As the state of Michigan implements teacher evaluation systems, educators need data that is accurate, timely and clear. Data SGP is an accessible tool that provides this information. SGP stands for Student Growth Percentile, and is an aggregated measure of a student’s current achievement in relation to other students with similar prior achievement (Betebenner, 2009).

The goal of data sgp is to provide teachers with reliable and useful information about student growth by using longitudinal data from the M-STEP assessments. It provides a new way for educators to view and interpret their students’ performance in the classroom, and can be used as part of educator performance evaluations.

It also allows districts to identify students that need additional support and resources. Educators can then use their individual student SGP scores to inform classroom instruction and develop Student Learning Objectives (SLOs). Districts can also share aggregated SGP data with parents.

SGPs are calculated for students in grades 4 through 8, and for students in grades 10 and 12 who have valid M-STEP test score histories. The SGPs in ELA and math compare current test scores with the same prior test score from a previous grade level. Similarly, SGPs in science compare current test scores with 8th grade test scores, which were the highest available tests for students to take at that time.

Data sgp is a free resource for educators to help them better understand and analyze the data from their student assessments. It is easy to use and provides valuable information about student progress, teacher effectiveness and school improvement initiatives. The website includes a collection of interactive tools and podcasts to guide users through the process.

While SGPs are a promising measure of student performance, there are some concerns. For example, a SGP can be distorted by the influence of a small number of high-achieving students who can’t keep up with the rest of their class. This is especially true in accelerated programs, where students can advance quickly and fall behind other classmates with more comparable knowledge, skills and ability.

Another issue is the large estimation errors associated with standardized testing. These errors are a function of the large number of items in most standardized tests, and are even larger when multiple assessments are used. This means that SGPs, which are estimates of a student’s latent achievement trait, can be inaccurate measures when the prior and current test scores used to construct them are error-prone.

Finally, it is important to remember that SGPs should not be interpreted as indicators of teacher effectiveness. SGPs can be influenced by student and classroom factors that cannot be controlled for in value-added models. Therefore, interpreting SGPs as teacher evaluation indicators could be misleading and may lead to biased conclusions about the effectiveness of individual teachers. These biases can be avoided by using a value-added model that regresses student test scores on teacher fixed effects, prior test scores and student background variables. This type of model is more accurate and has been shown to be more predictive than aggregated SGPs (see Educator Data Tools, Macomb and Clare-Gladwin ISD).