Data sgp is an important tool for improving student learning. It can be used at the classroom, district, and school level to support educator evaluations, identify teacher growth goals, and inform student grouping and educator allocation. However, SGP analyses are complex and require a substantial amount of computing time to run. The SGP package provides wrapper functions abcSGP and updateSGP that simplify the code required to conduct these analyses.
SGP analyses are conducted using data sets that contain the following information: VALID_CASE, CONTENT_AREA, YEAR, ID, SCALE_SCORE, GRADE, and ACHIEVEMENT_LEVEL (required if running student growth projections). Additionally, for operational SGP analyses, the sgpData_LONG and sgptData_LONG data sets also require a STUDENT_INSTRUCTOR look up file sgpData_INSTRUCTOR_NUMBER. The sgpData_INSTRUCTOR_NUMBER file is anonymized and contains the insturctor number associated with each students assessment record.
The SGP data set sgpData is an anonymized panel data set consisting of 5 years of annual, vertically scaled assessment data in WIDE format. The data set is designed to model the format of the data set that would be required for SGP analyses with the lower level studentGrowthPercentiles and studentGrowthProjections functions. The data set includes a student identifier, the date associated with each students assessment occurrence, and numeric scores associated with each students assessment occurrence.
Located on 160 acres of cattle pasture and wheat fields southeast of Lamont, the SGP observatory site has a central facility and a network of observing stations. The central facility is equipped with continuous measurement instruments that monitor atmospheric conditions. The site also has guest instruments that are deployed in support of specific research activities and to supplement ongoing measurements.
The goal of the SGP is to produce high quality data that can be used by researchers to address a wide range of research questions. SGP is unique in that it collects a large volume of data, provides data spanning more than one decade and a wide range of climate variables, and is available to researchers at no cost. The data collected at SGP is incorporated into Earth system models that are widely used in scientific research and in the prediction of weather events.
The SGP project is funded by a National Science Foundation grant. The funding is intended to support a long term program of development for the SGP data infrastructure and to provide additional resources for conducting educational and scientific analysis with the data. The SGP team has a broad range of expertise in computational statistics, machine learning, and data visualization. In addition, the SGP team is collaborating with a number of universities and government agencies on projects to apply the SGP tools to real world problems. The SGP team will continue to be flexible and responsive as new opportunities for collaborative work emerge. This will include expanding the reach of SGP and its educational applications through outreach and training efforts. The SGP team is also interested in developing new approaches and methods to use the data and in enhancing its utility for research, educational reform, and policy analysis.