Data SGP is an invaluable tool for teachers and parents looking to better understand student learning and growth. By comparing assessment scores against academically similar peers, this analysis provides teachers and parents with insights into progress and relative performance – information which can be used to create learning plans for individual students. Educators can also utilize SGP reports to gain a clear and comparative picture of student growth over time.
SGP measures relative growth on a scale from 1-99; lower numbers represent slower relative progress while higher numbers reflect greater relative improvement. For example, an SGP score of 75 indicates more development than 75 percent of their academic peers.
Assimilate SGP data in two ways: take either the mean or median SGP score. A mean SGP score represents an average of all student SGP scores and may be sensitive to outliers; on the other hand, taking into account both high and low scores more accurately makes up a median SGP score and is less susceptible to being affected by outliers.
To ensure accurate SGP analyses, it is crucial that assessment data be properly prepared. To assist with this task, the SGP package offers various functions that can help. These functions include:
Sgp Vignettes are intended to guide users through each step in the data preparation process and point out common errors and their solutions. Any issues experienced during SGP analysis typically relate back to poor preparation of data; so it is crucial that users follow proper procedure when handling this step of data preparation.
The SGP data set, sgptData_LONG, includes seven variables including unique student identifiers, grade levels/time periods and vertically scaled assessment results – an excellent model of how to format assessment data for use with SGP analyses. Lower level functions studentGrowthPercentiles and studentGrowthProjections require data in WIDE format while higher-level wrapper functions (abcSGP and updateSGP) accept LONG formatted input data.
As part of SGP calculations, the first step should be importing all necessary state data into one file for analysis – reports can then be generated, trend charts made and projections generated using this information. SGP analysis is most useful when the most current assessment data is available, which is why long-formatted data sets are more manageable than wide ones. However, users ultimately make the choice of whether to utilize WIDE or LONG data formats when updating analyses with additional years’ of information. Should a user opt for WIDE data formats instead of LONG ones, they will need to take additional steps in order to convert their WIDE format data to LONG format (usually via running the prepareSGP function).