Data SGP provides educators with a tool to better understand student growth potential. The analysis tool combines multiple years of student assessment data and ranks students based on their performance relative to their peers across the state or district. This information can assist with pinpointing educational needs and help educators improve student outcomes. While utilizing data SGP may seem like an extensive and time consuming undertaking, the process is actually fairly straightforward. The bulk of the work is in data preparation and understanding how to use the software tools for running calculations.
Unlike Value Added Models (VAM), which provide a snapshot of a student’s achievement level, data SGP focuses on a student’s relative ranking of their peer group on each assessed academic content area. Educators can also use the data to identify areas of strength and weakness within their schools. This tool can be used to set student achievement targets and demonstrate the amount of student progress required to meet these goals. It can also be used to track teacher effectiveness and help administrators identify high performing teachers.
To undertake data SGP analyses one will require longitudinal student assessment data in a standard format. Most analyses are run using the statistical analysis software environment R – which is available for Windows, OSX and Linux and is open source. Using this program for SGP analyses is fairly straightforward, but it does assume some familiarity with the program. Several resources are available online to assist newcomers to R and SGP.
When preparing longitudinal data sets for data SGP, it is important to organize the data into a file structure that makes it easier to manage. The data SGP package contains a table called sgpData that is intended to facilitate this task. This table has 5 columns, the first of which is the unique student identifier. The next five columns provide the scale scores associated with a student’s test score history in each of the past five assessment years.
It is important that the data set has the same number of assessment dates in each year in order to calculate an accurate trend line. The data SGP package includes a function that does this automatically for most analyses. In order to obtain more details on this process and how to use the sgpData function consult the SGP data analysis vignette.
The sgpData table also includes an anonymized table called sgpData_INSTRUCTOR_NUMBER that contains the instructor number for each of a student’s test records. This allows the user to see which instructors taught each student in a given year, though teachers can teach students in more than one content area in a given year.
Using SGP data can be time consuming, especially when updating and rerunning existing analyses. However, most analysts find that once they are familiar with the process, preparing and running data SGP analyses is relatively easy. Data SGP provides a powerful alternative to VAM that can be used to support educator goals and provide additional information about student performance.