What is Data SGP?

Data sgp is an educational database that contains information on many aspects of students’ academic performance. It is used by teachers and administrators to determine how well their pupils are doing academically, as well as to identify areas in need of improvement. This is important, as it allows them to make informed decisions regarding their student’s education.

SGPs are estimated from students’ standardized test score histories and can suffer from large estimation errors that can cause them to be noisy measures of latent achievement traits underlying these scores (Akram, Erickson & Meyer 2013; Lockwood & Castellano 2015). To help reduce these estimation error effects, SGP analyses employ two steps: 1) a comparison between a student’s current assessment performance and an estimate of their prior achievement level; and 2) a comparison of a student’s current assessment performance with other students’ previous achievement levels across time.

Using a student’s longitudinal data set, SGP analyses produce a graph that displays the percentile ranks of their current assessment score relative to other students who have taken tests in the same content area at different points in time. These percentile ranks are computed using a distribution from several years of compiled test data, rather than one year alone, so that the resulting knots and boundaries are smoother and more accurate than those produced by comparing a single year’s test results to other students’.

The sgptData_LONG data set is an anonymized, panel data set that includes 8 windows (3 windows annually) of assessment data in long format for 3 content areas (Early Literacy, Math and Reading). These data are comparable to the sgpData_LONG dataset without the demographic variables that are used to create student aggregates. The sgptData_LONG dataset also includes the sgpData_INSTRUCTOR_NUMBER lookup table which provides insturctor information associated with each student’s test record.

For most analyses, the sgptData_LONG is used for both baseline and cohort SGPs. The default choice for the SGP package is to use baseline SGPs because, by construction, they allow us to track changes in aggregate student growth over time. Cohort-referenced SGPs, on the other hand, are calculated by comparing a student’s current assessment score with their cohort’s average test score in a given year, which can introduce an artificial artificial bias into our estimates of growth.

To address this issue, the SGP package utilizes a “baseline” cohort, which is constructed by selecting the 20th, 40th and 60th quantiles of the observable scale score distribution for all students in each grade level. By doing so, we can ensure that the average progression rate for the baseline cohort is identical to the statewide mean and median for both cohort-referenced SGPs and benchmark SGPs. This approach is similar to the way that we compute student and school-level MGPs for the ACT Aspire benchmarks. However, the distinction between baseline and cohort MGPs is less straightforward when evaluating MGPs for individual schools or districts. This article will explore the reasons why this is so.