Data SGP is an analysis tool for longitudinal student assessment data that generates statistical growth plots (SGPs) depicting students’ academic progress relative to their peers. SGPs are generated based on standardised test scores and covariate information using an established “growth standard”, which takes into account prior testing history more accurately than traditional percentile scores.
SGP provides schools with an alternative model of growth by enabling them to set achievement targets/goals and then monitor how student groups are progressing over time towards these targets/goals. This makes SGP an efficient means of conveying to stakeholders that proficiency must be reached within a specified timeframe, as well as showing its effectiveness for schools or districts. Furthermore, it serves as a powerful method of explaining how much student growth must occur before reaching an achievement target – essential when seeking attention from state and local leadership.
SGP provides schools with an accurate picture of how well they are preparing students for the future by showing how each achievement target must grow over time. This enables educators to identify those students at risk of not meeting their goals and assist in selecting instructional interventions and programs designed specifically to support these individuals. Furthermore, it may assist administrators with making decisions regarding accelerating programs so that most of the targeted goals are reached on schedule without being held back by small percentages who fail to achieve sufficient gains.
SGP stands out by its ability to set multi-year growth standards based on official state achievement targets/goals, making it particularly helpful for schools in states which mandate minimum timeframes to reach proficiency. SGP serves as an ideal means of communicating the complexity of these requirements as well as showing how programs may reach proficiency faster even with limited resources available.
SGP methodology brings many advantages, yet can pose some challenges as well. One major consideration is the time required to prepare and run analyses using SGP methodology; typically this work includes three steps: data preparation, analysis/interpretation/writing reports. OSPI staff stands ready to offer training and support throughout this process.
To undertake Student Growth Potential analyses, one needs longitudinal student assessment data and appropriate software or hardware. Preparation time may include creating files for each year – once these are ready however, running calculations is relatively straightforward. SGPdata includes both WIDE format data sets which mimic time dependent data used with functions like studentGrowthPercentiles and studentGrowthProjections as well as LONG format sets that facilitate converting it to SGPdata format – LONG formatting tends to provide easier use and preparation when performing analyses; LONG formatting your data will provide the greatest ease in use and preparation when used most frequently for analyses.
