Explore how Stanford Assistant Professor Irene Lo and her team collaborated with the San Francisco Unified School District to design a new student assignment policy. Delve into the process of creating a zone-based system that aims to balance diversity, predictability, and proximity for the 2024-25 school year. Learn about choice modeling techniques used to predict student preferences, and discover the policy decision support tool developed for simulating and evaluating assignment outcomes. Examine the challenges and considerations involved in implementing geographic zones and reserves, as well as the use of equity priorities for target populations. Gain insights into the policy approval process and the ongoing efforts to ensure equitable zones and address potential negative effects of reduced choice.
Designing School Choice for Diversity in the San Francisco Unified School District
Stanford University via YouTube
Overview
Syllabus
HAI Weekly Seminar
Evaluating Policies: Choice Modeling Choice Modeling: Predict how students would choose if we changed the policy • Use historical choice data from 2014-2019 • Predict student choice: Will a student like, list, or enroll in a school!
Policy Decision Support Tool End-to-end simulation tool to test policies and evaluate resulting assignments
Evaluating Policies: Which Policy? Zones Zones + Reserves
Policy Recommendation and Next Steps Proposed Policy: Restrict choice using geographic zones and reserves, improve outcomes for target populations (homeless, foster care) using equity priorities SFUSD Board of Education approved policy in Dec 2020 for implementation starting the 2024-25 school year Challenges and considerations negative effects of reducing choice, zones, reserves system changes to ensure equitable zones
Summary Supported the development of a new student assignment policy in the San Francisco Unified School District with optimization and Al
Taught by
Stanford HAI
