Data sgp is a data set that contains information about students and their growth in academic achievement. The data is used by many organizations to assess the effectiveness of teachers, schools, and districts. This data can also be used to estimate student growth percentiles (SGPs) for different groups of students.
SGPs are an important part of the accountability system in the United States, as they provide a measure of student progress in college and career readiness. In addition, they are one of multiple indicators used to measure the effectiveness of teachers and leaders in the Teacher and Leader Key Effectiveness Systems (TKES and LKES).
When using sgpData with SGP, we recommend that you refer to the SGP data analysis vignette. This will explain how to use the sgpData data set and the SGP package in a step-by-step fashion.
The sgpData data set includes 5 years of annual assessment data from a panel sample of students. It is an anonymized, vertically scaled, assessment data set. The data consists of 5 columns that each provide a unique student identifier, the grade level/time associated with the assessment score occurrence, and the numeric scores associated with that occurrence.
This data set demonstrates the sgpData format, which is the standard format for SGP analysis. The data set can be downloaded by registering with the sgpData website.
If you are a member of the sgpData user community, please contact us to provide feedback or suggest changes to this document. We will consider your feedback and incorporate it into the sgpData user documentation.
SGPs are an important aspect of the accountability system in the United States, and they contribute to a variety of other school and district effectiveness measures. They are one of several factors in the CCRPI, which is a widely-used measurement of student progress in high schools. They are also one of the supplemental measures used to calculate the overall SGP performance index in the TKES and LKES systems.
While the relationships between true SGPs and student background characteristics are descriptive in nature, they can be influenced by a number of mechanisms. For example, if more effective teachers have students with certain background characteristics, then the average true SGP for these students may be higher than for other students. Or if less effective teachers have students with specific background characteristics, then the average true SGP may be lower than for other students.
Another mechanism for influencing the relationships between true SGPs and student covariates is the sorting of teachers to schools and classrooms that vary systematically with respect to our student background variables. For example, if more effective teachers tend to teach students from schools that are better equipped for teaching math, then the average true SGP for these teachers may be higher than for other teachers.
In contrast, if less effective teachers tend to teach students from schools that have poorer math facilities, then the average true SGP for these educators may be lower than for other educators.