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Review of feedback in Automated Essay Scoring
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The first automated essay scoring system was developed 50 years ago. Automated essay scoring systems are developing into systems with richer functions than the previous simple scoring systems. Its purpose is not only to score essays but also as a learning tool to improve the writing skill of users. Feedback is the most important aspect of making an automated essay scoring system useful in real life. The importance of feedback was already emphasized in the first AES system. This paper reviews research on feedback including different feedback types and essay traits on automated essay scoring. We also reviewed the latest case studies of the automated essay scoring system that provides feedback.
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Cited by 2 Pith papers
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PsyScore: A Psychometrically-Aware Framework for Trait-Adaptive Essay Scoring and ZPD-Scaffolded Feedback
PsyScore combines a Trait-Adaptive Neural IRT Scorer using GPCM with a ZPD-Scaffolded Feedback Generator to deliver both competitive scoring and pedagogically aligned feedback on the ASAP++ dataset.
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Comparative Validation of GPT-4o-mini and Teacher Mean Scores for Automated Scoring of Music Analysis Responses: Single-Pass Deployment, Repeatability, and Strategy-Specific Bias
GPT-4o-mini's scoring of music analysis essays agrees only moderately with teacher mean scores, with strategy-specific bias: Fs+CoT under-scores, RAG over-scores, and self-consistency is repeatable but weakly accurate...
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