Implementation Considerations for Automated AI Grading of Student Work

TL;DR

This paper examines the implementation of an AI grading platform in K-12 classrooms, highlighting teachers' and students' perceptions, trust issues, and the importance of human oversight for effective AI-assisted assessment.

Contribution

It provides insights into how teachers and students interact with AI grading tools and emphasizes the need for trustworthy, teacher-centered AI assessment designs.

Findings

Teachers valued rapid narrative feedback for formative assessment.

Teachers distrusted automated scoring and wanted human oversight.

Students appreciated quick feedback but remained skeptical of AI-only grading.

Abstract

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-oriented feedback but remained skeptical of AI-only grading. We discuss implications for the design of trustworthy, teacher-centered AI assessment tools that enhance feedback while preserving pedagogical agency.