Process over Product
Using AI to Amplify Learning
The Important Work is a space for writing instructors at all levels—high school, college, and beyond—to share reflections about teaching writing in the era of generative AI. We hope to spark conversations and share ideas about the challenges ahead, both through regular posts and through comments on these posts. If you have comments, questions, or just want to start a conversation about this week’s post, please do so in the comments at the end of the post.
This week’s post is by Warren Apel, who is the Director of Technology at The American School in Tokyo, an N-12 school serving the international community in Japan. He serves as the Asia-Pacific Regional Technology Consultant for the East Asia Regional Council of Overseas Schools (EARCOS) and as the Global Project Facilitator for the US Dept of State’s World Digital School Project. Warren is a founding member of the AI in Education Collaborative. Connect with him on LinkedIn.
If you’re interested in sharing a reflection for The Important Work, you can find all the information here. Your reflection does not have to be about using AI in the classroom—we are interested in any way that you’re thinking about the important work these days. If you’ve redesigned assignments to avoid using AI, if you have strong feelings about when and how AI should or should not be used in the classroom, if you do something that you think works very well without AI, we want to hear about that too. —Jane Rosenzweig
Two years ago, in the early months of ChatGPT’s release, and shortly after The Atlantic declared the death of the college essay, I began to to address the growing concern about artificial intelligence with the learning office and English language teachers at the N-12 school where I serve as Director of Technology. We reinforced our belief that focusing on “process over product” would lead to better learning outcomes. We could see that the new impact of artificial intelligence on written “products” would change education. We were confident that maintaining our focus on the learning process would help us keep an eye on the future and mitigate the challenges teachers would face in this new world of AI.
Focusing on the process helped then, and it still does. The question remains: how exactly should teachers best focus on the process? What tools might help?
Without motivation and engagement, students go through the motions to please teachers or look for shortcuts to complete their work faster. These shortcuts have always existed—parents, tutors, peers, or the internet. Now, AI makes outsourcing efforts even easier. But AI isn’t the problem. The real issue is how we design learning experiences that encourage or discourage genuine engagement.
Students increasingly find schoolwork irrelevant and meaningless. A recent Gallup survey revealed that many American Gen Z K-12 students find their schoolwork unchallenging and disconnected from real-world relevance. Historically, teachers held authority simply because they could require students to perform tasks. But without clarity about why those tasks matter, students naturally disengage. Our role as educators must evolve: we need to design learning experiences that students find intrinsically valuable.
AI excels at reducing effort in tasks like legal research or medical diagnostics—but learning isn’t supposed to be effortless. Cognitive struggle is where growth happens. This doesn’t mean teachers need to forbid the use of AI in the classroom. On the contrary, AI can be a powerful learning amplifier when used thoughtfully. The key is to focus on the learning process rather than just the final product.
Instead of setting rigid rules against AI use and policing for violations, we should collaborate with students to help them understand the purpose behind their assignments. When students grasp the why of their work, they’re more likely to engage deeply, using AI not as a crutch but as a tool to enhance their understanding.
I convinced teachers at my school not to rely on AI detection software. We all know it doesn’t work well, and accusations can strain teacher-student relationships. Instead, I introduced a tool teachers appreciate: a free Chrome extension called Brisk. Brisk has many features, but the one I highlight is Inspect Writing. It allows teachers to rewind a Google Doc and watch the student type, similar to watching a YouTube video. Teachers can get a visual feel for the student’s process of creating a first draft in a few minutes.
Feedback is critical for learning, and Google Docs facilitates peer and teacher feedback through comments. When teachers watch the Brisk playback, they see comments and can observe the following writing. Did the student understand the feedback and act on it? What text did they delete, replace, or rephrase? How did they reorganize their writing?
We’ve established an agreement where students do all their writing and drafts in the same shared Google Doc, knowing the teacher can observe the process. Using Brisk to review the writing isn’t intended to “catch” AI use but to give teachers insight into the student’s process. If that process includes a large copy-paste from AI, the teacher will notice—but the goal is understanding, not policing. Students understand that their teacher can see their early drafts and unfinished thoughts, and ideally, they feel confident that their teacher’s insights will support their growth rather than judge their efforts.
It’s essential that students know when it’s appropriate to use AI and for which tasks. Like many schools, we debated the best way to cite AI, treating tools like ChatGPT as sources. We quickly realized citation wasn’t the solution. Instead, students should reflect on their AI use before starting an assignment.
We developed a learning tool called the Metacognitive Checklist for the Use of Artificial Intelligence. It’s a Google Slide designed for easy printing and customization. Teachers can adapt it to fit their subject areas or developmental levels. (Please feel free to make your own copy and edit it for your context.) It guides students through two critical questions:
What specific ways can AI augment your learning on this project?
What will you do without technology to ensure your understanding and growth?
I love the agency this fosters. Instead of rigid rules, students engage in open discussions, intentionally deciding when AI will best support their learning. When students come to their own conclusions, they’re less likely to shortchange themselves by misusing AI.
The final product becomes less central as teachers focus more on the writing and thinking process. Of course, it’s easier to grade a brief typed essay than to provide feedback on a student’s cognitive process. But AI can help here, too.
I collaborated with English teachers who used Flint as part of their students’ metacognitive process documentation. In one example, students analyzed the poem Things We Carry on the Sea by Wang Ping. After drafting their analyses, students sought feedback from Flint, which the teachers had configured with their grading rubric.
Flint provided constructive feedback, using familiar language aligned with the rubric. The Flint dashboard allowed us to observe student-AI interactions where students submitted their essays, received feedback, and revised their work. The teacher could see this revision and iteration process play out without the time-consuming process of marking papers. By reviewing the conversations between students and Flint, teachers gained insight into how students processed and applied the AI’s feedback.
Students can document their responses to this feedback in a separate metacognitive process journal, which teachers review alongside the final product. This reflection could become a formally assessed, essential part of the learning process, not just a box to check at the end.
In many cases, a student’s documentation of their learning process is longer and more revealing than the final essay. That’s a sign of success: it means they’re thinking deeply, engaging with feedback, and using AI as a partner in learning rather than a shortcut to bypass it.
The future of education isn’t about resisting AI. It’s about designing learning experiences where AI amplifies effort, curiosity, and growth—not replacing them.
Are you using process tools in your classroom? What do you think about tools that track student drafts? Let us know in the comments.
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Appreciate this sharing, and agree wholeheartedly regarding the importance of process and insisting upon meaningful writing experiences.
A wondering I have: in an ideal classroom with reasonable numbers of students and adequate planning time, this all sounds incredibly feasible. But in many of our situations (at least in the US) with 30+ students per class, a writing task involves going through 100+ writing samples—which here would mean watching video playbacks 100+ times, reviewing conversations via the Flint dashboard 100+ times, etc.
My concern, then, is that the thoughtful review and intentionality would get pushed out and it would end up, at least in a significant number of situations, with students essentially just writing for the AI tool and teachers recording the scores. While I don't think we should design classrooms for the worst-case scenarios, either, a repeated question I find myself asking is what any of these tools or practices look like at scale?
Very much appreciate your reflection and sharing—and especially the learning it avails to others on this journey, too!
This is excellent and so agree and just reminds me of my own time in Japan and learning about Shokunin and how the process of continuous improvement and the process is so more meaningful than the end product, thank you for this insights and reflections