From Crafting Text to Crafting Thought: Grounding Intelligent Writing Support to Writing Center Pedagogy (2025)

Abstract: Intelligent writing support tools have evolved from solving surface-level issues to collaborating and creating language with writers. Along with these new capabilities come concerns that generated fluent text can impact writers’ processes in unintended ways, especially for students. In this workshop paper, we look to a similar transition that writing centers experienced over the last century, which shifted focus from fixing surface-level issues to maintaining student writer voices. We interviewed 10 current writing tutors and grounded their described practices with ideas proposed in writing center literature. We employed these strategies in developing an intelligent writing tool prototype. We describe the design of our tool and discuss potential evaluations along with how to foster deeper relationships between writers and writing centers using intelligent writing tools.

## introduction with the emergence of large language models (llms) and the advanced text processing capabilities they entail, writing tools have undergone a fundamental transformation from fixing surfacelevel issues to creating spaces for collaboration and co-creation between writers and ai agents. commercial systems and research prototypes alike have expanded beyond suggesting grammar, spelling, and sentence structure revisions @xcite to helping writers reflect on the logical coherence and flow of their writing @xcite , overcome writer's block @xcite , gain new perspectives and ideas @xcite , and develop deeper awareness of potential reader audiences @xcite . this transformation has fostered surging interest in both human-computer interaction (hci) and natural language processing (nlp) communities to develop systems and agents that can aid writers throughout their diverse writing practices. yet, it is not clear how writing tools will impact these writing practices, for better or worse. this concern is especially vital for student writers, who are still developing their own writing processes @xcite . writing tools hold the promise of supporting student learning, but the fluent text generated by many tools might dilute students' perception of ownership @xcite or open up risks of plagiarism @xcite . the transition in writing tools today-and the concerns this transition raises-echoes the evolution of university writing centers over the last century. around 80 years ago, writing centers, then referred to as writing "labs" or "clinics," began emerging at universities across the united states, aimed at addressing student writing problems @xcite . much like how many writers today use automated writing assistants to finalize their writing, these centers functioned as fix-up shops, "cleaning up" students' papers individually before submission @xcite . 40 years later the purpose of writing centers began to shift. writing centers became more writercentered rather than curriculum-centered, processoriented rather than product-oriented, and collaborative rather than instructional @xcite . in response to growing concerns of student ownership and plagiarism amid these changes, writing centers developed strategies that realized the vision of collaborative writing spaces while centering the student within the writing process @xcite @xcite . writing centers have since become a widespread and successful resource across institutions worldwide @xcite , demonstrating the value of collaborative support in students' writing @xcite . in this workshop paper, we explore the parallels between writing centers and intelligent writing tools to rethink the roles of writing support tools in the age of llms. we ask the question, how can intelligent writing support tools facilitate writer-centered, process-oriented, and collaborative writing sessions? to answer this question, we first conducted an interview study with 10 current writing tutors at 3 us-based university writing centers to explore their strategies during writing sessions and their experiences with ai in writing. this formative study grounded the high-level ideas proposed in writing center literature @xcite @xcite to concrete practices. we synthesized these practices into design guidelines focused on creating writer-centered, process-oriented, and collaborative writing sessions. we illustrate how writing center strategies can guide the development of writing support tools by developing an llm-based prototype writing tool, writor, based on our design guidelines. writor supports two writing stages based on the stages described to us by the writing tutors ( §3) and prior writing center literature ( §2): goal setting ( §5.2) and editing ( §5.3). in the goal setting stage, writor prompts the writer to reflect on the assignment and potential readers, synthesizing a set of goals with writer input. using these goals, writor provides feedback and suggestions to writers grounded to a submitted draft in the editing stage. writers can follow up on feedback or request additional feedback by highlighting sections of their text. crucially, writor is designed to never give text verbatim to a writer. instead, writor employs feedback strategies tutors highlighted in our interviews, such as asking questions, providing writing suggestions that are topically distinct from the current writing, or pointing to sections of a writers' own text that can serve as guides for revision. we end by discussing potential evaluations of writor and ways to foster relationships between writers, writing centers, and intelligent writing tools. to support writers, ai tools employ a range of feedback techniques. some use socratic questioning to prompt deeper reflection and critical thinking @xcite , while others provide continuous summaries to help writers reflect through their writing processes @xcite . some ai writing assistants, such as those explored by @xcite , attempt to align feedback with a writer's values and intentions, ensuring that suggestions are contextually relevant. gero et al. (2023) also points out having conversational exchanges with computers as a form of receiving feedback. additionally, many ai systems take a generative approach for feedback, offering text suggestions or rewriting sections for the writer @xcite . in addition to feedback-oriented tools, many writing assistants offer more direct intervention. systems like coauthor @xcite and wordcraft @xcite actively participate in text creation. the widespread usages of generalpurpose llms has further accelerated this trend, as users can employ these models to draft texts such as emails and essays @xcite . this direct generation approach raises important questions about authorship @xcite and what it means to develop authentic writing skills in an ai-augmented environment @xcite . considering the ethical concerns surrounding generative texts and need for a structured approach to effective writing feedback, we draw on existing writing and writing pedagogy theories to inform ai writing support. these pedagogical frameworks highlight writer agency, process over product, and non-directive feedback @xcite @xcite , offering a principled alternative to fully generative approaches. to situate our work in the broader landscape of writing assistant design, we build on the framework proposed by @xcite , which maps five key aspects of writing assistants: task, user, technology, interaction, and ecosystem. our work contributes most directly to the user, interaction, and ecosystem aspects, focusing on how writing assistants can embody principles from writing center pedagogy to better support writers' learning and development. ## interview study writing center principles introduce a framework to help focus the development of intelligent writing tools. to ground the writing center principles introduced in §2 into practical guidelines, we examined how writing tutors implement them in real tutoring sessions through semi-structured interviews. the study was guided by two research questions: this study was approved by the relevant institutional review board. the interview schedule is included in the appendix a. ## design goals we translate tutoring practices from our interviews into actionable design goals for intelligent writing support systems, as shown in fig. 1 . we unified guidelines around how we perceived these strategies interacting based on interviews with tutors and writing center literature. "empathy to writers" and "building confidence" were merged into g1, as both contribute to motivational scaffolding. "examples and analogies" and "reader-perspective" were combined into g3, as both are instructional strategies tutors used in sessions to support process-oriented learning. ## system design we illustrate how our design guidelines can inform the design of intelligent writing tools by developing writor, an intelligent writing tool that aims to provide process-oriented, writer-centered, and collaborative writing support. ## discussion & future work in this workshop paper, we look to writing centers as one vision of writing technology that appropriately supports diverse student writing tasks. our interviews with writing tutors ( §3) and resulting design guidelines (fig. 1 ) illustrate ways that writing tools can support students in developing their writing by centering the student in a collaborative, dialogic process. growing concerns about academic integrity @xcite and over-reliance on text generation @xcite present an opportunity to re-imagine intelligent writing tools from content generators to process facilitators. our prototype writing tool, writor, illustrates one approach to this new paradigm, encouraging writers to engage with and refine their own writing rather than relying on ai-generated revisions. below we discuss potential evaluations of writor and further refinements that we are excited to pursue.