The Atmospheric Radiation Measurement Program (ARM) collects instrument and model data at its Southern Great Plains sampling site for analysis by over 30 scientists who work from this central facility and remote instruments throughout this part of the US. Researchers analyze this information in order to improve cloud modeling, radiative processes, large-eddy simulation (LES) models used in atmospheric general circulation research as well as overall atmospheric health research.

SGP analyses are performed in R software environment which is available for Windows, OSX and Linux platforms and open source. To use it effectively requires a machine with sufficient memory and processing power and ample processing memory; before diving in to running SGP analyses it would be wise to spend some time familiarizing yourself with R as these analyses tend to be relatively straightforward with most issues related to data being the culprit for issues.

Student growth percentiles measure relative growth over time based on initial test score comparisons. Similar to standard percentiles, these percentiles range from 1-99 with higher numbers signifying greater relative progress. Students with high raw scores often exhibit fluctuating performance as time goes on; two students who start from different places could end up having the same SGP value.

Students with strong academic peer groups on previous MCAS test administrations typically will share similar Student Group Percentile (SGP) ratios with others with similar academic peer groups – even among students who earned very high raw scores, as the SGP model compares students who have shared comparable MCAS scaled score histories to determine relative performance.

SGPs are calculated utilizing assessment data from 2005-2006. Student Growth Percentiles are only available to students in grades 3-8 with valid and consecutive test scores; similarly, teachers of English language arts or mathematics grades who have sufficient baseline data and comparable test scores can create their own SGP.

Window Specific SGP, intended to show user a snapshot of student growth across multiple testing windows, and Current SGP are two types of growth projections created by Damian Betebenner and used for “check ins.” Both use his catch-up, keep-up growth projection approach which allows more appropriate interpretation of growth by accounting for differences in experiences across students.