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New framework integrates essay scoring with adaptive feedback

By PulseAugur Editorial · [2 sources] ·

Researchers have developed PsyScore, a novel framework designed to improve automated essay scoring (AES) by integrating assessment with instructional feedback. Unlike previous methods that treated these components separately, PsyScore uses a shared latent ability representation. It features a Trait-Adaptive Neural IRT Scorer for precise ability estimation and a ZPD-Scaffolded Feedback Generator that tailors feedback to student proficiency levels. Experiments on the ASAP++ dataset show PsyScore performs competitively in scoring and offers more pedagogically aligned feedback. AI

IMPACT This framework could enhance educational tools by providing more accurate and personalized feedback to students.

RANK_REASON The cluster contains a research paper detailing a new framework for automated essay scoring.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New framework integrates essay scoring with adaptive feedback

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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Wei Xia, Jin Wu, Haoran Shi, Xiangyu Wang, Chanjin Zheng ·

    PsyScore: A Psychometrically-Aware Framework for Trait-Adaptive Essay Scoring and ZPD-Scaffolded Feedback

    arXiv:2606.20287v1 Announce Type: new Abstract: Effective Automated Essay Scoring (AES) are expected to support both reliable assessment and actionable instructional feedback. However, existing approaches often treat scoring and feedback as separate components: neural scoring mod…

  2. arXiv cs.CL TIER_1 English(EN) · Chanjin Zheng ·

    PsyScore: A Psychometrically-Aware Framework for Trait-Adaptive Essay Scoring and ZPD-Scaffolded Feedback

    Effective Automated Essay Scoring (AES) are expected to support both reliable assessment and actionable instructional feedback. However, existing approaches often treat scoring and feedback as separate components: neural scoring models provide limited interpretability, while Larg…

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