Data SGP (Student Growth and Progress) is an aggregate of student-level measures such as test scores and growth percentiles that is collected over time to support learning and teaching. This information can help shape classroom practices, school/district policies and support larger research initiatives.
SGP uses longitudinal student assessment data to create statistical growth plots (SGPs), which measure students relative progress relative to academic peers. This can help educators determine whether students are making adequate academic progress or meeting an agreed upon growth standard (e.g. 75% growth standard), but doing so requires much time and can result in large estimation errors.
sgpdata is an open source project that offers an easier way to create SGPs using student data. Users can specify how many years to include, with an easily customizable and resizable display providing ease-of-use.
SGPdata also offers tools for visualizing, analyzing and downloading student-level data, such as viewing SGPs and growth percentiles as well as performing trend analyses. With an intuitive user interface that’s suitable for beginners as well as experts alike.
An invaluable aspect of sgpdata is the capability of formatting data either WIDE or LONG formats. Lower level SGP functions, like studentGrowthPercentiles and studentGrowthProjections, use WIDE data while higher level wrapper functions such as sgpCalc and sgpMeanMeasurement utilize LONG data formats instead. In general, operational analyses that run repeatedly would benefit more from formatting LONG data formats as this provides both preparation and storage benefits over WIDE formats.
The ID column in sgpData table serves as a unique student identifier. Subsequent columns GRADE_2013, GRADE_2014, GRADE_2015, GRADE_2016 and GRADE_2017 show grade level assessment scores in each year from 2013-2018 for a student that did not take 5 tests in total (value is missing/NA).
SGP team’s main aim is to compile or generate multiproxy sedimentary geochemical data for every Paleozoic Epoch and approximately every 25 Ma Neoproterozoic time slice in all global regions. These data will be put to various applications, such as SGP analysis and modeling, carbon cycling studies and trace metal isotope research. To make this effort a success, SGP members from around the globe collaborated closely on this task. This effort has been made possible in part through funding provided by the National Science Foundation and other grants, as well as individual SGP participants who have contributed their own money towards covering costs. Additional sources of funding are being explored for this important initiative; if you are interested in joining us in contributing towards its success please reach out to the SGP team today.