arXiv AI
DraftTrace: A Multi-View Analytics Environment for AI-Integrated Writing
Read the original on arXiv AI →The Flow has not summarised this story yet — read it at arXiv AI.
Related stories
arXiv Computation and Language
Sep 3
Expos\'ia: Teaching and Assessment of Academic Writing Skills for Research Project Proposals and Peer Feedback
Exposía is the first public dataset linking academic writing and feedback in higher education, comprising student research project proposals, peer and instructor comments, and free-text reviews collected from a Computer Science course. It includes human assessment scores based on a fine‑grained, pedagogically‑grounded schema for both writing and feedback. The dataset is used to benchmark large language models on automated scoring of proposals and student reviews, revealing that different LLMs excel at each task and that closed‑source models outperform open‑weight ones, while a multi‑aspect prompting strategy proves most effective for classroom deployment.
arXiv AI
Jul 2
SEFORA: Student Essays with Feedback Corpus and LLM Feedback Evaluation Framework
arXiv:2607. 00274v1 Announce Type: cross Abstract: Effective writing feedback is among the strongest drivers of student learning, yet producing it at scale is labor-intensive.
arXiv Machine Learning
Sep 14
Limits of LLM Text Detectors in Education
The paper "Limits of LLM Text Detectors in Education" argues that existing LLM‑generated text detectors assume a binary human/LLM distinction, which fails to capture realistic student‑AI collaboration. It introduces a contribution‑aware evaluation framework with eight student contribution levels and presents GEDE, a benchmark of over 900 human‑written and 12,500 generated essays across 886 tasks. Using GEDE, the authors evaluate four detection methods and find that most detectors perform poorly on intermediate contribution levels, especially LLM‑assisted revisions, raising concerns about false accusations.
arXiv AI
Jul 23
Prober.ai: Gated Inquiry-Based Feedback via LLM-Constrained Personas for Argumentative Writing Development
arXiv:2605. 05598v2 Announce Type: replace Abstract: The proliferation of large language models (LLMs) in educational settings has paradoxically undermined the cognitive processes they purport to support.
arXiv Machine Learning
Aug 27
Unfolding Scientific Papers into Multi-Turn Generation Trajectories for Continued Pre-Training
arXiv:2608. 25826v1 Announce Type: cross Abstract: A recent line of synthetic-data work reconstructs the thinking behind existing text rather than rewriting the text itself, but it operates on short web passages, recovers only local thoughts, and leaves the structure of whole documents untouched.
arXiv Machine Learning
Jul 20
Cost-efficient generative AI summarization for scalable automated essay scoring in educational assessment
arXiv:2607. 15829v1 Announce Type: cross Abstract: Automated essay scoring (AES) enables scalable assessment and timely feedback but remains challenged by transformer input-length limitations, which can cause information loss when processing long essays.