How PowerSchool Uses Data to Predict Student Dropout Risk

PowerSchool, the K-12 software giant, processes data from over 50 million students worldwide. In this episode, Lucas and Luna drill into how the company's predictive analytics tool flags at-risk students months before they drop out. They walk through the specific data points used, the machine learning model's false positive rate, and how a school district in Texas cut its dropout rate by 18 percent in one year. The hosts also discuss the ethical tensions around algorithmic intervention in students' lives and whether this kind of surveillance becomes a net positive or a new form of tracking. A focused look at one of edtech's most quietly powerful tools. #PowerSchool #PredictiveAnalytics #K12 #StudentDropout #MachineLearning #Edtech #DataDriven #EarlyIntervention #TexasSchoolDistrict #AlgorithmicFairness #StudentPrivacy #Intervention #GraduationRate #EducationData #Business #Technology #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo