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Postsecondary District Comparison
Postsecondary District Comparison Tool
Step 1: Select a District
Step 2: Selection Criteria
Comparable Districts Based on Selected Criteria
Additional Information
The comparison will find districts that are ranked within plus or minus 15 of your district’s ranking for enrollment and/or risk factors.
Compare Based on Enrollment: Check this box, and those districts closest to the selected district in 2023 audited enrollment will be listed. The audited enrollment counts exclude pre- kindergarten and not graded students.
Compare Based on Risk Factors: Check this box, and the districts that are most similar to the selected district in their predicted levels of risk will be listed. Predicted risk is based on a combination of four factors—cumulative poverty, cumulative student mobility, cumulative chronic absenteeism, and cumulative Identification of Disability. These four factors significantly influence effectiveness rates.
In most cases, the selected districts will have similar levels of risk on all four risk factors, but especially on the dominant factor, the level of cumulative poverty. For more about the risk factors, see the Risk Factors tab.
Both boxes checked: The software will report those districts that appear in both lists. Sometimes there are few or no districts that are similar in both enrollment and predicted risk.
Limitations: If a district is unusually high in a particular factor, for example, in chronic absenteeism, it might not be similar to the other districts in its other risks, even though it has a similar level of predicted risk.
For districts at the very highest or very lowest levels of predicted risk, there may be very few or no districts above or below them in predicted risk levels, so few or no similar districts will be reported.
Why did KSDE account for risk factors?
KSDE researchers used a set of risk factors and linear regression to predict the average postsecondary effectiveness rates for school districts. By including the risk factors as independent variables in the prediction, the variance of the predicted effectiveness rates is accounted for in the calculation. Once we have accounted for risk factors in the predicted rates, we can compare districts' actual effectiveness rates to their predicted ones. It is a way to compare all districts on their effectiveness rates after factors known to depress effectiveness rates, over which districts have limited influence, have been accounted for.
What were the risk factors included in the regression?
KSDE researchers used linear regression to identify factors that depress districts' postsecondary effectiveness rates. Based on this year’s data the significant detractors were (1) cumulative poverty, (2) cumulative student mobility, (3) cumulative chronic absenteeism, and (4) cumulative identification of disability. These four factors explained 54.3 percent of the variance of accredited districts' effectiveness rates. Students' cumulative poverty was by far the strongest detractor of effectiveness rates.
Cumulative poverty: The proportion of the students' school years spent in poverty. A school year in which the student spent any period of time eligible for free lunch was valued at one. If the student was not eligible for free lunch during the school year, but was for reduced-price lunch, the school year was valued at 0.5. For the selected five cohorts, these values were combined into the numerator. The denominator was the count of the total number of school years the selected five cohorts have attended Kansas schools.
Cumulative student mobility: The proportion of school changes during the school year. After selecting for the grades and years the five cohorts attended Kansas schools, the numerator is the number of times these students changed schools during a school year. The denominator was the count of the total number of school years the selected five cohorts have attended Kansas schools.
Cumulative chronic absenteeism: After selecting the five cohorts, the numerator was the count of student years in which students missed at least 10 percent or more of their days of membership in a school year. The denominator was the count of the total number of school years.
Cumulative identification of disability: The proportion of the students’ school years reported to have a primary area of disability. A school year in which the student was reported to have an active Individual Education Plan (IEP) which documents that the student received special education was valued at one. For the selected five cohorts these values were combined into the numerator. The denominator was the count of the total number of school years the selected five cohorts have attended Kansas schools