Data sgp provides educators with the tools they need to accurately assess student progress in their classroom. By calculating students’ growth percentages based on their prior test scores and that of similar academic peers, educators can identify underperforming students in need of extra support as well as those students who are excelling at a rapid pace. By providing a clear picture of what it takes for each student to reach their desired grade-level achievement target, educators can develop more effective differentiation strategies to meet the needs of every student.
Unlike most assessment metrics, growth percentages measure the relative performance of individual students to their academic peers. As such, they are more effective in identifying underperforming students in need of additional support and determining whether accelerated programs are meeting their intended goals. This allows educators to more effectively differentiate instruction, track the performance of students and teachers, as well as evaluate school/district-wide outcomes.
Although creating SGP analyses requires complex calculations and can be challenging when a student’s previous test history includes multiple testing windows or content areas, SGP provides educators with valuable insights for informing instruction, assessing teacher/student performance and supporting classroom research initiatives. Moreover, SGP provides the foundation for state-wide performance benchmarking.
SGP utilizes historical growth trajectories of Star examinees as well as the performance of similar students from each district to estimate a student’s predicted performance. This performance profile can be compared to the state’s expected proficiency rate (EPR) to gauge a student’s likelihood of meeting his or her grade-level goal.
Sgp is measured on a 1-99 scale and indicates how much a student’s score on a particular test section has increased relative to the average of the academic peer group with comparable prior test scores. For example, a student’s SGP score of 75 indicates that the student has shown more growth than about 75 percent of his or her academic peers.
As an analysis tool designed for use within the statistical software environment R, the data sgp package requires that users have familiarity with this platform. R is available free-of-charge for Windows, OSX or Linux and numerous online resources are available to help newcomers get started.
For SGP analyses to run correctly, the user must have access to LONG formatted data sets. The sgpdata package offers an exemplar LONG data set sgptData_LONG as well as an INSTRUCTOR_STUDENT lookup table to assist with this process. Furthermore, all higher level functions in the sgpdata package require that data be in the LONG format; however, this requirement can often be circumvented by preprocessing the data to eliminate redundant elements like test score predictors and student-level covariances. This can significantly reduce computation requirements while simultaneously improving the accuracy of estimates produced by SGP methods. See the SGP Data Analysis Vignette for additional details on this process.