SOURCE-LINKED INTELLIGENCE
SWIM: Student Writing Simulation via Proficiency-Conditioned Generation
Writing proficiency manifests in how students develop content, organize ideas, choose words, and use language. Despite growing interest in LLM-based student simulation, whether LLMs can reproduce such multidimensional variation in extended writing remains largely unexplored. In this work, we explore if language models can realistically simulate student writing, and introduce SWIM, a task that formulates Student Writing sIMulation as proficiency-conditioned essay generation. We evaluate prompting, supervised fine-tuning (SFT), and reinforcement learning (RL) methods for writing simulation using
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T23:10:51.000Z
First collected: 2026-09-21T05:11:56.580Z. This is not the publication date.