Student Growth Percentiles (SGP) show how students are progressing in relation to academic peers who have similar raw scores and test section history on state assessments. These academic peers may be in the same grade or school, across grades, or within a specific subgroup such as race/ethnicity, special education or multilingual learning.
SGPs are a common metric used by educators to determine student progress and identify areas for improvement. They are also one of the measures used to calculate value-added growth data for teacher evaluation. The Washington Department of Public Instruction (DPI) uses mean SGPs in their federal ESSA accountability system. Districts use SGPs in their local accountability systems and school report cards.
SGP is the result of a mathematical process that compares a student’s current assessment score with their previous assessment scores. For example, a student who takes an ELA assessment in grade 4 and again in grade 8 will receive two SGPs in ELA and one in math. A student who only took the ELA assessment in grade 6 will receive one SGP in math because they did not take a math assessment in grade 7.
A statewide median SGP is approximately 50. It is important to note that statewide median SGPs are calculated relative to academic peers that have taken the same MCAS tests and have similar test section histories. This is different from other measures such as the percent of students that are proficient and advanced for a particular year.
For a given year, the distribution of SGPs is expected to follow a normal curve with equal numbers of students at each percentile (the diagram on the right shows groupings of 10 percentiles). However, some years can have significant shifts in student performance due to factors such as the Covid-19 pandemic.
Students with low SGPs can make significant gains in the future to reach proficient status. Conversely, students with high SGPs might struggle to improve their performance over time. It is important for teachers and families to understand these trends so they can make informed decisions about what steps to take to close the gap between a student’s achievement level and what they need to be successful in the future.
The sgp package contains classes, functions and data that allow users to conduct a variety of SGP analyses. This includes SGPs and percentile growth projections/trajectories using large scale, longitudinal educational data.
The SGP vignette and the SGP github repository provide more detailed documentation on how to use the SGP package for these kinds of analyses. The exemplar WIDE data set, sgpData, and the LONG data set, sgpData_LONG, included when the SGP package is installed, model the format of data that is used with the lower level studentGrowthPercentiles and studentGrowthProjections functions.
In addition, the SGP github repository includes wrapper functions (abcSGP and updateSGP) that simplify the code required for conducting these analyses. They combine the six steps required to prepare and run a SGP analysis into a single function call, making them easier to use for operational SGP analyses.