Data SGP and SGPdata

Data SGP refers to an aggregated set of student performance information collected over time that teachers and administrators use for decision-making in instruction and assessment. It includes individual-level measures like test scores and growth percentiles as well as aggregate measurements at school/district levels such as class sizes, graduation rates and attendance figures.

SGP provides educators with a more accurate measurement of student achievement over time than average, median, and mode scores can provide. This data helps educators identify those students needing additional support; differentiate classroom instruction for high-performing learners; monitor progress of those performing below expectation; as well as make accurate predictions regarding future student performance when used alongside longitudinal data.

SGP is a metric developed to track student achievement progress over time using longitudinal test score data. It relies on latent achievement trait models estimated using teacher evaluation criteria as growth standards to minimize estimation error while increasing validity when comparing students, helping educators better inform instruction, assess student/teacher performance assessment systems and support teacher evaluation systems.

An SGP score compares a student’s assessment scores against those of their academic peers. The higher the SGP score is, the more relative improvement that student has shown – for instance, an SGP score of 75 indicates they have made significant strides forward compared with their academic peers.

Sgpdata is an R package that assists in the analysis of longitudinal student assessment data. It creates statistical growth plots (SGPs) which demonstrate student progress over time relative to academic peers. Furthermore, this package offers an exemplar WIDE format data set (sgpData) as a proxy for time dependent data used with lower level functions like studentGrowthPercentiles and studentGrowthProjections as well as LONG format files which may help in their conversion into this format.

SGPdata includes not only SGP data sets, but also higher level function wrappers that take advantage of this format of data. These functions perform many of the same analyses as lower level SGP functions but are typically easier to use due to reduced data preparation and storage burden.

The SGPdata package supports the inclusion of state specific meta-data within SGPstateData to enhance accuracy and efficiency in SGP analyses. This meta-data is typically utilized when calculating student growth projections/trajectories necessary to reach specific achievement targets or goals, and also serves to create an individual matrix of growth rates for every student in an educational environment. SGPs provide an effective means for evaluating the effect of personalized education programs on student achievement and can be used to inform instruction, evaluate teacher effectiveness, and support educator evaluation systems. However, they should not replace traditional academic achievement goals or targets but should instead serve as complements.