Data SGP is a set of statistical analyses that provide teachers and administrators with a more complete picture of student achievement. This set of analyses identifies a student’s performance relative to his or her academic peers, as well as how much the student has improved from one year to the next. These results are provided to educators and families in the form of student growth percentiles, which are calculated using methods developed by Damian Betebenner at the Center for Assessment at NCIEA. More information about student growth percentiles can be found on the Student Growth Percentiles and Resources webpage.

SGP results are based on the comparison of students with similar MCAS score histories (i.e., academic peers). Academic peers can be in the same grade as the student or any other grade that has MCAS test history for that particular subject area. Academic peers also do not have to be in the same subgroup (e.g., special education, race/ethnicity, multilingual learning). The same student can have multiple academic peers, but each peer group has its own average score from prior MCAS administrations.

Unlike traditional student assessment reports that only show a single score, student growth reports display a student’s growth from year to year in the context of the state’s student-growth model. This model is based on the principle that all students enter school with different abilities and needs, so it is important to measure their progress in relation to the performance of students in their academic peer groups.

In addition, the data sgp provides educators with information about how their own teaching practices may impact student outcomes. For example, a teacher who has not made significant gains in their students’ growth from year to year is unlikely to be recognized as an effective educator.

The sgpdata data set provides access to the underlying data used by the higher level studentGrowthPercentiles and studentGrowthProjections functions. It is available in both LONG format and WIDE format. We recommend using the long data set because it is more manageable for operational analyses, and because all of the lower level functions assume the existence of the embedded SGPstateData meta-data in the sgpdata data set.

This dataset includes the student identifier, content area, years of assessment, and scale scores for each student. It also includes a column for the teacher of record that is associated with each student’s assessment records, as well as a date variable that indicates when the record was created or modified.

This exemplar dataset is designed to provide a template for the required information needed to support student growth percentile calculations and student growth projections. The sgptData_LONG dataset contains 5 years of longitudinal assessment data in long format, for three content areas. This data set is comparable to the sgpData_LONG dataset but does not contain the teacher-instructor lookup variables required for use with the lower level studentGrowthPercentiles functions. The sgptData_INSTRUCTOR_NUMBER data set adds the teacher-instructor lookup variables for use with those functions.