Generative AI in K-12 Classrooms: A Midyear Implementation Report
Lief Esbenshade, Alex Liu, Michael Xiao, Zewei Tian, Min Sun, Zachary Zhang, Thomas Han, Yulia Lapicus, Kevin He

TL;DR
This report examines early teacher engagement with Colleague AI in diverse Washington State school districts during the first half of the 2025-26 school year, highlighting usage patterns and preliminary insights.
Contribution
It provides initial data on AI adoption in K-12 classrooms across varied districts, offering a midyear implementation perspective.
Findings
Varied district sizes and locations show different AI usage patterns.
Preliminary signals suggest links between AI use and student characteristics.
Data collection was limited to districts providing administrative records.
Abstract
This mid-year report summarizes teacher use of Colleague AI across 12 Washington State school districts from September 1 to December 31, 2025. Produced jointly by Colleague AI and AmplifyLearn.AI at the University of Washington, this report aggregates platform data and district-provided administrative records to provide an early look at how teachers engaged with AI during the first half of the 2025-26 school year. The districts vary in size from small districts with a few thousand students to large districts with up to thirty thousand students. The districts are rural, suburban, and urban. Only a subset of districts were able to provide mid-year administrative data, and findings that link teachers' use of Colleague AI to student characteristics should be interpreted as preliminary signals.
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