Data SGP is an analysis tool built specifically for use within the R software environment. Open-source and free to download for Windows, OSX and Linux users alike, SGP analyses require familiarity with R and its usage; there are various resources online which can assist newcomers.

Data SGP not only assists educators with pinpointing issues in student achievement, but can also pinpoint effective strategies to enhance performance of individual students. To derive maximum value from this powerful tool it is imperative that schools dedicate enough time and effort into organizing data into usable databases before conducting analysis – failure to do so could produce inaccurate and misleading results – particularly when trying to compare individual performance against their peers.

The Student Growth Percentiles (SGP) method uses large-scale longitudinal education assessment data to generate student growth percentiles (SGP) and percentile growth projections/trajectories (PGP). Schools using PGP can use it to set multi-year achievement targets/goals that provide stakeholders with a timeline in which a proficient student must reach state requirements.

SGP measures student test score progress against that of their academic peers nationally. Calculations use prior test scores, current score and growth expectations determined using Betebenner’s catch-up/keep-up SGP methodology to generate accurate estimates of SGP growth expectations.

SGP data enumerates various student and teacher details; beyond providing identification data of each unique student ID, SGP contains instructor numbers for every student as well as lists of teachers who have taught them across years and content areas. This data allows us to generate longitudinal student growth trajectories as well as teacher averages that help track student progress toward achievement targets.

As part of its data preparation for SGP analyses, duplicate student records often present a challenge. To address this, Data SGP includes a function for renaming them: the prepareSGP function can take as key fields VALID_CASE, CONTENT_AREA, YEAR and ID and create new records based on this key value. Furthermore, prepareSGP may optionally produce other variables useful in analysis such as HIGH_NEED_STATUS or INCOMPETENCE_RANK which help address this problem.

SGP analyses are only applicable to students who have participated in at least two separate testing windows, so schools should factor this into their SGP analyses as part of a school calendar decision. To ensure all eligible students can benefit from using this tool and improve student outcomes. Likewise, it should be noted that for optimal SGP analyses to take place it’s essential that at least four different testing windows were involved and at least one assessment taken during all four.