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AI-Assisted Educator Performance Scoring from Student Growth

Accountable
New York City Public Schools
Functional Modes
Deciding (Analytical AI)
Human executes
Purpose
Eligibility & Public Benefits
Input Dataset
Sensitive personal information Identifiable data
Algorithm or Model
Optimization
Output Dataset
A decision about you Identifiable data

This system uses student assessment scores and demographic data to estimate how much each student was expected to learn, then compares those predictions to actual scores to generate a growth rating for teachers and principals. That rating — the Measures of Student Learning (MOSL) — is combined with an observation-based rating to produce an annual Overall Rating for each educator. Under New York State law, this Overall Rating is a significant factor in decisions about employment, tenure, and salary.

Sources for this disclosure

  • AI register
    NYC Algorithmic Tools Compliance Report (2025) — MySchools – Match

    Year: 2025. Agency: NYC Public Schools. Department: Division of Instructional and Information Technology. Date first use: 2018/08. Source CSV provided by user.

Schema: ai@2026-05-06-beta