Graded Partial Credit Model

PsyScore: Psychometrically-aware framework integrating IRT scoring with ZPD-scaffolded LLM feedback for essay assessment

PsyScore is a new framework for Automated Essay Scoring (AES) that unifies diagnostic assessment and instructional feedback through a shared latent ability representation. It combines a neural Item Response Theory scorer (based on the Graded Partial Credit Model) with a multi-agent LLM feedback generator conditioned on estimated student proficiency, operationalizing Vygotsky's Zone of Proximal Development. Experiments on the ASAP++ dataset show competitive scoring performance alongside more pedagogically aligned feedback. The work addresses a gap between psychometric rigor and LLM-based adaptive instruction.