Data SGP is a tool designed to collect and manage student growth data efficiently and manage it for analysis, such as percentiles and projections. Widely utilized throughout Massachusetts school districts, Data SGP benefits include increased efficiency when evaluating and assessing students and increased accountability between schools, districts, and individuals in terms of accountability measures and accountability requirements for individual schools and districts. Unlike most student achievement systems, this system permits comparisons of academic performance between groups as well as between schools districts students in any given year.
SGP data analysis systems are specifically tailored to handle large volumes of information while remaining manageable compared to traditional big data applications, such as global Facebook interactions or massive datasets that require traditional management solutions (Big data). SGP analyses typically produce millions of results relative to other big data applications like Hadoop (e.g., global Facebook interactions).
SGP systems can be complex to navigate. Data preparation, in particular, is crucial to the success of any analysis conducted through SGP software and any errors encountered often stem from poor preparation practices. Therefore, it is recommended that practitioners follow best practices when it comes to data preparation for SGP analysis.
SGP analyses involve comparing student growth percentiles with academic peers. To do so, data such as student IDs, grades and MCAS assessment scores for each student are needed for analysis. To facilitate this comparison process, the SGP package provides two data sets which can be used: window specific SGP for reporting student growth within a set time window; and current SGP which gives each student their most recent relative performance value available at that moment in time.
SGPs offer an invaluable new method for measuring student development; however, their implementation can be complex and time consuming. Furthermore, because raw data cannot be converted directly to SGPs by the system automatically, there may be several steps involved before being ready for analysis. Additionally, it can be challenging to accurately distinguish whether any changes in SGP data reflect an actual shift in student performance or just random fluctuations; it is thus wise to be cognizant of this potential source of error when using SGP data for comparisons between students. SGPs provide a powerful analysis tool for student performance at the state level; however, average SGPs can be quite unpredictable. For instance, during the Covid-19 pandemic the trend changed from increasing absolute performance to declining absolute performance for SGPs at state-wide level – but this change did not represent actual changes in district or school-level student performance.