Data for Southern Great Plains
The Southern Great Plains Observatory is part of the US Department of Energy Atmospheric Radiation Measurement Program (ARM). Spanning 350km by 350km, this testbed serves to improve cloud and radiation models used by global climate models. At its heart lies an instrumented central facility southeast of Lamont in Oklahoma with 30 scientists and technicians monitoring instruments, along with observations sent directly from satellites and ground stations throughout its site that are transmitted through to an ARM Data Center where these observations can be utilized by global scientists worldwide.
Traditional student assessment reports demonstrate a student’s achievements; growth reports provide information about how much the individual student has improved academically from year-to-year, measured against comparisons of students against their academic peer group at their previous assessments.
Normative growth is a method for calculating student growth percentiles that compare students against their academic peers at both the state and national levels. Each state’s Student Growth Percentile report serves as an SGP report and contains ratings for individual students, school, district and growth estimates and trends for groups (i.e. racial/ethnic groups or schools).
When using the Student Growth Plan report to compare students from year to year, it’s important to remember that SGPs are calculated every year anew; any differences in percentile rankings should be treated with caution; an anomaly of less than 10 points likely won’t have any serious ramifications.
Student Growth Performance, or SGP, is calculated based on how a student’s performance in 8th grade on state assessments compares with that of all 8th graders across their state. Their academic peer group is established using the same method used to calculate SGP; its determination can be found within their individual assessment record.
For optimal analysis, the SGP package recommends formatting data in LONG format (sgpData_LONG). StudentGrowthPercentiles and studentGrowthProjections both utilize this format, as do higher level wrapper functions abcSGP and updateSGP. When running consistent analyses year after year, formatting the LONG format can simplify preparation and storage of your data.
This data set illustrates the necessary variables needed for SGP analyses: VALID_CASE, CONTENT_AREA, YEAR, ID, SCALE_SCORE, GRADE and ACHIEVEMENT_LEVEL. When creating individual student aggregates using summarizeSGP function an additional variable is also needed – sgpData_INSTRUCTOR_NUMBER is recommended here to show how preparation and storage procedures necessary to conducting operational SGP analyses can be followed efficiently; hence sgpData_LONG should always be prepared prior to conducting operational analyses of SGP in any operational SGP study for best practice!