Data sgp is a metric designed to track student achievement growth over time using longitudinal test score data. Its primary use is informing instruction, assessing teacher/student performance and supporting educator evaluation systems. Its methodology involves latent achievement trait models estimated from standardised assessment data and student covariates compared against growth standards established through historical test score history. This reduces estimation error and provides a more valid measure of growth than conventional percentiles.
SGPs are useful for analyzing students’ academic growth in the context of their grade level peers, subject area and/or across districts. They can also be a powerful tool for teachers as they compare their students’ growth to the growth of their peers and identify areas where their class might need improvement. This information can then be used to focus classroom differentiation and instructional strategies.
Educators can access SGP data by visiting their state’s website and following the directions provided. They can then view reports specific to their district that show how students performed on each subject tested; the percentage of students who fell “inside” the curve, meaning they exceeded their expected performance; and the number of students who fell below the curve. These reports can be very helpful for identifying students who might need additional support and helping them achieve their full potential.
The most important thing to remember when looking at SGP data is that the data should be viewed in the context of the students’ prior achievement. SGPs are based on students’ standardized test scores with covariate information. Students are compared with their academic peers who have the same combination of prior test score history. For example, let’s say a sixth grader Simon scored 370 on this year’s statewide ELA exam. This year’s scale score growth would be a 70 point increase over his previous score of 300. It might seem that this is a large gain, but Simon’s growth was comparatively much smaller than that of his classmates who had the same mix of prior test score history.
It’s also important to remember that SGP data is based on longitudinal assessments and thus takes time to stabilize. SGPs should not be used for high stakes purposes until at least 2018. This allows three more years for educators to become familiar with the data and to ensure that the system is functioning correctly.
To run SGP analyses you’ll need a computer that has the free open source software R installed. It can be downloaded for Windows, OSX and Linux. If you are new to R, it’s a good idea to spend some time familiarizing yourself with the program before jumping in and running SGP analyses.
SGPdata is a dataset that contains a list of student data for each school and grade level in a given state. Each file includes the student name and statewide ID, a list of their individual tests taken, their SGPs, and the teacher data associated with each test. In addition, the file contains an anonymized student-instructor lookup table that lists which instructors were assigned to each student for a given test.