Vigor, Voice, and the Future of College Writing in the Age of AI
Why First-Year Composition Needs to Change—But Not Disappear
At a March 2025 AI-focused academic conference, higher education policy expert and recent Modern Languages Association president Christopher Newfield had an unsettling conversation with an Ivy League administrator. The administrator shared that their office was already preparing to defend the campus-wide writing requirement against an anticipated push from senior campus leadership to eliminate it. The reasoning for the change? “In today’s world, students need to learn to use AI,” especially as a replacement for traditional workplace writing.
Newfield, writing about this moment in a blog post “Liner Note 19. All-Out War on the Knowledge Society,” didn’t treat it as a passing comment. He saw it as part of a more significant shift: in the AI era, writing instruction may soon be seen not as essential academic infrastructure but as dispensable and outdated. With many in the field actively reimagining how we teach writing in response to generative AI, calls to eliminate the requirement itself—like Melissa Nicolas’s November 2023 Inside Higher Ed piece—are still rare but increasingly thinkable.
This post is a thought experiment: What if Newfield is right? What if the general education writing requirement is at risk—not just because of cost-cutting or transfer pressures but because influential institutions begin to treat writing instruction itself as obsolete in the age of AI? And if that threat to our discipline is in the offing, how can we reshape first-year composition to reflect the human capacities that education should still protect?
There’s so much of value that we already teach in first-year writing: inquiry, synthesis, ethical judgment, reflection, rhetorical awareness. I don’t want to be alarmist. But I do worry that if we attempt to wall off our writing instruction from the active use of generative AI—whether out of fear, doubt, or habit—we risk making ourselves irrelevant at the very moment when our work is most needed. If we refuse to engage with the tools that are reshaping writing itself, we may find the requirement under real threat—not just from political or budgetary pressure but from the perception that we’re teaching a version of writing that no longer matches how writing happens in the world today.
From Rigor to Vigor in College Writing
For decades, first-year writing has been organized around a “Learn to Write” model: teaching students to master academic genres, thesis statements, paragraph structures, and citation formats. It often takes the form of essay training—sometimes helpful, but too often rigid, overly formal, and disconnected from how writing actually functions in students’ lives and in the world.
The result has too often been rigor without vigor—essay-shaped artifacts that meet formal expectations but rarely invite surprise, risk, or discovery. Writing becomes something to get right rather than something to think with.
But even before AI shook the foundations of school-based writing, composition scholars have been calling for a different emphasis. Donald M. Murray, Pulitzer Prize-winning journalist and author of the 1996 classic Write to Learn, argued that writing should be seen not as a product, but as a process of discovery:
“Writing is a process of exploration; and, by discovering what we have to say, we discover who we are.”
Similarly, writing studies scholar Heidi Estrem puts it plainly in Naming What We Know:
“Writing is a knowledge-making activity.”
This shift—from rigor to vigor—is not about abandoning structure or standards. It’s about re-centering energy, experimentation, and thought. It’s about reclaiming the writing classroom as a space for wrestling with ideas that don’t yet have a form, rather than polishing ones that already do.
In this model—what the Writing Across the Curriculum movement calls “Write to Learn”—students write to inquire, reflect, synthesize, and grow. Writing becomes a method of learning, not just a deliverable.
And in the AI era, this isn’t just a pedagogical preference. It may be the only way forward. If machines can deliver rigor on command, what’s left for us is the work of thinking, grappling, and making meaning—a vigorous kind of writing that’s still, and maybe more than ever, worth teaching.
Insisting on Process in an Age of AI Output
If we shift from rigor to vigor, then writing is no longer just a performance of correctness—it becomes a practice of thought. In this model, writing is not simply a way to report conclusions; it’s how students reach them. The focus moves from producing tidy, self-contained essays to engaging in iterative, inquiry-driven work. Writing becomes a process of wrestling, revising, and reimagining—not just documenting what’s already known.
For decades, writing instructors have championed the value of process—the rough drafts, the abandoned ideas, the generative confusion. But that ideal has often struggled to survive in classrooms shaped by rubrics, deadlines, and the gravitational pull of the grade. We reward polish when we should reward persistence. And now, in the age of generative AI, that tension has become unavoidable. When a machine can produce a competent college-level essay in seconds, we’re forced to ask: What are we actually teaching when the grading system rewards appearance over inquiry and values the outcome more than the messy struggle that gives it meaning?
Vigorous writing doesn’t fear the draft. It doesn’t fear failure, either. It embraces revision as a form of thinking, not just fixing errors or refining structure. And in this framework, AI isn’t a threat—it’s a collaborator. When students co-write with AI tools—not to bypass the process, but to deepen it—they’re still doing the real work: questioning, refining, interpreting, and deciding what matters. The machine can generate drafts and suggestions—but only the writer can recognize what reflects their thinking, revise what doesn’t, and shape the language into something that genuinely expresses what they mean.
If we want to keep writing instruction meaningful, we must design for—and assess—thinking in motion, not just polished final drafts. That means:
Exploratory and recursive writing, not one-and-done drafts
Writing through problems, not just writing up answers
Reflection, synthesis, and intellectual risk-taking over surface-level fluency
As John Warner, author of Why They Can’t Write, cautions:
“If we’re not careful, we can spend all of our energy teaching students how to produce a particular kind of writing that they will never do again after they leave our classrooms.”
The goal isn’t to abandon academic writing altogether—it’s to release it from the straitjacket of lifeless rigor. We must treat writing as a habit of mind: flexible, reflective, and open to surprise. In the AI era, this kind of writing—the kind that reveals thinking, not just polish—is what remains uniquely ours to teach. And what makes it still worth teaching.
If we want writing instruction to survive—and matter—five core practices should take center stage in a vigor-driven, AI-aware classroom.
Core Practices for a Vigor-Driven Classroom
Vigorous writing is not just a method—it’s a mindset. It resists templates, invites uncertainty, and teaches students how to live with complexity rather than rush to closure. If we’re serious about shifting from polish to process, from output to inquiry, we need to elevate the skills that support this kind of writing. Not as extras. As essentials.
The rise of generative AI not only calls into question the value of traditional essay-based instruction but also clarifies what writing courses have always done best: help students think critically about the world, their role in it, and how meaning is constructed across texts, media, and technologies.
The skills needed to do this work are not new. They have long been part of composition—sometimes explicitly, sometimes buried beneath the surface of thesis statements and structured paragraphs. What’s needed now is not invention but re-centering. These skills must no longer orbit the essay; they must become the gravitational center of the course itself.
Call it critical digital literacy, expanded textual literacy, or simply what it means to read and write well today: this work prepares students to interpret, navigate, and intervene in a world where not everything that looks like writing comes from a human mind—and not everything that persuades or informs does so in good faith.
It means teaching students to:
Ask better questions in a world that offers templated answers
Reflect on their thinking and process, not just deliver content
Navigate ethical dilemmas around authorship and AI use
Communicate rhetorically across contexts, resisting homogenized machine-generated discourse
Compose across modalities, using image, sound, data, and text to shape meaning intentionally
These five capacities—inquiry, metacognition, ethical judgment, rhetorical agility, and multimodal fluency—are not new additions to writing instruction. They are what writing instruction has long gestured toward. Now is the time to make them central—not to defend the writing requirement with appeals to tradition but to clarify its enduring relevance in a world where machine-generated output is everywhere and human meaning-making is more urgent than ever.
1. Inquiry and Intellectual Curiosity
At the heart of vigorous writing is not the answer, but the question. First-year writing should help students ask better, deeper, and more generative questions—across disciplines, genres, and media. These questions fuel interpretation, skepticism, and imaginative thought.
In an era when AI can instantly deliver polished answers, inquiry becomes a form of intellectual resistance: the ability to pause, probe, and dwell in uncertainty.
Good writing instruction cultivates curiosity—not compliance—and centers inquiry as a habit of mind that cannot be automated.
2. Metacognitive Awareness and Process Thinking
Writing isn’t just about producing content—it’s about learning how we produce it. Vigorous writing requires students to reflect on their thinking, their decisions, and the shifts that happen between draft and revision.
In a world of instant AI drafts, students must be able to explain how they arrived at a claim, why they revised it, and what that process revealed. Their writing isn’t just an artifact—it’s evidence of growth.
Teaching writing today means teaching students to narrate their own learning—not just turn in a finished product.
3. Ethical Judgment in a Machine-Mediated World
Authorship, originality, and collaboration have always been part of writing instruction. But AI raises new ethical stakes: What counts as assistance? When does convenience become avoidance? How do we disclose co-writing without undermining ownership?
Writing classrooms are uniquely equipped to help students wrestle with these questions—not with fear but with honesty and nuance.
We’ve long taught citation. Now we need to teach technological transparency and ethical decision-making in co-authorship.
4. Audience Awareness and Rhetorical Agility
Rigid academic formats often teach students to write only to their teacher. But writing that matters requires students to adapt their voice, tone, and structure based on shifting audiences and platforms.
AI can mimic genre conventions, but it doesn’t grasp context or care. Human writers do.
Rhetorical agility is no longer a capstone skill—it’s a survival skill in a world of flattened, machine-written prose.
5. Multimodal Fluency and Composing Across Technologies
Writing today is rarely just words on a page. Students blend text with image, audio, video, code, and data—often intuitively, but not always critically.
First-year writing should be where that fluency becomes intentional: where students learn to shape meaning across modes and platforms, and where they ask what their design choices do rhetorically.
Multimodal writing isn’t extra—it’s how students already compose. Our job is to teach them to do it with clarity, purpose, and power.
Language Is the System. Writing Is the Key.
This is exactly why, as Ethan Mollick argues, the humanities—and especially writing—must play a central role in the AI era. Mollick, a professor at the Wharton School and a widely followed voice on AI in education, has repeatedly emphasized that AI systems are not just tools; they are language models:
“One reason I wish more humanities-oriented people would engage with AI is that models are writers, trained on words, producing words. There are strengths & weaknesses in the models that can only be seen if you engage deeply with them as writers.”
If large language models are trained entirely on human writing, then understanding how language works—how it persuades, distorts, informs, and excludes—is not peripheral. It’s infrastructure.
That means writing instruction is no longer just about academic literacy or thesis construction. It’s about shaping the ethical, rhetorical, and intellectual frameworks that will define how humans and machines make meaning together. We need writers—human writers—who can evaluate, intervene in, and reimagine these systems.
That work doesn’t start in the workplace or the think tank.
It starts in classrooms like ours.
The Future We Write Toward
This is not a nostalgic defense of writing and writing instruction. It’s an argument that we must transform it—urgently and intentionally—to remain indispensable. If first-year writing courses are seen merely as grammar drills or essay mills, they may not survive the next wave of AI integration in higher education.
But if we reposition writing instruction as a place where students learn to inquire, reflect, discern, and communicate meaningfully across media and modalities, its value will be unmistakable. Not because it’s traditional but because it teaches the human capacities most needed in an AI-shaped world.
In this vision, writing isn’t replaced by AI.
Writing teaches students to think in dialogue with AI and think beyond the machine.
That’s not just a future worth preserving.
It’s one worth writing toward.
This post was drafted using AI-assisted tools in collaboration with my own writing and revision process. This reflects my commitment to experiencing both the potential and limitations of using AI in writing instruction.
The future of writing will be roughly like the future of math when calculators became widely available.
Students don't need to do every calculation manually, but they do need to do it enough to know what a good answer looks like.
Your ideas are the start of what that will look like for writing.