{
  "annotation_id": "2c86c02a-6fb2-4e75-890f-4c17e7ae9d31",
  "date_created": "2026-02-17T05:53:08.702000Z",
  "date_modified": "2026-02-17T05:53:08.702000Z",
  "file_hash": "298e7709770940dfde1f91abd087b86ac9d64b81359e5ab14ec2ffb47195398c",
  "private": false,
  "record": {
    "abstract": "We present Expos\\\u0027ia, the first public dataset that connects writing and feedback assessment in higher education, enabling research on educationally grounded approaches to academic writing evaluation. Expos\\\u0027ia includes student research project proposals and peer and instructor feedback consisting of comments and free-text reviews. The dataset was collected in the \"Introduction to Scientific Work\" course of the Computer Science undergraduate program that focuses on teaching academic writing skills and providing peer feedback on academic writing. Expos\\\u0027ia reflects the multi-stage nature of the academic writing process that includes drafting, providing and receiving feedback, and revising the writing based on the feedback received. Both the project proposals and peer feedback are accompanied by human assessment scores based on a fine-grained, pedagogically-grounded schema for writing and feedback assessment that we develop.\n  We use Expos\\\u0027ia to benchmark state-of-the-art open-source large language models (LLMs) for two tasks: automated scoring of (1) the proposals and (2) the student reviews. The strongest LLMs attain high agreement on scoring aspects that require little domain knowledge but degrade on dimensions evaluating content, in line with human agreement values. We find that LLMs align better with the human instructors giving high scores. Finally, we establish that a prompting strategy that scores multiple aspects of the writing together is the most effective, an important finding for classroom deployment.",
    "arxiv_id": "2601.06536",
    "authors": [
      "Dennis Zyska",
      "Alla Rozovskaya",
      "Ilia Kuznetsov",
      "Iryna Gurevych"
    ],
    "categories": [
      "cs.CL"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "title": "Expos\\\u0027ia: Academic Writing Assessment of Expos\\\u0027es and Peer Feedback",
    "url": "https://arxiv.org/abs/2601.06536",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "35a0fb1c-2a77-43e6-9f72-5c4dbf0dfdac",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}