Data SGP is an analysis tool for longitudinal student assessment data that creates statistical growth plots (SGPs) which provide visual evidence of students’ progress relative to their academic peers. SGPs are created by combining students’ standardized test scores with covariate information using a “growth standard” that is established through their prior testing history. Unlike percentile scores, SGPs identify trajectories of student achievement that can be used to articulate and measure achievement goals and targets.

Data sgp uses a longitudinal student data set, such as the state’s Star system data, to generate SGPs for each individual student by comparing their current assessment score with the growth standard for their grade level and analyzing how much they must grow to reach an achievement target. SGPs can help educators identify low achieving students and can guide their development of interventions to accelerate student progress toward their achievement targets. SGPs can also inform the setting of accelerated achievement targets by helping educators determine how many points a student must make in a year to be on track to achieve their target.

SGP analyses can be conducted with the R software environment which is freely available for Windows, OSX, and Linux. Running SGP analyses requires some familiarity with R. The SGP package includes a vignette that provides a detailed overview of the software and its uses. The vignette is available in the Documentation section of this website.

The SGP package also contains an exemplar WIDE format data set, sgpData, that models the time dependent format used with the lower level studentGrowthPercentiles and studentGrowthProjections functions. sgpData is a 5 year panel data set with the first column providing the unique student identifier and the subsequent columns providing grade level/time associated with the students assessment occurrences. sgpData also includes INSTRUCTOR-STUDENT lookup files, sgpData_INSTRUCTORNUMBER and sgpData_INSTRUCTORNUMBER_LONG, to assist in converting these data sets to the SGPdata format.

Using SGPdata to run operational SGP analyses is generally straightforward. However, a few key steps are required: