Data sgp is a set of tools that allows users to run operational analyses and reports against state-specific data. Its lower level functions, studentGrowthPercentiles and studentGrowthProjections, require WIDE formatted data while the higher level functions (wrappers for the lower levels) require LONG data. We recommend using the LONG format for all operational analyses as it is more simple to manage and most of the higher level SGP functions assume that your data will be in this format. In most cases, errors that arise during data analysis revert back to issues with data preparation so ensuring your data is prepared correctly before running SGP analyses is important.
Student growth percentiles are measures of a student’s relative progress on MCAS in comparison to other students with similar MCAS performance histories. A student’s SGP is calculated by comparing their current test score to the 90th percentile of the most recent cohort of students who performed like them in the same content area and grade. For example, a student’s SGP could be calculated by comparing their current test score to that of the 10th grade class in ELA or math and by using their highest MCAS score from the two most recent tests taken.
In addition to the student data, the sgpData data set also contains teacher information and student demographics. The sgpData_INSTRUCTOR_NUMBER field is an anonymized list of teachers that are associated with each student’s test record and the sgpData_STUDENT_DEMOGRAPHIC_FIELDS field contains data on a variety of student characteristics that can be used to determine the student’s grade-level status, such as gender, race/ethnicity, socioeconomic status, and disability status.
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