Data SGP is an aggregate of student growth and achievement data, including demographics, prior achievement levels and performance in any one content area of each year of schooling. Furthermore, this data enables teachers, administrators and policymakers to improve instruction within schools or districts by accessing these insights into student development.
The sgpData set offers users access to a comprehensive compilation of student and teacher aggregates that enable them to draw conclusions regarding teachers’ effectiveness in improving students’ learning. In addition, this dataset offers indicators about individual students, such as current grade level or test score information that may help determine whether or not they are on track for graduation from high school.
sgptData is one of the most comprehensive data sets available and allows you to generate both student growth and achievement plots as well as student level aggregates (along with teacher and school aggregates). When using this dataset, only four required variables (VALID_CASE, CONTENT_AREA, YEAR, ID number, SCALE_SCORE GRADE number and ACHIEVEMENT_LEVEL are required if creating student aggregates through summarizeSGP function); demographic/student categorization variables may also be included but these variables are optional.
The dataset sgpData_INSTRUCTOR_NUMBER is an anonymous student-instructor lookup table, providing the instructor for every assessment record a student completed within a certain content area in a certain year. This allows us to track how many students each teacher taught within that year as well as evaluate relationships between true SGPs and student background factors like prior achievement or family income.
Cohort-referenced SGPs require at least three years of stable assessments; Colorado currently uses two years to establish a baseline from which growth estimates can be made. If multiple prior year scale scores are necessary, however, only the two most recent scores can be considered by the model.
As there may be various causes for an increase in SGPs for any cohort, it is crucial to assess empirically how much inferences about student or school-level growth might differ if baseline-referenced SGPs were instead of cohort-referenced ones. Although the analyses in this report were planned and carried out prior to COVID-19 disruptions, their purpose remains relevant under standard test administration and reporting conditions; we discuss any implications resulting from any differences seen later.