The data sgp package is a tool for analyzing longitudinal student assessment data. It produces statistical growth plots (SGPs) that describe students’ academic progress relative to their peers. SGPs provide a more accurate picture of student achievement than traditional percentile scores, because they consider prior testing history as well as current performance. These SGPs provide teachers and administrators with the information they need to support student learning, including how to identify students who may be struggling or ready for acceleration.
The SGPs generated by the data sgp package are based on a combination of current assessment results and prior assessments that have been standardised to reflect the same level of difficulty. This means that the SGPs produced by data sgp do not necessarily match those of other states or districts and should be treated as state specific.
SGP analyses require a working knowledge of the R software environment and the underlying data structure. It is recommended that you familiarise yourself with the R environment before diving into running SGP analyses as there is a fair amount of back and forth between data preparation and analysis.
Once you have the required software and hardware, data sgp analyses are fairly straightforward. The bulk of time in any SGP analysis is spent on data preparation and it is essential that the data is prepared correctly. Any errors that arise in the analysis process often revert back to data preparation issues, so it is important to take your time and prepare your data well.
As a package built for the R software environment, the data sgp package requires the R program installed on your machine. The R programming language is available for Windows, OSX and Linux and is free and open source. The data sgp package is built on top of the sgpdata package which provides the base functionality for all SGP analyses. The sgpdata package contains 4 examplar data sets for use with SGP calculations. The first, sgpData, specifies the data in WIDE format that’s used with the lower level SGP functions studentGrowthPercentiles and studentGrowthProjections. The other two, sgptData_LONG and sgptData_INSTRUCTOR_NUMBER, specify the data in LONG format that’s used by higher level SGP functions like abcSGP, prepareSGP and analyzeSGP.
In addition to SGPs, the data sgp package also generates student proficiency tables that show a student’s average score on a test section alongside their proficiency rating. This allows educators to quickly see how a student’s score compares to the performance of their peers in the same grade, subject or school.
This information can help them identify any areas where their students are struggling or excelling and allow them to adapt their teaching and assessments accordingly. Additionally, SGPs can be used to inform student progression decisions by showing schools how many percentage points of their achievement targets each student must grow in order to meet their goals. By identifying which students are close to their goals, teachers can target interventions and programs to assist those who need it and accelerate the pace at which others reach their goals.
