How AI Improves Dropout Early Warning
To help alert their overworked staff to students in need of attention, a state education agency funded development of an advanced Dropout Early Warning system. In this case study, we discuss our experience integrating machine learning with counseling, social work, and other student services workflows, focusing on predictive quality, personalization, actionability, and scaling up.
- Daniel Jarratt, Data scientist, Infinite Campus
- Judi Vanderhaar, Program Consultant, Division of Student Success, Kentucky Department of Education
- Thomas Christie, Data scientist, Infinite Campus
Daniel Jarratt, Data scientist, Infinite Campus
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