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 academic peers. SGPs offer more accurate measurement of growth than traditional percentile scores do and can be used to identify both accelerated learners and students who may not be making the expected levels of progress.
SGPs are a valuable addition to the tools available to schools and districts as they strive to provide every student with the opportunities they deserve. SGPs allow educators to use data to communicate to stakeholders that proficiency must be reached within a certain timeframe while also serving as an incentive to teachers by linking performance against measurable goals. This is something that standard growth models cannot accomplish!
When using SGPs, it is important to keep in mind that there are many variables at play. For example, a student’s SGP can be significantly affected by the design of the baseline cohort and/or teacher or school characteristics. In order to minimize these effects, it is recommended that analyses be run on a baseline cohort consisting of students who have been taught by the same instructors throughout their education experience.
The SGPdata package is designed to make running SGP analyses as simple as possible. The bulk of the work in SGP analyses is the data preparation and the SGPdata package facilitates this process by providing an easy to use interface for importing the student data files into R and converting them into SGP state datasets. The SGPdata package includes WIDE format data sets that simulate the time dependent data used with lower level SGP functions like studentGrowthPercentiles and studentGrowthProjections, as well as LONG format datasets that assist with converting these to SGPdata datasets.
Once the student data is in the correct format, the SGPdata package provides a number of useful tools for quickly displaying, comparing and reporting on SGPs. The most commonly used tools include Window Specific SGPs, which compare or report a single student’s SGP over a specific window of time, and Current SGPs, which display a student’s latest SGP as a quick check-in on the progression of their growth.
Regardless of which tools are used, the most important step in SGP analyses is ensuring that all of the data files being analyzed have been imported correctly. Once this is accomplished, the remainder of SGP analyses is a relatively simple two step process. We encourage schools and districts to take advantage of the SGPdata package’s easy-to-use tools and learn more about how SGPs can be used to improve student achievement in Michigan. Please feel free to contact us if you have any questions about utilizing the SGPdata package. We are happy to help!