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Student Growth Percentiles (SGPs) provide an estimation of student’s relative progress as measured against classmates who share similar MCAS performance histories. Estimated SGPs can provide an invaluable comparative measure for inference and decision making as they provide a comparison measure between student’s performance compared to that of peers.
Recent research has demonstrated that estimates of student growth based on standardized test scores are inexact measures of latent achievement traits (Akram, Erickson & Meyer 2013; Lockwood & Castellano 2015; McCaffrey Castellano Lockwood McCaffrey Castellano Lockwood McCaffrey Castellano Lockwood McCaffrey Castellano Lockwood McCaffrey Castellano Lockwood McCaffrey Castellano Lockwood 2015 McCaffrey Castellano Lockwood Lockwood 2015); these errors lead to large estimation variances which lead to inaccurate performance indicators.
This variance constitutes an element of bias when using aggregated SGPs as indicators of teacher effectiveness. To mitigate it, one option would be estimating a value-added model that regresses student test scores on teacher fixed effects, prior test scores, as well as student background variables.
SGP Package functions that perform calculations such as studentGrowthPercentiles and studentGrowthProjections require WIDE formatted data; their higher level function wrappers (teacherGrowthPercentiles and teacherTestPerformanceProjections) however require LONG formatted data. If performing more advanced analyses than basic analyses is of interest, we strongly suggest setting your data up using LONG format instead of WIDE.
Once data are prepared properly, conducting SGP analyses is usually straightforward. Any discrepancies found typically trace back to improper preparation issues that affect data preparation.
SGP analyses are intended to be as straightforward and user-friendly as possible, which is why we provide detailed descriptions of each step involved in data preparation and running SGP analyses.
Additionally, we have produced several vignettes illustrating common SGP analysis tasks. If there’s something specific you would like us to provide a vignette on, let us know and we will try our best to come up with something relevant for your task.
No matter whether you need an insight into student growth data for yourself or other teachers, or want accurate data sgp tools to evaluate student development. In this article we explain how to use the SGP data tool effectively in order to gain this insight.
The SGP data tool offers a new way of visualizing student development within your school. It enables you to track trends over time, determine which subjects or grade levels have shown increases, as well as detect those students falling below the class median.
To gain access to this data tool, Massachusetts public schools need only log into EduStat and select the “SGP Data” link from the left-hand menu.
