USBE outlines discipline-data outliers, disparities and new law-enforcement fields

At the spring data conference, Wynn Schuder of the Utah State Board of Education described how incident and discipline data are being used statewide and flagged persistent quality issues that can distort metrics. "Serious consequences for students," Wynn said, arguing that accurate incident reporting is needed to identify disparities and target supports.

Wynn showed state review findings from school year 2023: 96% of LEAs reported incident data, 88% exceeded the minimum threshold of one incident per 50 students, but 37 LEAs failed to meet that threshold and 12 reported zero incidents. The presentation flagged large outliers where single incidents listed dozens of students or where individual students had implausibly large cumulative suspension-day totals (for example, more than 100 days), which the presenter characterized as likely data errors.

Wynn urged LEAs to review the primary infraction type field because 'other' was the most-common entry in 2023 and often included events that should have matched existing infraction categories (disruption, truancy, fighting, bullying). He also presented multiple metrics demonstrating disparities: students experiencing intergenerational poverty, low-income students, English learners, students experiencing homelessness and students with disabilities had higher incident and lost-instruction-day rates than not-low-income peers.

The session also noted new law-enforcement fields collected this year (search and seizure, criminal and noncriminal citations, physical arrests) and that USBE is discussing how and when to share more data publicly, while balancing small-n privacy considerations at the LEA level. Wynn offered training materials and urged special education directors and data leads to use the discipline incident summary for SPED report to verify removal counts and whether services were provided during removals.

USBE said it will continue to run preliminary annual data reviews and follow up with LEAs that appear to have incomplete or inconsistent reporting.