Data sgp is an important part of the SGP system that allows teachers to see how their students compare to their academic peers. Educators can use data sgp to understand student growth and make decisions to accelerate student achievement. In addition, educators can also use data sgp to identify low achieving students so they can provide appropriate interventions.
SGP is working to assemble an unprecedented amount of information on a large scale for scientific purposes but it is still relatively small in comparison to data sets used for, say, global Facebook interactions. For this reason we think of SGP research as’medium data’ rather than ‘big data’ (see Is it really big data?).
The sgptData_LONG data set is an anonymized, panel data set that includes 8 windows (3 windows annually) of vertically scaled assessment data. This data set models the format required for the lower level SGP functions studentGrowthPercentiles and studentGrowthProjections. The sgptData_LONG format has 7 required variables: VALID_CASE, CONTENT_AREA, YEAR, ID, SCALE_SCORE, GRADE and ACHIEVEMENT_LEVEL. All other variables are demographic/student categorization variables that are used by the summarizeSGP function.
This data is available through NJ SMART by linking district course roster submissions with the relevant mSGP scores for each qualifying teacher. Districts are required to submit accurate rosters and should verify accuracy with their supervisors prior to submission. The mSGP score is then translated to a medial student growth percentile using the median student growth percentile conversion chart. This is tabulated with the teacher practice score and SGO score to calculate a teacher’s final evaluation rating.
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