Data SGP utilizes longitudinal student assessment data to create statistical growth plots which measure students’ relative progress relative to academic peers, as well as projections of future growth based on an established growth standard. This information can then be used for informing instructional practices, evaluating educators/schools/districts, supporting broader research initiatives and providing insights for instructional practices/evaluation practices/evaluations/evaluations etc.
The SGP data set offers historical student performance information for grades 4-8 students. DESE calculates each SGP by comparing their current test score against results from prior assessments; using two most recent testing windows when calculating SGPs for students in grades 4, 6, and 8. Due to the nature of science tests, however, SGPs are unavailable for this subject area.
SGPs are only calculated on tests with valid scores. For students in grade 9, their SGP is determined based on an assessment taken during an earlier testing window (typically fall or winter); all other grades base their SGP on the most recently administered assessment.
Students’ current SGP is determined by comparing their test score against that of students from the same grade and subject taking an assessment at the same time, using a fixed number of academic peers as comparison groups. Students with high SGPs often display very different scale scores compared to those with lower scores as this means they were performing better on prior assessments than their counterparts who scored lower.
Making SGPs involves complex calculations with large margins of estimation error, so much time must be devoted to data preparation to ensure accurate and useful analyses are produced from them. Most issues encountered with SGP analyses stem back to inadequate preparation processes.
The SGP data set contains a table called sgpData_INSTRUCTOR_NUMBER that lists each instructor associated with a student test record. This table is updated after every assessment and available when you customize a Star Growth Report using its timeframe drop-down menu.
Students’ self-graded performances (SGPs) of teachers may be affected by individual learning characteristics of each student, as well as classroom environment and instruction. Therefore, educators who rely on SGPs as evaluation metrics should carefully consider all these other factors when making evaluation decisions regarding promotion and tenure decisions for teachers.
Although SGP calculations can be completed from any single year of data, we strongly advise operating analyses using LONG formatted data sets instead. This allows for easier management and takes advantage of additional features only available with LONG data sets. Furthermore, most functions used to do calculations (studentGrowthPercentiles and studentGrowthProjections) require LONG data and many of these higher level functions are built around having embedded SGPstateData meta-data within your long data set – saving your organization a great deal of time in running operational analyses.