Data sgp is a powerful tool for understanding student growth in a variety of ways. It allows for comparisons of student growth across students, grades and subjects, as well as comparing the growth of different schools, districts, and subgroups within schools and districts. It also provides information about the changes in trajectories over time, which is critical for predicting future performance.
While statewide average SGPs can be very stable, individual growth trajectories can fluctuate. These fluctuations are due to a variety of factors, including differences in test administrations, teacher preparation programs and class size. They can also be caused by local events such as a pandemic, which can result in fewer students taking the test and, consequently, lower overall scores.
Using data sgp to understand these fluctuations is important for interpreting student growth and for planning for the future. When comparing student growth trajectories between years, it is critical to account for these fluctuations by adjusting the scales and by recognizing that a change in a single point on the SGP scale does not mean that a student’s academic progress has stalled.
When analyzing SGPs for particular schools, districts, and subgroups, it is also important to remember that SGPs reflect averages across many different groups of students. These groups may include students of different ages, genders, races/ethnicities, and socioeconomic backgrounds. It is important to consider how these individual variations impact the average SGPs for the group and whether the average SGPs are meaningful.
SGPs are calculated based on trends in the statewide assessment data each year, which can cause a shift in average student growth for the state as a whole. For example, during the Covid-19 pandemic in 2024, a larger percentage of students experienced less growth than in previous years due to lower participation in the state assessment, which led to lower overall statewide scores. While this was a temporary phenomenon, it highlights the importance of evaluating and understanding trends in the data before interpreting them for individual students.
The SGPdata package installed when you install the SGP toolkit includes exemplar WIDE and LONG formatted longitudinal data sets (sgpData_WIDE and sgpData_LONG) to help you prepare your own student growth data set. A SGP object with long formatted data in its @Data slot (created by the prepareSGP function) can produce student growth percentiles and projections (both cohort and baseline referenced) as well as cut scores, CSEMs and other state related assessment data. An optional boolean argument passed to studentGrowthPercentiles indicating whether results from the sample subset of the cohort should be returned for inspection. If not specified, the entire original data set is returned in the SGP object’s @Data slot.
