How to Interpret Statistical Growth Plots
Statistical Growth Plots, or SGPs, leverage longitudinal student assessment data to produce a measure of students’ relative progress compared to their academic peers. This data can be used to inform educator evaluation systems and can help schools communicate to educators and parents how their students are growing – or not – toward a specific achievement standard (e.g. 75% of academic peers).
While SGPs can be calculated from students’ standardized test score histories, they typically require multiple years of stable assessments to produce accurate results and require significant computational effort. In addition, correlations between the baseline SGP and prior year scale scores will likely be less than zero, potentially introducing large estimation errors into SGP estimates.
SGPs are unique in that they provide educators and parents with a single number that conveys to them how much students have grown or not grown in relation to their academic peers. A SGP score is reported on a 1 to 99 scale, with higher numbers indicating more relative growth. This simple metric is useful for communicating to teachers and parents that their students are either growing faster or slower than expected, and that this can be due to a variety of reasons.
In addition to the SGP summary report, educators can access a more detailed SGP spreadsheet by selecting a student in the report and choosing the “SGP Data” tab. This tab provides a table of SGP data for the selected student across five years of testing. The first column, ID, identifies the student’s unique identifier and the following five columns, SS_2013, SS_2014, SS_2015, SS_2016 and SS_2017, display the individual assessment scores for each of these years.
A common mistake made in interpreting SGP data is to simply look at the percentiles and assume that higher percentages mean more relative growth. In reality, however, a high percentile may actually indicate that a student has shown less progress than most of their peers or no more progress than other students with similar prior testing history.
Educators can use SGPs to identify areas where students need additional support, especially for academically struggling students. The granularity of the SGP data enables educators to make targeted and focused decisions about which supports will be most effective for each student. In this way, SGP data can help educators drive student growth in ways that can be difficult to accomplish with traditional, high-stakes assessments alone. This type of student-centered decision making is an important aspect of a student-centered education system. For example, teachers can use SGP information to make decisions about which interventions to implement for a student with low reading or math scores and then track the impact of these interventions over time. This kind of individualized instruction is key to helping students grow and learn.