Data sgp is an interactive graphic that allows you to view growth data for individual students, grade levels, schools and districts. It is a valuable tool to assist educators in their SLOs and continuous improvement efforts. Individual student growth data can also be shared with parents to enhance their understanding of their child’s progress.

The purpose of data sgp is to provide users with a convenient and accessible way to visualize student growth data using a dynamic, zoomable interface. Users can select any of the available data sets by clicking on them or by navigating through the tree menu in the left hand corner. A popup window will then display the data set selected. This window will contain all of the information about the data set including its name, type, data format, and a sample graph for visualization purposes.

A unique feature of this data sgp is the ability to establish multi-year achievement targets/goals for students based on official state achievement standards. Specifically, the data sgp allows a user to specify what level of growth, in terms of a percentageile ranking, is required for each student to reach their achievement target. This is accomplished by linking a student’s current performance to their own prior achievement standard using a set of growth percentiles.

While the graphical display of data sgp is a useful tool to help identify areas of student success, the analysis and interpretation of individual growth percentiles remains essential for educators. Recent research has shown that the error-prone nature of standardized test scores creates considerable noise in estimated SGPs, making them noisy measures of latent achievement traits (Lockwood & Castellano, 2015).

As such, it is critical to understand the underlying assumptions and limitations of the growth percentile calculations used in data sgp. This article explains the assumptions of these calculations as well as provides an example that illustrates some of the most common errors and pitfalls that can be encountered when using growth percentiles.

Since the development of the SGP methodology in 2008, median SGPs have been the primary summary statistic used for analyzing student growth data. However, the Department has made a decision to move away from medians and toward means as the preferred summary statistic. This article outlines the rationale behind this change.

The data sgp package includes a WIDE format exemplar data set, sgpData, and a LONG format exemplar data set, sgpData_LONG. Using data in the wide or long formats with SGP is, in general, straight forward. The SGP vignette provides more comprehensive documentation on how to use these exemplar data sets for SGP analyses.

The first column in sgpData, ID, provides the unique student identifier for each year of student assessment data. The following 5 columns, SS_2013, SS_2014, SS_2015, and SS_2016, provide the student assessment scale scores for each of these years. In some cases students do not have five years of test data so their growth percentiles are missing (NA). This is indicated by an NA in the column.