Data sgp is an analysis tool for longitudinal student assessment data that creates statistical growth plots (SGPs). SGPs provide visual evidence of students’ progress relative to their academic peers. SGPs also incorporate students’ prior testing history, allowing for more accurate measurements of student progress than traditional percentile scores alone.

While the term “big data” has become popular in science, business and modern life, the sgp research that is currently taking place is relatively small potatoes when compared to the amount of data that would be required to analyse global Facebook interactions. As such, it is more appropriate to think of the data sgp effort as a ‘medium data’ project, one that will allow for the assembly and analysis of a large number of datasets but one that is still manageable by standard relational database applications.

In order to use the data sgp tool, educators can either access the summary report or the more detailed sgpData spreadsheet. The sgpData spreadsheet provides SGP data for each student over the course of five years (see the Data SGP Format section below for more information on how the time dependent data is stored). The first column, ID, provides the student’s unique identifier. The following 5 columns, SS_2013, SS_2014, SS_2015, SS_2016 and SS_2017, provide the student’s assessment score from each of the five years that they have been tested.

SGPs are based on DESE’s standardized test results in ELA and mathematics for grades 4 through 8, and in science for grade 10. When available, the most recent year of prior test data is used.

Using the SGP tool allows teachers and administrators to compare a student’s current growth percentile with their target growth percentile. This can help them identify students that need additional support or are making progress at an accelerated pace. It can also serve as a motivational tool for teachers by linking their performance against official state achievement targets and goals.

In addition to identifying student proficiency, SGPs can be used to determine which student groups need more focused instruction and resources. These can include low-performing schools/districts, at-risk students and English language learners. This information can be useful in directing the work of the state’s education system and helping to inform policy decisions.

SGP analyses require the user to have a working knowledge of the R programming language, which is freely available for Windows, Mac OSX and Linux users. If you do not already have R installed on your computer, download and install it from the CRAN website. For guidance in running SGP analyses, consult the SGP Data Analysis Vignette. The vignette includes an example WIDE format data set to simulate the time dependent data used by lower level functions such as studentGrowthPercentiles and studentGrowthProjections, as well as a LONG format data set to assist with conversion into this format. In almost all cases, errors encountered while analyzing SGPs will revert back to issues with data preparation. This is why it is important to spend adequate time on data preparation prior to attempting any SGP analysis.