Data sgp is the collective of aggregated student performance data collected over time that teachers and administrators use to make instructional decisions and evaluate schools/districts. It is a set of individual-level measures like test scores and growth percentiles, as well as aggregated measures at the school and district levels including class size, attendance rates and graduation rates. The goal of data sgp is to help educators better understand students’ learning progress over time and improve classroom instruction and educator evaluation systems.
Growth percentiles are a metric that measures a student’s academic achievement progress relative to their academic peers. They provide a more meaningful measurement of students’ academic progress than traditional percentile or mean/median scores and are a useful tool to inform instructional decision making, teacher evaluation practices and support educator-student relationship research.
The purpose of this project is to provide a flexible and customizable statistical software environment and user-friendly interface for educational researchers to analyze and visualize longitudinal (time dependent) student assessment data. The software is designed to be used by both novice and expert users. It can be run in either the command line or as a Python script and provides both flexibility and control over the analysis process.
As the amount of data collected about education and students continues to increase, it becomes increasingly important to have software tools that allow educators to access, analyze and interpret these large datasets in a useful way. Data sgp is an open source software application that allows educators to analyze longitudinal student assessment data and create statistical growth plots. These growth plots enable educators to see a student’s academic performance over time and to identify areas where improvement is needed.
This tool is designed to be as simple as possible for new users to understand and use. The bulk of the work involved with SGP is in data preparation and once this is completed, analyses using SGP are relatively quick and straightforward. We provide a number of tutorials and videos to assist new users in getting started with SGP.
SGP analyses are typically conducted using the R statistical software environment. This is a free and widely available tool that is commonly used for academic assessment analysis, although it can be used for other types of statistical data analysis as well.
The R software requires a modern computer running Windows, OSX or Linux with the latest version of Java installed. This is a free, open source program that can be downloaded from the R website.
The sgpData data set includes an exemplar WIDE format data set that simulates the time dependent data used with lower level SGP functions (studentGrowthPercentiles and studentGrowthProjections), as well as a LONG format data set to assist in converting WIDE format data sets into this data structure. This sgpData data set also includes an instructor lookup table that identifies the teacher associated with each of a student’s test records. Each student can have multiple instructors associated with their test record during a given year.