Interview with Write Now Philly about Teaching Writing in the Age of AI

I had a great conversation with writer Khristina Cabrera from Write Now Philly about, as the title of the interview says, "Teaching Writing in the Age of Artificial Intelligence." As she termed it, we focused on  “navigating AI use in the classroom."

Interestingly, I've used a lot of pixels in this space to describe how and why I think asynchronous writing, often through message/discussion boards, is a strong way to teach in the writing class[room], but I tell Cabrera that while "I’m not disheartened by" AI in a writing pedagogical sense, using an asynchronous teaching model

isn’t as effective anymore, because AI is a big problem in discussion board conversations, so I’m thinking now, what can I do differently to continue to give students a good educational experience? I don’t want to think, how can I prevent them from cheating, because I think once you get into that deficit kind of approach, then it can be more frustrating.

It's certainly an ongoing challenge.

She had many thoughtful questions, and the interview helped me work through some thoughts about teaching and writing with AI.

The published interview promotes a recent publication of mine, but in this case the good news is that was really just a set-up for someone else's work, as I co-authored a forward I wrote for Amy Cicchino and Troy Hick's edited collection Better Practices: Exploring the Teaching of Writing in Online and Hybrid Spaces. Check it out!

Maybe someday, "I taught an LMS today..."--but not yet

AI--yep, it's been infringing on fundamentals of writing instruction, as almost every professional conversation in the field would indicate. Teachers are scrambling to find reliable plagiarism checkers. Blue books and oral exams are re-emerging. People are eyeing retirement so they don't have to deal with this.

I have clearly staked out territory in my career as an advocate for asynchronous online writing courses (OWCs), working from my conviction that the written digital exchanges among OWC students are arguably better for their learning than onsite courses. I wrote in my 2009 book Teaching Writing Online: "The online environment also provides us with an opportunity specifically because of the subject matter of the writing course [...] Our constant efforts to work with student texts are unique and irreplaceable, and our model of technology use can be perhaps the most humanistic in the academy" (xxi)

"Unique and irreplaceable"--I feel like this been a wheelhouse for writing teachers, and a space that allows us to maintain student writing--as well as identity--authenticity.

But recent coverage of the release of Einstein, an agentic AI program that allegedly connects with common LMS systems and basically completes all coursework for students, has (even) me wondering about the endeavor. As reported in a February 26, 2026 Inside Higher Ed article by Kathryn Palmer, Einstein "logs into Canvas every day, watches lectures, reads essays, writes papers, participates in discussions, and submits your homework—automatically.”

This program and others that will undoubtedly follow carry the threat of a non-human agent making its way through a course in ways that may be indistinguishable from a human. Damn, I could teach a bot!

Michelle Kassorla, Associate Professor of English at Georgia State University | Perimeter College, Dunwoody, provided a good write-up/review of Einstein on her Academic Platypus Substack. Kassorla signed up for Einstein using a debit card with no money on it and her son's computer (to avoid institutional IT woes). She immediately saw that it's pricey for a college student: The Plus plan, the apparently lowest-tier, is $40/month. She recorded her experience and then quickly (in 2 minutes and 30 seconds) discovered "that Einstein is just a wrapper over OPENCLAW! AAAAAAAH I had just installed an agent that runs in the terminal in my son’s computer—potentially exposing EVERYTHING on it to the agent. I got off the recording ASAP to delete the program from my son’s computer." (1)

You can read more about Kassorla's take on a program of which she says, "However, it is probably duping students, who have no idea how dangerous it is."

Yet she ends with a glimmer of hope--at least for now. Kassorla makes some suggestions that online writing teachers can certainly relate to: "What can we do about this? Design your courses carefully, scaffold, make them process oriented, and put in some hard stops where students have to do a hard thing that you grade before they can move on."

At this point, there's still teacher volition, and I want to emphasize that the IHE article perked up my antenna a little because it says Einstein (my emphasis) "can help with any subject, including math, physics, computer science, history, literature and economics, and even keeps working when students are asleep." In that list, I didn't see writing--I see all content courses.

We're still teaching humans. There are challenges out there, but we're not spending our time only making bits in Canvas "smarter," not yet. 

Note:

1) According to Wikipedia,"OpenClaw serves as an agentic interface for autonomous workflows across supported services. OpenClaw bots run locally and are designed to integrate with an external large language model such as Claude, DeepSeek, or one of OpenAI's GPT models."

Process Narration Videos and authentic student writing

Just like everybody else in writing classrooms nowadays, I'm dealing with AI. I like to think I'm mostly working with it, although, my sanguine teaching nature aside, I'm for sure at times working against it.

In several classes, I've overtly invited students to write about and sometimes even for the machine, as in my recent Language Puzzles and Word Games: Issues in Modern Grammar course, which includes this writing project choice (among many): "Using a prompt similar to an assignment from one of your courses, compare the text created by a generative AI chatbot/natural language generator with your own writing specifically in terms of grammar and usage."

In the Fall, I got to talking to an exceptional student, Veronica Medlock, about the drafting process in her writing. After that conversation, she quickly created and sent me a short YouTube video of the drafting changes while she composed, accompanying the video with a voice narration of the process.

It was fascinating.

We're trying to take this show on the road and have sent in a conference proposal about how such "Process Narration Videos," as we're calling them, can help promote and support authenticity in student writing assignments. Students can compose and submit these easy-to-create videos, which are built on the draft stage "mapping/tracking" that is a fundamental component of writing composition tools like Word and Google Docs, with accompanying voice narration.

Why is this so great? Of course, the English and writing teaching and learning literature has been overflowing with discussions about the problems of teaching writing in the--dare I call it?--age of AI. Teaching publications are dedicating focused space to AI (1) and instructors nearly every day receive invitations to professional development opportunities or information about new ed tech tools. Language and literacy teachers at all levels (and, of course, in many, if not all, other academic disciplines, e.g., math and programming) are dealing with the challenges of AI in teaching with a range of attitudes, approaches, tools, and philosophies. 

Some of my colleagues feel the authenticity problem is so dire that they are abandoning process-driven writing approaches and are instead returning to blue books or other non-digital, offline writing approaches. Those who have not given up have taken various often time- and energy-consuming stances and approaches: Requiring increasing amounts of informal writing, carefully scrutinizing the drafting process, leaning heavily on AI checkers in a kind of technological arms race, etc.

But as part of an overall writing pedagogy, Process Narration Videos provide a foundationally sound, pedagogically driven solution to authenticity issues in writing instruction. They reinforce good writing pedagogy, as they are grounded in writing process and ask students to reflect on their writing. They also help students see different stages of their writing, incorporate metathinking, consider rhetorical choices, and embrace informal writing, which of course is often embedded in strong writing processes.  

If our proposal gets accepted, Veronica and I will discuss the compositional background of this approach while focusing on the practical, hands-on way that it can be applied in classrooms across educational levels and curricula.

An important point is that students are often as frustrated by the prospects of other students using AI as their teachers are. So we're aiming to hit a nice balance: While Process Narration Videos can serve a dutiful--and responsible--academic process in discouraging AI-connected plagiarism, they are also simply good teaching and learning practice.

Note:

1) The topic of the most recent issue of CCC [77.1] was, as the Editors’ Introduction stated, “A Dappled, Undisciplined Response to Generative AI."

Narrating a research journey

While we were teaching... lots of questions for writing instruction, especially in digital environments.

As I always say, I'm not playing cops and robbers with my students, but we have to be responsible; we have to keep sharpening the way we approach writing assignments. Much like we always should be doing, we've got to use common sense to help students do their best work. AI is just the latest temptation for them not to do so.

Sources are an issue. Since search engines have evolved, there has always been an opportunity for students to come up with wild sources: Where did some of these things come from? 

Aside from the well-established "hallucination" issues that come up when we use AI as a research tool--and remember, that type of search is not what LLMs are primarily designed for or good at--it can also dig up/create material from who knows where.

A way to help combat this is a twist on the annotated bibliography: Ask students, using plain language and perhaps images, to narrate the research path they've taken. I'll frame it like this for students:

Tell me for each source in your bibliography/references/works cited:

1. What tools or apps you used for the search, or, alternatively, who you talked to.
2. What prompts you used to generate your references: Reproduce them verbatim.
3. How much did you each resource when choosing to add it to your resource list?
• This is a shame-free zone: Did you read the abstract? Glance through it for a key word, author, or quote? 
• Reflect on what you did: This will be of interest not just to me but I imagine to you as well.
4. How did you extract information into your project?
• Did you use quotes, paraphrased material, data? 
5. How did you create the citation?

Of course, this is not an exhaustive list, and this is not necessarily something you would use only in OWCs, but because of the text-heavy environment of the OWC, a "research narrative" might be particularly useful there.

On the novelty scale, this approach is pretty tame, but it provides--in what I would argue is a constructive, reflective way--an overt learning strategy for students to describe how they are interacting with AI and search tools to generate the sources and knowledge that form the basis for much of their writing projects.

Writing instructors: Lean into our roots!

As I suppose many writing teachers are, I'm increasingly being asked about teaching writing now that AI is ever-present among us, especially teaching online, whether online writing instruction (OWI)-specific or not. My suggestions/recommendations are strongly based on my belief that we lean back into many of the long-term pedagogical strengths of Writing Studies/Composition and Rhetoric.

First off, it's not all a cosmic struggle vs. plagiarism. While authenticity is tied up with good instruction, we can't let plagiarism become a bugbear that obstructs us or distract us from fundamentally working with students to improve their writing.

We have for a long time had a lot to offer, and in OWI courses, especially asynchronous courses built on writing interactions, we can manifest much of these advantages by using, as I wrote earlier this year, a mix of approaches: 

• Process/drafting. We should continue to create learning environments in which students fundamentally engage in process-driven writing.
• Peer review. Peer-to-peer writing has many advantages, including that it creates authentic audiences for which students are responsible. Again, this means that while some (few) students might feel unabashed about putting an AI (or otherwise inauthentic) writing piece in front of a professor, they may think hard before placing such a piece in front of fellow students. In general, a lot of peer writing helps make the class a semi-public space.
• Informal writing. Students need to have many opportunities to connect writing and thinking. We can say it all we want, but we need to have students see it by giving them ways to use informal writing to build more complex projects.
• Low-stakes writing. Tying in with the above, I'm a believer in grading (almost) everything, but with the caveat that the grading be FLS: frequent and low-stakes.
• Unusual readings. As I wrote a few months ago, assign a "textual brew of unusual texts and discussion prompts." To put it simply, build assignments from texts that are less likely to be part of an LLM's database.
• Metacommentary/Reflection. Remember that us writing teachers are very good at this, with our long-entrenched embrace of portfolios, including for assessment. Last year, I wrote about how, "Metacomments push students to talk about their practice and to defend their choices." 
• Embracing the technology. Part of using metawriting and metathinking is bringing into conscious focus things around us that might otherwise be transparent. While you don't have to center your course (or even assignments) around technology, it is worth making sure technologies are not transparent: Have the students address their use of technology, even in short reflections.

These approaches and suggestions are not just Writing Studies/Composition pedagogy but are specifically how such pedagogies might manifest themselves through OWI. As those of us in the field of OWI have been saying for well over decade, at some point all writing instruction became OWI, and we cannot retreat into blue books because of technological change.  

 OWI is far from dead--long live OWI!

As AI becomes increasingly [S]ubtle

Lately, it's not often I refer back to my 2002 dissertation, "Subtle Technology and Student Writers: The Ambient Influence of Technological Myths on Communicators," but in the diss I had a core idea that's relevance might be re-emerging, a concept I described as Subtle T(echnology); I'll define it here very briefly as "a theoretical transformation digital technology might undergo that leads to complete dependence on these machines." The transformation occurs "when five interdependent traits of digital technology are fully realized: ubiquity, transparency, dependency, interconnectedness, and insubstantiality" (1).

With the explosion of AI use, I think Subtle T provides a valuable lens for viewing this technology, which I could argue has been integrating itself into our activities in ways that meet the traits above.

Of course, I was always a Writing Studies/Comp Rhet researcher and practitioner, so in the diss I described how Subtle T functioned in writing instructional scenarios.

Recently, I had a situation in a course in which I thought a student might have plagiarized language in parts of a project. I didn't think this student had malevolent intent, but some of the writing seemed inauthentic when compared with their other writing, particularly informal writing, in the course.

My course AI policy encouraged productive use of LLMs, so I was more interested in a constructive dialogue than a wrist-slapping--or worse.

When we met, I pointed out passages I felt were inauthentic, and I said while I didn't think it was material deliberately clipped from other sites or sources, it appeared to be AI-generated text. 

We had a good conversation, but the student was nonplussed as I talked about using AI and when eventually asked straight-up if they used AI tools. They told me, equally straight-up, no. The student said while they had indeed used material they found in Google searches to help develop the project, they were "just using Google," not AI.

Well, of course, if you are "just using Google" right now, the first "hit" is an "AI Overview," marked with a "sparkle icon." The student was surprised by this and told me, and after our discussion I believed it, that they didn't think of the results of Google searches as AI, despite the "sparkle icon."

This to me was another good example of how we'll have to keep up in our courses with AI. Many teachers are growing accustomed to handling the results of prompt-based AI use: We feel confident that students who use prompts and submit the subsequent text from LLMs are overtly plagiarizing. But embedded tools?--we'll have to sharpen definitions. Grammarly is one thing. AI built into Google searches is another. 

I almost feel that we might have to broaden our perspective and be careful not only of students using AI but of AI using them: Their common behaviors may be co-opted in ways that are ubiquitous, transparent, dependent, interconnected, and insubstantial. They will notice less and less.

Maybe it's time for me to renew my efforts to get that diss published. 

Note:

1) From page 1 of the diss, which I completed at Temple University. 

Audio still sounds right for student response

I'm a ways away from blogs and other writing I've done about audio--and at times, audiovisual--feedback (see References below).

In practice, though, I've been sticking to it, lately using Turnitin's built-in audio function (Turnitin itself is built into Blackboard at Drexel), which gives you a one-click option for a three-minute audio response to student assignments.

As I've described, there are many advantages to audio response, including comprehensiveness of response, time spent on task (audio response is fast), and psychological load of responding to student writing.

It strikes me that audio also may be more relevant than ever as teachers struggle with AI, because I think among the authenticity/integrity issues that we're running with AI tools into is the way they may depersonalize the student-teacher writing relationship.

When you provide voice commentary, students hear you--I intentionally emphasized both words. Will that make them feel bad, feel sorry, feel reflective about me as their instructor? I don't know. But I do think that it makes them feel something about me, because I'm clearly on the other end.

What does a student who has intentionally and perhaps maliciously cheated think when they hear that raspy voice of mine enthusiastically and often discursively responding to their work? Perhaps they have ice water in their veins, but it seems my chances of receiving authentic writing from them improve.

Perhaps I'm fooling myself. But it doesn't matter anyway, because providing audio or audiovideo response is faster and more thorough. If it personalizes me along the way, all the better.

A few pieces about this I've written:

“The Low-Stakes, Risk-Friendly Message Board Text.” Teaching with Student Texts: Essays Toward an Informed Practice. Eds. Joseph Harris, John Miles, & Charles Paine. Logan, UT: Utah State UP, 2010. 96-107.  

“Cutting Keystrokes, Improving Communications: Response Technologies for Writing Instruction.” California English 15.1 (September 2009): 27-30. 

“Responding to Student Writing with Audio-Visual Feedback.” Writing and the iGeneration: Composition in the Computer-Mediated Classroom. Eds. Terry Carter and Maria A. Clayton. Southlake, TX: Fountainhead Press, 2008. 201-27.

A mix of approaches in this term's asynch OWC

I'm again teaching an asynchronous first-year online writing course (OWC) this term, and in an environment of increasing AI apps in which teachers not only worry about academic integrity but have more fundamental concerns about what it means to teach writing, I have found myself working from established practices while still refining them to account for the fast-paced changes we're facing.

I'm engaged in a variety of practices to try to maintain a writing-heavy class environment, some of which I've written about individually before:

• I'm again using the "textual brew" of unusual texts and discussion prompts.
• I'm trying to strengthen the relationship between the discussion posts and the major course projects.
• Speaking of discussions, I'm using them in a tried-and-true way to see a great deal of informal student writing: It's mid week 4, and in a class of 20 we're already over 550 posts (including my contributions).
• Drawing on the fundamental nature of low-stakes, informal writing, I'm having students in mini  assignments--right on the discussions!--analyze and revise their own posts; e.g., revising out instances of the verb "to be" in a post they choose.
  
• I've included the stoplight approach to AI that I mentioned last time.
• I'm asking students to include a one-page metacommentary about their use of AI in conjunction with that stoplight approach.
  
• Working with several of my colleagues in a mini teaching circle, I've assigned a fantastic book that helps students take a critical look at technology, Jason Ohler's Taming the Beast.

How's it all going? Talk to me after the quarter is over. However, I'm enjoying it: The challenge is there. These practices have created a productive pressure on my pedagogical approaches.

"Stoplight" approach to AI use in writing assignments

Like you, my Inbox is bombarded with messages about AI. I try to keep up, to stay especially focused on the writing instruction-centric ones, but it seems that only an AI-based triage tool can help me with the deluge...

Teachers do keep productively discussing the challenges of student use of AI, especially in writing instruction. This term, I am team-teaching an Honors seminar Contrasts in AI: Now & Future, part of Drexel's overall Honors College theme this year: Black & White. The class has been a great experience, particularly working with my colleague, a computer and electrical engineering professor.

Our course is about AI, and in addition to many informal assignments such as reading notes and quizzes, we also have three short papers/projects. We talked about this a lot in the summer, and we eventually developed a "stoplight" approach that we thought not only fit well with our course subject matter but also helped us address the challenges of requiring short papers in this current AI educational environment. Lightly edited from the syllabus, here is what we asked of students:

You will write three short, 500- to 1,000-word papers/projects in the course, due Weeks 4, 8, and 11. We’ll discuss each in class when it is assigned, but in general you’ll follow these guidelines:

1. For the theme/thesis of each paper/project, you will develop a contrasting perspective/view of some aspect(s) of AI, building on the course materials and conversations.
2. Each paper/project will be different in its use of AI, based on a “stoplight approach”:
• Project one is RED: You cannot use any AI, including grammar checkers like Grammarly. It may be impossible to avoid some built-in tools in Word and Google Docs.
• Project two is YELLOW: You can use some components of AI to help you develop your ideas and deliver them. You might think of writing on a kind of scale of complexity or a continuum, starting with the word, working through the sentence, then paragraph, then overall concept/purpose. (We missed a few steps in between for sure.) For “Yellow,” please do use AI bots/apps in your project, but only do so up to the paragraph “level.” We ask that you still not use AI for invention, conceptual, or organizational matters, but you should feel free to “partner” with ChatGPT, Copilot, etc. to help you at the sentence- or word-level, perhaps in particular with grammar and mechanics.
• Project three is GREEN: You can freely use AI as a partner to help you write your paper. Note that you cannot just submit the raw text generated by an AI app/tool, but you can certainly go through an evolution of prompts in presenting your final paper.
3. For each paper, you will include at the end a one-page metacommentary about how the use of or the constraints on the use of AI affected your development of your ideas. There are alternative ways you could present this metacommentary that we’ll discuss in class. Note this is different from the AI statement described in the Course Policies below.

So far, we've received the red and yellow papers/projects. This class of bright students have written strong, thought-provoking projects, but, boy, has the hidden gold been in the metacommentaries. 

In these end reflections, students have commented in considerable depth about the constraints of the red and yellow categories, how they navigated what those categories have meant to their writing process, and in some cases how they hadn't realized how much they had become reliant on AI tools in their writing. (Note the metacommentaries are part of the grade, a deliberate move we made so as to reward their thoughtful work.)

I want to reiterate that our class is about AI: Issues surrounding AI are part of the course subject matter. That certainly helped lead us to developing a "medium is the message"-type approach to the assignments.

However, including these detailed metacommentary components has helped us with our writing pedagogy. While plagiarism and authenticity weren't primary targets, the metacommentaries have encouraged authenticity while also providing them with a platform to discuss their own writing and thinking processes, in line with decades of composition work about the value of such writing.

As instructors, we are eager to receive paper/project three next week, not only to see their final thoughts about AI contrasts but to read how the open green category differed for them in their use of AI in their writing.

Messy final drafts and metacomments

Like many teachers, I've been thinking about how writing studies faculty can help ourselves and our colleagues by drawing on our expertise to keep up with some of the challenges AI poses in writing instructional environments.

One teaching strategy I have been using is discussion-board dialogue about final student projects , as I described in "AI apps and student writing worries?: An old, reliable OWT practice can help"and "Generative AI and integrity concerns: More discussion board support."

That was a mixed bag. I used this teaching strategy in two very different courses. In one class it worked great. In another class, not so much.

In the latter class, I think the lukewarm success was partly because the course assignments didn't lend themselves to conversation. This course, The Literature of Business, has assignments that, while students can make them their own, does create somewhat similar results.

So I lived and learned. In recognition of those problems, I added another layer. I started also using metacomments: simply put, I ask students to write about their own writing as part of the assignment. This is an old composition practice, and in fact Julianne Ross-Kleinmann and Wess Trabelsi recently described a version of it in a smart T.H.E Journal piece "Teaching and Learning, Cheating, and Assessment in the Age of AI":

Another way to change teachers' method of assessing papers is to ask students to defend their work. This means having a conversation with them about their paper, either in person or when they upload it to the learning management system. Why did they make this argument or include that fact? What is the crux of their position? If they can't answer these kinds of questions, maybe they shouldn't receive a good grade on the paper — even if it is an excellent piece of work on its own. (emphasis mine)

Metacomments push students to talk about their practice and to defend their choices. In asking for these comments at the paragraph level, I am seeking granular analysis about their rhetorical choices.

My primary goal is constructive pedagogy, but if we're worried about authenticity and plagiarism, these comments head off a lot of clear, wholesale "borrowing": even if generative AI (or their roommate!) wrote a paper for them, they would still in many cases have to think through what each paragraph means in the context of the assignment.

If they tried to get AI, they still have to cut-and-paste individual paragraphs and generate the purpose--note, not the summary--of that paragraph in the context of the entire assignment. They're going to have to do some work in most cases.

My students have produced strong metacomment work. At times the comments are good. Sometimes they are fantastic. And occasionally they are better than the writing project itself.

However, I had to shake myself out of normalcy and embrace a new mindset when reading student writing. While in writing studies we often talk about embracing process, we traditionally still want something clean handed to us. Indeed, I think most teacher-readers are enamored of the "clean draft": neat, tidy, finished. I get why, but if we use metacomments the way I'm suggesting, we're asking for a "messy final draft," one in which students accompany each paragraph with comments about what they want to achieve; such writing will be intrusive. 

I don't require students to be fancy in formatting their metacomments. Footnotes or endnotes are ideal, but I'm fine with inserted bracketed or boldfaced comments after each paragraph: Messy, but functional for this purpose!

Ultimately, I'm moving away from the cleanly "typed" paper toward a product that vividly shows the often messy excellence of student thinking.

AI and the Philadelphia Eagles' greatest center ever

Occasionally I get to cross my two little corners of the web. Here is a version of a piece I wrote on my blog on the site When Falls the Coliseum about the farewell speech of Philadelphia Eagle center Jason Kelce. It was a powerful, emotional speech, and a strong piece of writing and rhetoric.

The delivery was not just quintessential Kelce, but it was very much something of the writers of his time and generation: Dressed in a sleeveless workout shirt and sandals, he read the speech from his phone; he had perhaps even composed it on that phone--writers regularly compose on phones now.

For a book club at Drexel, I happen to be reading The Meaningful Writing Project by Michele Eodice, Anne Ellen Geller, and Neal Lerner, in which they describe their research project to discover how students report the qualities of meaningful writing experiences, how those experiences are connected to learning, and how what faculty offering such projects conclude about meaningful writing, finding this:

meaningful writing projects offer students opportunities for agency; for engagement with instructors, peers, and materials; and for learning that connects to previous experiences and passions and to future aspirations and identities. (4)

Watching Kelce, I thought and felt a lot of things from many perspectives. In my role as a teacher, I thought: "No way AI wrote that speech."

Why? Because I was struck by how authentic Kelce's speech was. It was him in content, style, and voice.

I thought how proud I am when I receive authentic writing from my students. And it made me think again of the big challenge--a challenge now renewed because of generative AI (GAI)--facing us writing teachers to create writing assignments that are not plagiarism proof so much as plagiarism discouraging because they bring out authentic, meaningful writing from our students.

I know it's not simple for us as teachers to create such writing assignments. After all, we're not going to be able to reproduce easily contexts like Kelce's, where someone emotionally bids goodbye to an activity of passion after nearly a decade and a half.

But I believe GAI productively pressures teachers to create more meaningful writing environments for our students. Assignments with authentic roots will have a greater likelihood of inspiring such responses.

There's considerable and rightful concern in composition about GAI. Will GAI engines grow in sophistication to the point that we won't need people for that very human task, writing? Maybe, but as I watched Kelce, I thought, "I don't think so"--or at least, "We've got a ways to go before that happens."

I won't start boasting that I can create plagiarism-proof assignments: Students will take up the challenge and prove me wrong. But listening to Jason Kelce's farewell from football, I realized that if I keep striving to develop assignments that mean something to them, students will return something meaningful for me and, more importantly, for themselves.

Integrity and AI

At Drexel I'm a member of a recently assembled committee called the Provost's Office Working Group on Policy for Academic Integrity with Artificial Intelligence. Like many (most? all?) colleges and universities, we're trying to create academic integrity guidelines (or guardrails) for our faculty and students.

One aspect of our working group's efforts that I like is that in the background of our statement, the initial item describes the value of AI in education. We're not treating these tools first and foremost like a problem: Instead, we are treating them like tools vast potential, but potential we must understand within a sphere of sensible, ethical guidelines.

This is crucial, because in line with our local work, statements and guiding principles are being posted everywhere. Here are a few samples.

Even early on, people were developing language, such as the course policy wording by Ethan and Lilach Mollick in “Why All Our Classes Suddenly Became AI Classes” (1). They provide sample course policies:

I expect you to use AI (e.g., ChatGPT and image generation tools) in this class. In fact, some assignments will require it. Learning to use AI is an emerging skill and I provide tutorials on how to use them. I am happy to meet and help you with these tools during office hours or after class.

Be aware of the limits of ChatGPT, such as the following:

• If you provide minimum-effort prompts, you will get low-quality results. You will need to refine your prompts in order to get good outcomes. This will take work.
• Don’t trust anything it says. If it gives you a number or fact, assume it is wrong unless you either know the answer or can check with another source. You will be responsible for any errors or omissions provided by the tool. It works best for topics you understand.
• AI is a tool, but one that you need to acknowledge using. Please include a paragraph at the end of any assignment that uses AI explaining what you used the AI for and what prompts you used to get the results. Failure to do so is in violation of academic honesty policies. Be thoughtful about when this tool is useful. Don’t use it if it isn’t appropriate for the case or circumstance.”

The February 2023 Institute for Learning and Teaching at Colorado State describes a "multiple possibilities" approach to syllabus statements with AI, including examples from syllabi:

• The Prohibitive Statement states that any AI "use on graded work/ work for credit will be considered a violation of the academic misconduct policy." The Prohibitive Statement is appropriate "for a class in which the course outcomes have been compromised by use of the technology," such as a writing course.
• The Use-With-Permission Statement "makes it clear that only certain uses will be acceptable" to the instructor.
• The Abdication Statement includes an example that states, "From his point forward, I will assume that all written work has been co-authored or entirely written by ChatGPT." In this case, instructors will grade such writing "normally" and the "grade will be a reflection of your ability to harness these new technologies as you prepare for your future in a workforce that will increasingly require your proficiency with AI-assisted work."

Notre Dame's May 2023 statement is short, strongly worded, and straightforward: "When students use generative AI (such as ChatGPT) to replace the rigorous demands of and personal engagement with their coursework, it runs counter to the educational mission of the University and undermines the heart of education itself."

Director of the University of Missouri's Office of Academic Integrity Ben Trachtenberg took an FAQ-type approach to a March 2023 statement, answering questions such as

• May Students Use ChatGPT and Similar Tools for their Academic Work?
• Can Professors Tell if Students Use ChatGPT?
• What’s the Bottom Line?

Answering the last question, he indicates students should seek to uphold Mizzou's values as described in the Mizzou Honor Pledge: "If you think your instructor would object to your using ChatGPT (or a similar tool) in a certain way, you should not do it. If you are unsure, you should ask your instructor first."

Interestingly, the resource site for Royal Military College of Canada (RMC)/Canadian Forces College (CFC) focuses on syllabus policies about the low quality of detection tools: "Until formal direction is received from the Department of National Defence, it is suggested that, for privacy, ethical, and security reasons, no student, faculty, or staff should be required or expected to create or pay for personal accounts in commercial generative systems such as ChatGPT."

In Listserv conversations I have followed within Drexel and beyond, many programs and individual faculty have tried to define the way they will judge AI use in their own classrooms. In addition, members of the academic community are increasingly concerned that authors will submit AI-composed manuscripts. 

As usual, it's a good idea to ask colleagues what they are doing: Our teaching communities often contain deep wisdom, and we should continue to take collaborative, local approaches to creating sensible policies about the use of AI/ML. The material above represents just a few of these efforts.

Notes:

1) From February 9, 2023 Harvard Business Publishing Education.

Trying to keep up with natural language processing tools

Turnitin responded quickly. Faced with natural language processing tools, it deployed Turnitin's AI writing detection model. One day recently I opened Turnitin through my CMS, and there was the AI detector, ready to go.

This is likely a necessary response by the long-standing plagiarism guardian. "AI" has zoomed past cut-and-paste, and tools like Turnitin are trying to keep up.

As I've said on several occasions, I use Turnitin not so much for its plagiarism-catching talents but because it is integrated into Blackboard and has an easy-to-use commenting interface that includes the ability for a teacher to create a three-minute voice response. (I wish more teachers would use voice commenting features...)

We know its AI checker is not going to be perfect, but I had to relay this brief anecdote about just how far away it appears we are.

A sharp student in my class Language Puzzles and Word Games: Issues in Modern Grammar just submitted her second short paper.

Ah, relief: The AI checker came up 0%. (I expected nothing less, of course!)

A problem, though: Her project, in line with what we're doing in the course, was a comparison of a paper she wrote in another class and how ChatGPT would have responded to a similar prompt. In her paper, she used giant chunks of ChatGPT-generated text to illustrate grammar, usage, and style differences in her work from the natural language generator.

0%. Zero. Zilch. Nada. The AI detector didn't pick up any of it.

(The text she used was not bound by quotation marks, FYI.)

No one is expecting perfection, especially at this stage (and Turnitin includes serious qualifiers about the effectiveness of its tool), but we should remain very aware that digital watchdogs likely won't catch digital text. We have to do it ourselves.

We're in the early stages of a major shift in teaching, and we're collectively engaged with on-the-fly decisions about how we're adjusting to that change. I trust my students, but teachers will invite authorial misrepresentation if we don't develop pedagogies on the front end instead of relying on cross-our-fingers detection after the papers are in.