Data sgp is an analysis tool for the statistical software environment R. To use it, you must have a computer running windows, macOS or Linux and access to R’s open source version. It is designed specifically for analyzing educational assessment data but it can be used with any kind of statistical data. Like most analysis tools it requires the bulk of its time to be spent on data preparation. Once the data is ready to be analyzed it can be done quickly and efficiently.

The key to interpreting data sgp is to look at the percentiles. The percentiles represent the relative progress of students as compared to their peers with similar MCAS score histories. In other words, if a student’s SGP is 85 then it means that she scored higher on her MCAS in grade 8 ELA/math than half of the students with similar scores.

SGP stands out from competing approaches by allowing schools to establish multi-year growth standards based on official state achievement targets/goals. This allows schools to communicate with stakeholders that proficiency must be reached within a certain time frame. It can also serve as a tool for identifying students that need assistance in reaching proficiency – either accelerating their learning or providing additional supports.

To use data sgp you will need to be familiar with the basics of the statistical software, the R language and how to prepare your data for analysis. There are a number of online resources that can help you get started with the necessary skills and software.

Once you have the proper software and data prepared a run of data sgp will only take two minutes. During this time the results will be displayed on screen, saved to a file and downloaded to the local computer. This will allow you to view your results with a text editor or Excel spreadsheet.

We recommend that you download and work with the sgptData_LONG dataset as it provides an example of a complete data set for the use of the lower level SGP functions. The data set includes sgptData_LONG variables for VALID_CASE, CONTENT_AREA, YEAR, ID, SCALE_SCORE and GRADE (required if running student growth projections). It also includes the SGPstateData meta-data needed by the higher level SGP functions.

If you are not familiar with the R language or how to prepare your data for analysis, we recommend that you consult the documentation for the SGP package. A number of vignettes have been developed to guide you through the process. Depending on the type of analysis you are looking to conduct, there may be more detailed documentation that is specific to that process. If you have a specific question about using the package that is not covered in the documentation feel free to contact us. We will be happy to assist you.