Data sgp is an important tool for examining individual student growth and achievement. It allows educators to compare the performance of students with similar prior achievement, a process that has long been recognized as a fairer and more relevant way to evaluate both student progress and educator effectiveness than examining unadjusted achievement levels alone. The SGP Package provides functions for calculating student growth percentiles and projections, analyzing the results, and creating a graph showing the growth and achievement of a given student over time.
In addition to the lower level SGP functions, this package also provides higher level wrapper functions that can simplify the source code associated with running an SGP analysis. For example, the SGP package includes the functions abcSGP and prepareSGP that wrap the 6 steps required to run a basic SGP analysis into a single function call. This is especially helpful for operational analyses, where these steps are typically conducted simultaneously and are often repeated each year, making the use of these wrapper functions significantly simpler than implementing the lower level SGP functions from scratch.
The SGP package supports both wide and long format data sets. While using a wide format data set is straight forward, using a long format is a little more involved. To help users determine which data format to use, there is a vignette available that describes the differences between using WIDE and LONG data formats with the SGP package. In general, the use of a LONG data format is preferable for all but the simplest, one-off analyses. In addition, the longer data sets allow for more robust preparation and storage functions compared to the WIDE data formats.
The exemplar data set sgptData_LONG contains an anonymized panel data set of 8 windows (3 windows annually) of assessment in the LONG format for 3 content areas (Early Literacy, Mathematics, and Reading). The sgptData_LONG set contains student-instructor lookup tables, sgptData_INSTRUCTOR_NUMBER, that provide the instructor numbers associated with each student test record. This allows instructors to be assigned multiple times to a student for the same content area and year.
SGP analyses are conducted by comparing the student assessment score from a given grade to a previously reported measure of student achievement. This comparison can then be used to calculate student growth percentiles and project future scores based on the current grade. In the case of a student with a history of failing grades, the projected scores can be used to identify the student’s expected level of proficiency at each grade, allowing educators to monitor a student’s academic progress and adjust instruction accordingly.
SGPs are most useful when analyzing student achievement data from the same year, but they can also be used with multi-year and cross-year data to analyze trends in student achievement. In addition, SGPs can be used to examine the impact of instructional strategies on the progression of student learning over time. While this is still a relatively new and emerging field, there are already many educational organizations that are using SGPs to support their instruction and evaluation of educator effectiveness.