Implementation Considerations for Automated AI Grading of Student Work

This paper presents a co-design pilot study with 19 K-12 teachers examining the classroom implementation of an AI-powered grading platform (Colleague AI) that generates rubrics and provides automated feedback on student work. Through usage logs, surveys, and interviews, the study evaluates teacher and student perspectives on AI-generated scoring versus narrative feedback, revealing trust issues with automated grading but appreciation for rapid formative feedback.

This study explores the classroom implementation of an AI-powered grading platform in K-12 settings through a co-design pilot with 19 teachers. We combine platform usage logs, surveys, and qualitative interviews to examine how teachers use AI-generated rubrics and grading feedback. Findings reveal that while teachers valued the AI's rapid narrative feedback for formative purposes, they distrusted automated scoring and emphasized the need for human oversight. Students welcomed fast, revision-orie

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