arXiv — NLP / Computation & Language · · 3 min read

Effects of Varying LLM Access on Essay Writing Behavior

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Computer Science > Computation and Language

arXiv:2606.00250 (cs)
[Submitted on 29 May 2026]

Title:Effects of Varying LLM Access on Essay Writing Behavior

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Abstract:Investigating the degree to which large language models (LLMs) affect teaching and learning in universities can help identify strategies for integrating LLMs in a way that supports, rather than undermines, student learning outcomes. This study examined how varying levels of LLM assistance affect writing performance, engagement, and perceived authorship. We report a pilot study in which 24 college students were randomly assigned to write a short essay with no LLM access, limited access (<=3 prompts, responses capped at 100 words), or unlimited access. Overall essay quality was statistically indistinguishable across groups. Yet writing behavior and perceived authorship diverged sharply: students with limited access reported higher ownership (62.5% would submit the essay as independent work, vs. 25% in the unlimited group), stronger organizational gains, and more strategic, revision-focused prompting. The unlimited group spent more time writing, produced essays more similar to LLM output, and reported reduced creative expression. Our findings suggest that constraining, rather than banning, LLM access may preserve authorship confidence while retaining the scaffolding benefits of AI assistance.
Comments: BEA (Building Educational Applications) Workshop 2026
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC)
Cite as: arXiv:2606.00250 [cs.CL]
  (or arXiv:2606.00250v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2606.00250
arXiv-issued DOI via DataCite

Submission history

From: Julia Christenson [view email]
[v1] Fri, 29 May 2026 18:30:30 UTC (968 KB)
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