, the data sgp package includes a series of tools that allow for additional analyses of student performance. These include windows specific SGPs (see the next section), which are calculated over a range of testing windows, and current SGPs, which can be calculated with the most recent test and one prior assessment from an earlier testing window.

A key feature of SGPs is that they are based on quantile regression, which uses the mathematical method of percentile rank to calculate a linear relationship between previous test scores and a student’s current year’s score. This is a statistical method that is very powerful and accurate, and it is the basis of all SGP calculations.

To perform a window specific SGP, you will need to provide a list of dates and/or assessments that you would like to compare, and then select the appropriate year from the drop down menu. This year will be automatically added to the list of previous years that you have selected, and any SGPs that you previously calculated for this group will be automatically recalculated and updated with the new assessment data.

The WIDE format of the SGP data set provides more options for simple, one-off analyses, but it is generally recommended to use the LONG formated data for operations and for managing SGPs operationally year after year. In fact, all of the higher level SGP wrapper functions are designed for use with LONG format data. Additionally, the SGP package contains embedded long format state specific meta-data that is used by lower level functions. See the SGP package documentation for more details on these features.