Wisconsin Dropout Early Warning System accused of being 'unreliable'

Occurred: April 2023

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A system used to predict the likelihood of students graduating at Wisconsin high schools was found to be wrong most of the time, raising questions about the reliability of the system.

Wisconsin's machine learning-based application Dropout Early Warning System (DEWS) was wrong 'almost three-quarters of the time' that it predicted a student would not graduate, and wrong more often about Black and Hispanic students not graduating than about white students, according to a 2023 Markup/ChalkBeat investigation.

The investigation also found that educators had not been properly trained to understand the dropout risk labels and intervene accordingly, and that students had not been informed about the existence of the system.

Meantime, University of California-Berkeley researchers concluded the system failed to achieve its primary goal of improving graduation outcomes for the students it labels as 'high risk'. They recommended Wisconsin scrap its use of individual factors such as a student’s race or even test scores in determining that student’s dropout risk.

Operator: Wisconsin Department of Public Instruction
Developer: Wisconsin Department of Public Instruction

Country: USA

Sector: Education

Purpose: Predict student drop-outs

Technology: Machine learning
Issue: Accuracy/reliability; Bias/discrimination - race, ethnicity

Transparency: Governance; Marketing

Page info
Type: Incident
Published: October 2023
Last updated: February 2024