Data SGP is the collective of aggregated student performance data collected over time that teachers and administrators use to better understand students’ progress and inform instructional practices. It includes individual-level measures like test scores and growth percentiles, as well as aggregated measures at the district and school levels such as class size, attendance rates, graduation rates, etc. This information is important because it allows educators to identify areas for improvement, inform classroom practices, evaluate teachers/schools/districts, and support broader research initiatives.
In order to make effective decisions based on SGPs, schools need accurate and comprehensive data. However, collecting, analyzing and managing this data can be daunting and time consuming for teachers, administrators, and IT teams. This tool provides a user-friendly, automated approach to extracting, processing and visualizing statewide SGP data. The tool can be run from a command line or from a script and requires the use of the statistical software environment R (Betebenner, VanIwaarden, Domingue, Shang, 2014). The tool is designed to be easy-to-use and supports a variety of analysis functions including the calculation and display of student growth percentiles and trajectory plots.
This tool is available to all ACT member states and can be downloaded for free from GitHub at http://datasgp.r-projects.org/. It is not intended to replace existing statewide student achievement and teacher evaluation systems but rather to provide additional data to help inform those systems. This is particularly critical for systems in transition from a student growth system to an educator evaluation system.
The SGP calculations are based on large samples of students from across the country who have tested in recent years through school day testing programs. Samples are weighted to be more representative of the national population of students who take ACT assessments with respect to student demographics (student race/ethnicity and gender) as well as student poverty level and school type (public or private).
To estimate SGPs, the software uses quantitativeile regression methods that allow us to calculate percentile growth trajectories for students by comparing their current test scores to the performance of academically-similar peers. Percentile growth trajectories are useful for measuring the extent to which a student grows relative to their academically-similar peers, and they can be used to identify areas of rapid or slow growth.
The tool allows users to specify a range of parameters for the analysis and visualization of student growth percentiles and growth projections. These include the use of WIDE or LONG format data, a Boolean argument indicating whether to simulate SGP values for each student based on test-specific conditional standard error of measurement (CSEM) estimates provided in the input file SGPstateData, and an argument determining how many years of growth should be displayed in the student growth plots. The output can be saved as a PDF, PNG or JSON file. The tool can also be configured to zip school folders containing the student growth plots to facilitate distribution.
