Statistical Growth Plots (SGPs) use longitudinal student assessment data to generate relative estimates of each student’s growth relative to his or her academic peers. They offer educators a straightforward, fast, and meaningful method for measuring progress that allows them to gauge whether students are making good strides towards reaching their desired learning outcomes.
SGPs are determined by comparing current and prior test scores against an established growth standard – for instance, one that indicates at least 75% growth among academic peers. DESE uses both recent tests as well as any prior exams from earlier testing windows (these windows do not necessarily correspond with school years) in creating SGPs; calculations for MCAS exams also incorporate these calculations.
SGP scores are reported on a 1-99 scale with higher numbers indicating more growth than lower ones. Once measured, these growth scores are then divided into four tiers that show how much relative progress students should expect in reaching proficiency in subjects like math and literacy. Finally, Star Growth Reports provide educators with an easy way to quickly determine if their students are growing faster, slower or about as expected.
SGP analyses utilize R, which is available for Windows, Mac and Linux operating systems. Conducting such analyses requires some familiarity with R’s installation and configuration capabilities for your environment; extensive documentation and tutorials for using it online can be found.
Though ‘big data’ has become an increasingly familiar term in science, business, and everyday life, compared to large-scale scientific research projects that use massive datasets like tracking global Facebook interactions or mapping human genomes; SGP analysis actually requires relatively less information. When measured against other types of research (for instance tracking global Facebook interactions or mapping human genomes) SGPs represent what would otherwise be considered medium data sets.
Districts need access to a database containing student and instructor data in order to run SGP analyses effectively, and sgpData offers this database in formats compatible with such analyses, with many useful features to assist districts with managing SGP data such as an automatic lookup function linking students with instructors using unique identifiers associated with test records; it also features an instructor number field which can help distinguish among multiple instructors assigned for a subject area.
Future developments of SGP data include supporting additional aggregations and analyses functions, expanding subject areas and grade levels supported, as well as new methodologies for calculating growth for students in grades 9 through 12 using their Star test history. We appreciate your patience as we work on these important projects, making announcements as changes occur and answering any inquiries or comments regarding them. Please reach out!