Data SGP is a critical part of the SGP package, offering classes, functions, and data structures for calculating student growth percentiles (SGP) and projections/trajectories based on large scale longitudinal education assessment data. Quantile regression techniques are utilized in order to estimate conditional density associated with an individual student’s achievement history and then used to compute current SGP and projection/trajectory required to reach future performance targets.
The SGP package features the sgpData data structure which provides an easy way to store, access and manage student growth information across several analyses. This structure includes unique student identifiers, grade level of most recent test taken as well as scale score data from prior five year tests administered. Furthermore, it includes a “Method” field which shows which methodology was employed when computing each SGP analysis.
Operational SGP analyses involve both preparation and analysis of SGP data. Most analyses that we assist on utilize a two step process: Prepare SGP data, then Analyze SGP data. To maximize efficiency the SGP package provides wrapper functions which “wrap” multiple steps into one function call to streamline operations and reduce source code requirements needed for conducting analyses.
SGP compares a student’s growth against that of their academic peers nationwide. Academic peers refers to those in the same grade with similar achievement histories on Star assessments. It provides educators and parents with insight as to whether their child is growing faster, slower or similarly than his or her academic peers nationally.
To calculate SGP, we begin by compiling student growth data sets for all students. The first step in this process is creating a file with student identifiers and grades from five most recent Star assessments taken by each individual student; this file can then be loaded into SGP package using prepareSGP function before being analyzed by functions like studentGrowthPercentiles and studentGrowthProjections.
Finalize SGP processing by using combineSGP’s function to compile all results derived from these analyses into one master longitudinal record for each student. This step allows schools and districts to generate the SGP trajectories and projected growth needs that appear on report cards, which is essential in assuring accurate SGP reporting and providing informed decision making in schools and districts. This process yields a master longitudinal record that can help us evaluate whether students are on track with meeting their educational goals, make decisions regarding any necessary interventions for that student, as well as inform conversations between families and community members regarding progress towards educational goals.
