Student growth percentiles measure how much students have improved when compared with students with similar prior test scores (academic peers). Their calculation uses quantile regression. The SGP package offers classes, functions and data that enable the calculation of percentile growth projections/trajectories using large scale, longitudinal education assessment data; lower level functions like studentGrowthPercentiles and studentGrowthProjections use quantile regression coefficient matrices obtained through quantile regression for this process and provide educators with useful information in setting realistic achievement goals that target achievement goals accurately for every student.
Data Stewards are crucial members of any organization who understand both the big picture and small details about how the company creates, manages, manipulates and stores data as well as how this data is being utilized by staff and the wider community. Data stewards act as liaisons between technical staff and those most in need of accessing that information.
The SGP project began in 2015, with its primary aim being the compilation or generation of multiproxy sedimentary geochemical data for Neoproterozoic to Paleozoic sediments spanning Neoproterozoic to Paleozoic time periods, including parameters like iron, carbon, sulfur and major and trace metal isotopes among others.
As depicted above, sgpData contains one row for each student with their ID number, followed by five columns providing assessment scores from every year of testing. If a student lacks five years’ worth of test results then their record will display missing value or NA.
sgpData was specifically designed to work with LONG format data sets, and many higher level functions in the SGP package are intended to work on such long data sets. For operational analyses, it is highly recommended that you make use of wrapper functions abcSGP and updateSGP that simplify source code associated with these calculations.
The sgpData function can also help create district screening windows to assess whether students are ready to enter the next grade level and identify those needing additional support. The sgpData function offers an efficient way of quickly comparing student performance across an entire district and can quickly reveal any issues which might be hindering students’ ability to excel academically. Schools and districts seeking to increase accuracy in Star assessments and make more informed decisions regarding student progress can use this useful tool. sgpData will regularly be updated to reflect the most up-to-date data; you can find updates here. sgpData is an invaluable tool for educators working to help every student reach his/her full potential, which is why its reliability, accuracy and timeliness is of such great value to educators. We thank our partner from the Department of Education for making it available.