AI-Supported Analysis of Student Work Saves Teachers Time Without Replacing Their Judgment

Whitepaper/Report

EdLight report on a pilot examining how AI-supported analysis of handwritten student work functioned in middle school math classrooms, with a focus on instructional decision-making, time use, and alignment with teachers’ professional judgment.

Visit Resource
This link will take you to an external website.
Purpose/Abstract

This pilot examined how EdLight’s AI‐supported analysis of handwritten student work functioned within everyday classroom contexts, with a focus on instructional decision‐making, time use, and alignment with teachers’ professional judgment. Middle school math teachers used EdLight to analyze exit tickets and student work artifacts as part of their regular instructional routines.

Data sources included weekly teacher logs, post‐pilot surveys, and teacher empathy interviews. Findings indicate that EdLight enhanced teachers’ instructional sensemaking and efficiency when insights aligned with curriculum pacing and classroom realities. Teachers consistently valued the tool’s ability to surface patterns across student work, supporting quicker grouping decisions and more focused planning.

Pre/post survey data indicated a shift from approximately 45 minutes per class to 15-30 minutes for most teachers, reflecting reclaimed instructional planning time and faster access to actionable insights. The pilot also surfaced important design insights about when AI‐generated feedback is most actionable in practice.

Citation
ImpactSTATS Inc. & EdLight. (2026). Fitting Into the Flow: AI-Supported Student Work Analysis in Illustrative Mathematics Classrooms.

Areas researched: AI, Professional Learning

Previous
Previous

SafeInsights Teacher Report: An Innovative Way to Help All Students Succeed

Next
Next

Informing Change: A Final Research Report on the Findings from the Longitudinal R&D Partnership for Math Equity Project