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What is Data SGP?

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Data sgp is a system that utilizes longitudinal student data to produce statistical growth plots (SGPs). SGPs display the percentile ranks of a student’s current test score relative to those of students with similar prior achievement levels. This is a more accurate measure of achievement than unadjusted test scores and allows us to see a student’s performance in the context of their entire academic path rather than their current year only.

SGPs are estimated from students’ standardized test score histories and, like the prior and current test scores themselves, can suffer from large estimation errors. These errors make estimated SGPs noisy measures of the latent achievement traits underlying those scores. To help mitigate these errors, SGP analyses use two steps that compensate for the effects of the estimates of a student’s prior and current performance.

The first step is to compute a student’s current test score using their MCAS history. This is done by comparing the student’s current test score to the test scores of other students who have performed similarly on MCAS in the past. The second step is to compare the student’s current MCAS performance to a set of goals that have been established based on their prior test scores and MCAS history.

While the calculations behind SGPs are complex, the information they provide is communicated in terms that are familiar to many teachers and parents. As a result, SGPs can be used as an additional way to inform stakeholders about the academic progress of individual students.

A key feature of SGPs is that they are able to specify what a student’s future growth standard should be, allowing districts to establish achievement targets for their students and then track the progress that each student needs to make toward those goals. SGPs can also be used to inform stakeholders about the impact of various educational policies on student outcomes by illustrating the difference between actual and target growth for different groups of students.

One example of this is the impact that absences can have on a student’s growth rate. As shown in the table below, students who regularly attend school have higher true growth rates than those who skip class frequently. Likewise, students from families with low incomes tend to grow slower than those from wealthier families.

While it’s tempting to focus on short-term student outcomes, it’s equally important to recognize that students must learn and develop over time. In the long run, this is what will ultimately determine their success in college and careers. The challenge is to ensure that we are giving all students the opportunity to reach their full potential by providing them with an appropriate education. To do that, we must take a holistic view of each student’s unique journey and support them along the way. The ability to quickly and accurately access student data is critical in that effort.