Implementation Considerations for Automated AI Grading of Student Work

Zewei Tian; Alex Liu; Lief Esbenshade; Shawon Sarkar; Zachary Zhang; Kevin He; Min Sun

Implementation Considerations for Automated AI Grading of Student Work

Human-Computer Interaction 2025-11-06 v2

Authors: Zewei Tian , Alex Liu , Lief Esbenshade , Shawon Sarkar , Zachary Zhang , Kevin He , Min Sun

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.

Keywords

intelligent tutoring systems education technology artificial intelligence

Cite

@article{arxiv.2506.07955,
  title  = {Implementation Considerations for Automated AI Grading of Student Work},
  author = {Zewei Tian and Alex Liu and Lief Esbenshade and Shawon Sarkar and Zachary Zhang and Kevin He and Min Sun},
  journal= {arXiv preprint arXiv:2506.07955},
  year   = {2025}
}

Implementation Considerations for Automated AI Grading of Student Work

Abstract

Keywords

Cite

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