Data SGP is a database of student growth percentiles and projections generated by Wyoming’s Star Assessment system. It allows educators, parents and students to track their student’s progress over time relative to other students across the state. The database is created by analyzing the growth trajectories of students who took the same Star assessments in different years and comparing them to determine which students are growing faster than others. This process is called normative growth modeling.

For example, consider a sixth grade student named Simon who scored a 390 on this year’s statewide assessment in English language arts (ELA). The student’s scale score growth is 370 points. This is a significant improvement, but it is not clear whether this is greater than the growth of a fifth grade student named Rachel who scored a 390 on the ELA test. Without using SGP, this comparison would not be valid because the two students likely have different academic peer groups and starting scores. With SGP, this is not a problem because the SGP compares the student’s current score to their academic peers.

The SGP data is grouped into deciles, each of which has 10 percentiles or 100 students. The smallest decile has the most students, with each decile increasing in size as the percentiles move up. This grouping ensures that every student is represented at least once in the data set, ensuring that the results are accurate and meaningful.

Although the deciles are grouped based on grade level, the data can be viewed by class or by teacher. This feature is especially useful for teachers who want to see how their students are performing relative to their peers, or to see if their students’ performance has been consistent over the past several years. This is similar to the way that lottery analysis tools identify hot and cold numbers based on previous results, reducing the guesswork that goes into selecting lottery numbers.

A key point to keep in mind when interpreting SGP is that the percentile ranking is calculated anew each year. This means that differences in SGPs between years should be interpreted with caution. A difference of fewer than 10 points in SGP is unlikely to be meaningful.

In addition to the decile data, sgptData_LONG contains the same information but in long format for 8 windows (3 windows annually). This is useful for running longitudinal analyses that include both achievement and growth.

The first column in the sgptData_LONG file is ID, which provides the unique identifier for each student. The next 5 columns, SS_2013, SS_2014, SS_2015, and SS_2016, provide the student’s statewide assessment scores from each of those years. Finally, the last column, SS_2017, provides the student’s most recent statewide assessment score. The sgptData_LONG spreadsheet also includes demographic variables that are used for student categorization when running longitudinal analyses. This is not required if only student growth and achievement plots are being run. To download the sgptData_LONG dataset, please visit our data portal.