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iSchedule to Personalize Learning (Analytics Operations Engineering, Inc. on behalf of New York City Department of Education)

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Description

We present a tool to assist schools in the NYC Innovation Zone with generating student-centered course schedules. The core algorithm breaks the scheduling problem into a series of sub problems and applies graph-based randomized heuristics, then outputs a diverse set of schedules among which the school principal can ultimately choose. Our tool reduces the annual work load for each school from 8 weeks to 2 weeks, while affording administrators more choice and flexibility.

Contributors

  • Adeline Kuo

    Analytics Operations Engineering, Inc., Boston MA, United States of America
    Email Adeline Kuo

  • Anjuli Kannan

    Analytics Operations Engineering, Inc., Boston MA, United States of America

  • Gerald van den Berg

    Princeton University, Princeton NJ, United States of America

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