Data sgp is the collective of aggregated student performance data collected over time that teachers and administrators use to make decisions about instruction and assessment. This data can include individual-level measures like test scores and growth percentiles as well as aggregated measurements at the school and district levels such as class size and attendance rates. Using this data helps educators and administrators identify areas for improvement, inform classroom practice, evaluate schools/districts, and support broader research initiatives.
Unlike most assessment metrics, student growth percentiles are reported relative to the score of academic peers. A student’s growth percentile indicates how much his or her raw score on a specific test section has grown in comparison to other students with high scores on previous test sections. Student growth percentiles can help educators and administrators determine whether a student is making progress towards achieving grade level achievement.
SGP analyses can be conducted with longitudinal (time dependent) student assessment data in either WIDE or LONG format. We recommend the LONG format for operational analyses since it offers advantages in terms of data preparation and management. The SGP Package includes lower level functions called studentGrowthPercentiles and studentGrowthProjections that can be used with either format; however, higher level wrapper functions (abcSGP and updateSGP) simplify the source code associated with these lower level functions for LONG format data sets.
These higher level wrapper functions assume that the exemplar LONG format data set sgpData_LONG, the embedded student-teacher lookup file sgpData_INSTRUCTOR_NUMBER, and state specific meta-data stored in the SGPstateData structure are available. In addition, these functions require the sgpData_LONG variable to be updated on an ongoing basis with new years of data.
The process of creating these SGP reports is fairly straightforward. Start by identifying the raw data you would like to analyze, then decide which columns should display the statistical categories and their decimal formats. For example, you may want to only display three decimal places in the BA column and two in the ERA and WHIP columns. Finally, spend a minute formatting the cells in the stat category columns so that their appearance makes sense. You can also add a heading to each column that explains what type of statistic is being calculated. To do this, right click on the column heading and select “format cell.” From there you can change the font size and style of text as needed. Then you can save the report as a PDF or Excel spreadsheet by clicking on file and selecting save as.