Data sgp is a tool that allows educators to track student performance over time. It can be used to evaluate teacher effectiveness, compare students across grades, schools and states, and help identify underperforming or high achieving students. It can also be used to track student growth and predict future achievement. These tools are widely used in schools around the world.
The data sgp package includes functions to perform basic and advanced student growth percentiles and projection analyses. It also provides a lookup table (sgpData_INSTRUCTOR_NUMBER) that contains instructor details associated with each test record. These lookup tables make it easier to conduct the analyses and reduce the complexity of source code associated with operational analyses. The SGP package also offers higher level functions that combine lower level functions into one function call, further simplifying the source code for these analyses.
There are two common formats for longitudinal (time dependent) student assessment data: WIDE and LONG format. The sgpData exemplars include a WIDE format, with each row representing a unique student and the columns containing variable data for the same student over multiple years of testing. The first column of the sgpData exemplars, ID, provides a unique student identifier. The next 5 columns, GRADE_2013, GRADE_2014, GRADE_2015, GRADE_2016 and GRADE_2017, provide the student assessment scores for each of the 5 years.
When using the sgpData exemplars, it is important to understand that the values in these columns represent percentages of the students in each grade level who scored above or below that score. Thus, when calculating growth trajectories, it is important to take into account the number of students who scored above or below the score. This will affect the accuracy of the final growth trajectories.
For example, a student who scored above the 50th percentile in Grade 5 may be expected to achieve the 75th percentile in Grade 9. However, because there are only 25 students scoring above that mark, a 50th percentile prediction will only predict that half of these students will reach the 75th percentile in Grade 9, and half will not.
This is why it is so important to have a good understanding of the limitations and constraints of student growth percentiles. Educators who are unfamiliar with these limitations and restrictions should consult the SGP documentation, vignettes and examples before conducting any student growth projection analyses. This will help prevent unnecessary errors and ensure that analyses are performed correctly. If any questions or issues arise while analyzing student growth data, please contact the SGP support team for assistance. Thanks!