Student Growth Percentiles (SGP) compare a student’s performance to that of their academic peers across one or more years of MCAS assessment data. These percentile rankings help teachers identify students who are growing in their academic skills and also identify students who may be at risk of not meeting grade level standards.
Renaissance Star provides SGP scores to schools and districts for all tested students each spring. Students are eligible for SGP calculations if they:
were enrolled in the same school/district during all four testing windows. They were assigned to a class with an active MCAS assessment record in the fall of the year prior to the spring test. The student’s MCAS assessment score for the spring is in the same content area. They have a valid course roster submission through NJ SMART from their district that lists the teacher of record for the class during that year.
SGP calculations use up to two years of historical MCAS data and are based on a statistical technique called quantile regression. A student’s academic peers are identified from the statewide pool of students with similar MCAS scaled score histories, taking into consideration factors such as demographic groups, educational programs (e.g., sheltered English immersion, special education), and grade levels.
A student’s SGP is a percentile rank of their current MCAS score relative to the average of all students who have taken the MCAS test in the same grade and content area. Students whose current MCAS score is higher than the average score have a SGP above 50. Students whose current MCAS score is lower than the average have a SGP below 50.
Teachers can use SGP scores in conjunction with students’ MCAS scaled scores and achievement level rankings to gain a more complete picture of a student’s progress. SGPs help teachers understand whether a student grew more than, less than, or the same as their academic peers and can be used to inform decisions about instructional strategies and interventions.
SGPdata includes the classes, functions and data necessary for creating a wide range of operational analyses including student growth and achievement plots and SGP projections/trajectories. In addition to the standard SGPdata functions, SGPdata also includes the sgpData_LONG data set for running SGP analyses on a larger scale. This dataset contains 8 windows (3 windows annually) of long format student assessment data in the content areas of Early Literacy and Mathematics for 3 years, and the sgptData_LONG which contains state specific meta-data embedded within the SGPstateData function for use by the sgp_projection_long() and sgp_projections_long() functions. See the SGPdata documentation for more information on using these data sets. Managing long format data is more manageable than managing wide format data and many of the SGPdata functions have been designed to work with this format. Wide-format data is supported but must be converted to long for use by these functions.