arXiv: cs.AI preprintsInternational11 November 2026
Reliability of Claude Code as an Agentic AI Grading System for Handwritten University Exams
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arXiv:2611.13217v1 Announce Type: new Abstract: This study examines the reliability of Claude Code, an agentic deployment of the Claude Opus 4.6 large language model, as a grading system for handwritten university exams. Four research questions addressed agreement with expert human grading on total scores (RQ1), agreement across five question types from multiple choice to evaluative judgement (RQ2), consistency across two independent grading sessions one week apart (RQ3), and the accuracy of AI-generated feedback (RQ4). Claude Code graded the 20-mark mid-term papers of 60 consenting students i
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