Wisconsin Dropout Early Warning System found to be mostly wrong

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. Wi sconsin'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. System 🤖 DEWS Documents 📃 Wisconsin Department of Public Instruction website Wisconsin Department of Public Instruction . Drop-ou t Early Warning System Wisconsin Department of Public Instruction (2021). DEWS Equity Analysis 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

Organisation involved

Wisconsin Department of Public Instruction

Product, system or model

Dropout Early Warning System (DEWS)

This is a record of what was reported, not a finding that anyone broke the law. If it names your organisation and you believe it is wrong, the corrections process is free and open to everyone.