Data sgp is an analysis tool for longitudinal student assessment data. It creates statistical growth plots (SGPs) that display students’ academic growth trajectories over time and provide evidence of student achievement relative to their peers. SGPs are based on students’ standardized test scores combined with covariate information using an established growth standard defined through previous testing history. These growth plots are more accurate than traditional percentiles because they account for a student’s test performance in a broader context.
To obtain SGP data teachers should first register on the state’s website. Once registered, teachers will be provided with a login and password to access the SGP website where they can download the latest version of the software. Once the software has been downloaded, a teacher can start performing analyses on their students’ data. Educators must be prepared for this process to take some time as they must download the data, clean it and format it so that the results can be properly evaluated.
SGP analysis focuses on students’ progress and their current proficiency level in comparison to other students across their grade levels. This enables educators to better identify students who are struggling, and to focus on specific learning areas where more instruction is needed. In addition to identifying students in need of assistance, SGP analysis can help educators understand what their students are doing well and make instructional decisions accordingly.
A key component of SGP is the student growth percentile, which provides an estimate of a students’ expected progress toward proficiency for a particular content area based on their past performance and their historical growth trajectories. This is a powerful tool for assessing the effectiveness of individual teaching strategies as well as district and state accountability systems.
Unlike percentiles, which are a static measure of a student’s performance, SGP growth percentiles are updated regularly and can provide teachers with a more accurate picture of a student’s proficiency status. In addition, SGP can be used with the student growth projections function to see future estimates of a students’ potential proficiency level based on their current trajectories and other covariates.
The SGPdata package includes an example WIDE format data set (sgpData) to simulate time dependent data used with lower level functions such as studentGrowthPercentiles and studentGrowthProjections. It also contains a LONG format data set to facilitate the conversion of this type of data into SGPdata formats.
There are 7 required variables when using LONG data with SGP analyses: VALID_CASE, CONTENT_AREA, YEAR, ID, SCALE_SCORE, GRADE and ACHIEVEMENT_LEVEL. These are the variables that are used to calculate the student aggregates for use with the summarizeSGP function.
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