Demographic Metadata as Construct-Irrelevant Noise in DistilBERT-Based Automated Essay Scoring

arXiv:2606.21066v1 Announce Type: new Abstract: Automated Essay Scoring (AES) systems are increasingly used to support teachers in managing grading workloads and to provide a supplementary rater in large-scale assessments. While human grading is frequently influenced by students' demographic characteristics, the efficacy of different strategies for integrating demographic metadata with textual input used to train AES models remains underexplored. This study investigates the impact of a specific ...