Data SGP is a collection of data analysis tools created to assist educators with accurately assessing students’ progress and pinpoint areas for improvement in classrooms. It enables educators to more precisely articulate student achievement goals, support high achieving students more directly, and assess accelerated programs more objectively – thus eliminating any possible issues due to those few students who do not make sufficient gains.
Understanding SGP requires understanding its mathematical models and assumptions that underlie its calculations, so for newcomers the SGP package contains tutorials and examples that explain these fundamental concepts. Furthermore, articles provide an overview of its methodology as well as explaining its underlying assumptions as well as its implementation into practice – it is imperative that you fully grasp these ideas before trying to apply SGP on your own data sets.
SGP leverages students’ current test score and prior test scores to generate projections of their future academic performance compared with peers. This information is conveyed using familiar percentile terms familiar to teachers and parents, providing useful predictions of students needing additional assistance, feedback on classroom instruction, or informing school/district research initiatives.
Students’ SGP trajectories can be studied to ascertain how much growth is necessary to reach/maintain proficiency and identify trends over time. With this data in hand, tutoring or summer school could potentially improve outcomes for these students; and additionally the analysis could inform school/district goals for helping accelerate them towards grade level expectations.
SGP (Student Growth Percentile) estimates how much their raw test score has improved relative to students with similar prior test scores (their academic peers). It allows teachers and administrators to quickly communicate current levels of proficiency among students as well as project future performance using numbers that are more intuitive than traditional assessment metrics.
An administrator must prepare data in the sgpData data set and execute one of the lower level SGP functions (studentGrowthPercentiles or studentGrowthProjections) before running one of the higher level functions that produce visualizations or more in-depth SGP analyses that require LONG formatted data.
At our firm, most SGP analyses we assist with are run using the SGP Vignette Dataset – a publicly accessible data set which contains all of the data and metadata necessary for conducting an in-depth SGP analysis, including state specific meta-data embedded into it. While Wide format downloads may be possible from here as well, our lower level SGP functions work best when used with Long data formats – in particular since managing and updating long data is much simpler than Wide data. Analyses can be run on one year of data or multiple years of data.
