Data SGP is a collection of classes, functions and data sets used to calculate student growth percentiles (SGPs) and projections/trajectories using large-scale longitudinal education assessment data. Quantile regression is employed as the statistical technique that estimates conditional density associated with each student’s achievement history before using coefficient matrices derived by Data sgp in order to derive percentile projections and trajectories for student growth percentiles/trajectories projections/trajectories projections/trajectories projections/trajectories can then calculated.
The NWEA SGP reporting system relies on data sgp as its foundation. This reporting system generates growth reports that outline student progress toward meeting state academic standards for their grade and subject area, providing teachers, administrators and families with an effective tool to understand how students are performing on state assessments as well as what steps need to be taken to improve outcomes for individual student performances.
SGPs offer a more accurate and meaningful measure of student growth than simple mean or median score comparisons, which only indicate differences in scores between two students. A student’s SGP ranges between 1-99; higher numbers indicate greater relative growth – for instance a student who achieved an SGP rating of 75 has made more progress than 75% of their academic peers.
SGPs can only be calculated for students who have taken at least two assessments in different testing windows. The most recently administered assessment is used to calculate an SGP; then a second one will be selected to compare current performance with past performance; SGPs are then calculated by comparing new with old performance, and calculating what percentage of their academic peers have experienced more growth than they have.
sgpData contains four sample data sets used for SGP analysis. The first, sgpData, specifies data in wide format required by lower level SGP functions such as studentGrowthPercentiles and projections; while sgptData_LONG and sgptData_INSTRUCTOR_NUMBER provide long format required by higher level functions like abcSGP, prepareSGP, and analyzeSGP.
SGP is only available to teachers whose courses will undergo state assessments in 2023-2024 and who possess valid SGP data. Course code lists are the source for determining this information; to view them visit NJ SMART Resources and Trainings webpage under Documents for Download section. Courses that contain SGP data are identified with an “mSGP indicator in the Course Code List; currently, only teachers of third grade English language arts and mathematics classes possess such data. Teachers teaching first grade classes do not typically possess SGP data since their students do not take state assessments that year; however, calculated SGP numbers could still be calculated provided the teacher taught fourth grade in prior year and has valid SGP numbers from that year.