How to Interpret Data SGP

data sgp

In addition to displaying student growth relative to other students with similar prior performance, data sgp is often used to identify students who are falling behind and to provide them with appropriate support. For example, students with high relative growth and low prior achievement might be identified as high-risk and targeted for interventions. However, there are some important considerations that should be taken into account before interpreting data sgp.

While there is much excitement about the potential for individualized student support based on data sgp, it is important to recognize that this data does not necessarily provide accurate information about an individual’s progress or potential. Specifically, the relationships between true SGPs and student background characteristics can create a substantial source of uncertainty when using estimated SGPs to make inferences or decisions for individual students. This uncertainty is even more likely when the data are aggregated to the teacher level, as is the case with the SGPs displayed in the Star Growth Report.

The SGPs displayed in the Star Growth Report are based on the average of an individual student’s performance across multiple assessments. In order to calculate a student’s current SGP, the system must have access to both a current assessment (within the past 18 months) and at least one prior test from an earlier testing window. The current assessment and the previous test are used to estimate a student’s current growth trajectory, and a projection of the future trajectory is then calculated based on that trajectory.

These correlations between current and prior SGPs, as well as the within-subject, cross-year correlations of the latent achievement traits, are a critical component of the model that is used to estimate a student’s current SGP. It is not possible to determine whether or not the correlations between these variables are a function of PTh, although it is possible that the lower within-subject and cross-year correlations in Grades 7 and 8 reflect the fact that the covariates tend to explain a larger percentage of achievement variation in these grades than in Grades 4 and 5.

There are some clear benefits to using SGPs, including the ability to use them to project future progress for individual students and to identify those who may need additional support. These benefits have contributed to the growing adoption of SGPs in the United States.

For these reasons, it is critical that schools understand the limitations of SGPs and be cautious when interpreting them to make decisions about students or their teachers. It is also important that school leaders are aware of the potential biases in using SGPs to make decisions about their students and teachers. If not carefully interpreted, SGPs can lead to falsely positive or negative decisions that do not advance student learning. To help schools overcome these challenges, we have provided the following guidance for using and interpreting SGPs. We will continue to develop additional resources and training materials for schools and districts to support the use of SGPs.