From Crafting Text To Crafting Thought: Grounding AI Writing Support To Writing Center Pedagogy

Yijun Liu, University of Illinois Urbana-Champaign

John Gallagher, University of Illinois Urbana-Champaign

Sarah Sterman, University of Illinois Urbana-Champaign

Tal August, University of Illinois Urbana-Champaign

Date

02/2026

AI Overview

Why it matters

AI writing tools that generate or rewrite text risk replacing student voices, diminishing user agency, and undermining critical thinking skills. Grounding AI assistants in writing center pedagogy could instead support students' revision processes without writing for them.

Study at a glance

Question: How can AI writing tools be designed to facilitate writer-focused, process-oriented, and collaborative writing support?
Setting and data: Ten university writing tutors across three U.S. institutions; review with 30 writing instructors, tutors, and AI researchers; June–July 2025.
Method: Mixed methods: semi-structured formative interviews, iterative system development, internal audit, and an expert review using surveys and follow-up interviews.
AI tools: Writor, GPT-4.1-mini

Key findings

Experts rated Writor's non-directive, process-focused feedback as superior to commercial generative AI tools, with the strongest endorsements coming from educators skeptical of AI in writing.
Experts confirmed Writor successfully maintained a positive tone, balanced praise with critiques, and protected writer agency, though it could not replicate human-level depth and empathy.
Participants viewed Writor as an aid to complement rather than replace human instruction, identifying pre-tutoring preparation and modeling peer review as its most appropriate integration contexts.

Summary drafted with AI from the full paper and may contain errors. See the full paper for details.

As AI writing tools evolve from fixing surface errors to creating language with writers, new capabilities raise concerns about negative impacts on student writers, such as replacing their voices and undermining critical thinking skills. To address these challenges, we look at a parallel transition in university writing centers from focusing on fixing errors to preserving student voices. We develop design guidelines informed by writing center literature and interviews with 10 writing tutors. We illustrate these guidelines in a prototype AI tool, Writor. Writor helps writers revise text by setting goals, providing balanced feedback, and engaging in conversations without generating text verbatim. We conducted an expert review with 30 writing instructors, tutors, and AI researchers on Writor to assess the pedagogical soundness, alignment with writing center pedagogy, and integration contexts. We distill our findings into design implications for future AI writing feedback systems, including designing for trust among AI-skeptical educators.