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The SGP model utilizes the historical growth trajectories of Star examinees to map out what the range of possible trajectories might lead to, including what growth is necessary for students to reach or maintain proficiency. These projections are updated regularly so that students’ projections are based upon the most recent data available. The SGP is a great tool for educators to use in identifying individual student learning needs and planning appropriate interventions for each student.
When a student’s SGP falls below the state target, a teacher may be encouraged to make additional adjustments in their instruction to ensure that the student makes adequate progress towards the goal. These interventions can include small group and one-on-one instruction, additional practice in specific subject areas, or the use of new instructional materials. These interventions can help a teacher address the specific needs of each student and support them to achieve their educational goals.
A student’s SGP rises above the target when their performance improves. This is because the student’s learning gains are greater than their previous scores. A student’s SGP will fall below the target if their performance declines. This can be caused by a number of factors, such as a student’s level of mastery, a drop in test scores, or a negative impact from a special education program.
It is important to understand how SGP scores are calculated and the factors that influence them. SGP scores are a valuable indicator of student progress, but they can be misleading if used incorrectly. For example, aggregated SGP scores can be biased if they are interpreted as an indication of teacher effectiveness. This bias is easy to eliminate in a value-added model that regresses student test scores on teacher fixed effects, prior test scores, and student background variables. This type of model reduces the variance due to teacher-level relationships, and therefore provides more reliable measures of teacher effects. This type of modeling approach is also more transparent to teachers. However, the trade-off is the increased complexity of these models. Some educators might prefer to stick with simpler models when calculating SGPs.