What is Data SGP?

Data SGP stands for Student Growth Projection. This data is available for all students who participated in the Star assessment, enabling educators to use student SGPs to identify areas of strength and weakness as well as inform classroom instruction. Individual SGPs may also be shared with parents to enhance the overall picture of student achievement. Educators can use individual SGPs for SLO development while administrators use it guide district-wide improvement initiatives.

SGP analyses use longitudinal student assessment data in WIDE or LONG format, ideally in WIDE or LONG formats. Since most errors associated with SGP analysis stem back to issues related to data preparation, it is crucial that accurate and complete preparation be performed beforehand. To aid with this preparation process, the SGP package offers two sample data sets in WIDE and LONG formats (sgpData and sgpData_LONG respectively), to assist users when creating student assessment data suitable for SGP analyses.

SGP analyses convert raw student scores into scaled scores for comparison with an average of all scaled scores for all students in a specific grade and subject area. With this information in hand, the SGP program determines whether each student’s scaled score falls above, below, or at an equal level as this average. It then reports on what percent of those students in that group have attained proficiency.

SGP compares each student’s historical growth trajectories with projections from prior years (or other years, if desired). SGP then provides a range of projected outcomes for each student based on these analyses, such as whether or not they will reach proficiency and what their projected scores will be in future years.

Student growth percentiles provide an effective tool for comparing the performance of students across grades, schools, districts and states. SGP metrics can be particularly helpful when identifying underperforming and high-achieving students – and particularly useful when trying to pinpoint underachieving or high-achieving students. Students with high raw scores on previous test sections may be surprised that simply maintaining their level of achievement indicates growth given how subjectively measured by SGP metrics are perceived as indicators.

SGP documentation, vignettes and examples provide thorough explanations of its calculations and processes for SGP analyses. Users are strongly advised to familiarize themselves with these resources prior to beginning any analyses; should any issues arise while conducting analyses they should contact support for assistance. The SGP package offers both basic and advanced growth projection analyses that can be run simultaneously using various combinations of studentGrowthPercentiles and studentGrowthProjections functions. The SGP Package features higher level functions called abcSGP and updateSGP that combine lower level functions into one function call, simplifying source code associated with operational analyses. Furthermore, this package features the sgpData_INSTRUCTOR_NUMBER lookup table containing instructor details associated with every student test record.