How to Get the Most Value From Data SGP
Data SGP provides students and educators with a wealth of information that can be used to understand their student’s progress over time. This information can be used for a variety of purposes including identifying areas for improvement, informing instructional practice, supporting classroom research initiatives and evaluating schools/districts. However, there are a number of common errors that can be made when using this information which can significantly limit its value. This article is intended to highlight some of these errors, how to avoid them and provide guidance on getting the most value from this data.
Data SGP is a set of measures that describe the amount of growth a student has demonstrated relative to academically-similar students. These metrics are reported on a scale of 1 to 99 and can be interpreted like percentile ranks, with higher numbers indicating more relative growth than lower ones. In other words, a student who scores a 75 on the Badger Exam has performed better than 75% of her academic peers (assuming all students had the same achievement history).
SGPs are available for all students in grades 4-12. SGPs are reported by individual grade level and also by high school, to provide an opportunity for analyzing growth among all students in the district, as well as the progress of individual students within the system.
Educators can access data SGP for their students through the dashboard and student report cards. They can also access more detailed data by selecting a specific student in the report card and choosing the SGP Data tab. This spreadsheet contains SGP results for the student over five years and includes the student identifier in column 1, along with assessment data from the Badger Exam and the Forward Exam (in that order).
The first row of the spreadsheet provides the SGP score for each year, followed by the student’s actual scale score for that assessment. The next row of the spreadsheet displays the growth percentiles, which are compared to students in the same academic profile. The last row of the spreadsheet displays the projections and trajectories, which are based on the growth percentiles and the predicted scale score at the end of each assessment year.
The process of preparing and running SGP analyses requires a good understanding of the mathematical models behind this approach. It is therefore recommended that all users of this tool familiarize themselves with the SGP vignette, which includes detailed information on how to prepare and conduct these analyses. Alternatively, for a more general introduction to using wide-format data sets with this package, see the Data Analysis vignette. In both cases, the bulk of the time spent with this package is on data preparation and the analysis itself is designed to be simple and straightforward. Despite this, it is very important that users are aware of the assumptions and limitations associated with this methodology before they proceed with any analyses. The more familiar they are with the underlying model, the easier it is to spot and avoid the pitfalls that can reduce the value of this data.