Student Voice, Socratic AI, and the Art of Weaving a Quote

How a custom bot helps students turn source quotes into personal insight—and share it with others

This summer, I tried something new in my fully online, asynchronous college writing course. These classes have no Zoom sessions. No in-person check-ins. Just students, Canvas, and a lot of thoughtful design behind the scenes.

One activity I created was called QuoteWeaver—a PlayLab bot that helps students do more than just insert a quote into their writing.

👉 Try it here

It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.

And it’s not all AI, all the time. I also ask students to do paper-based brainstorming using crayons and markers, snapping photos of mind maps or one-pagers to upload to Canvas. These low-tech, reflective steps complement the structured AI dialogues and help students engage through tactile, visual thinking.

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From Quoting to Thinking

We often ask students to “integrate a quote” or “unpack the meaning,” but these phrases assume a kind of inner scaffolding that many students—especially in asynchronous courses—haven’t had a chance to build. QuoteWeaver tries to change that.

The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:

• What made this quote stand out to you?

• How would you explain it in your own words?

• What assumptions or values does the author seem to hold?

• How does this quote deepen your understanding of your topic?

It doesn’t move on too quickly. In fact, it often rephrases and repeats, nudging the student to go a layer deeper. As one student put it:

“Even though sometimes it seemed like it kept asking the same question reworded over and over, it helped me come up with new thoughts and break down how to format a paragraph.”

This recursive approach helps students who might otherwise skim past a quote, plug it into their paper, and move on. Instead, they’re asked to pause, reflect, and construct meaning.

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Academic and Spoken-Word Versions

After helping the student explore the quote’s meaning and purpose, QuoteWeaver supports them in crafting two versions of a full paragraph:

• A formal academic paragraph, with signal phrase, quote, and analysis

• A spoken-word version, in their own voice, as if explaining it to a friend or podcast listener

This second version encourages rhetorical flexibility and self-awareness. Many students are surprised to find that the spoken version is the one that “feels more like them”—a reminder that their voice has value in academic spaces, too.

“The spoken-word version felt more natural for me as I was able to express my real emotion as well as making personal connections.”

By asking students to choose between versions—or combine them—this process opens a space for metacognitive reflection: What am I really trying to say, and how do I want it to sound?

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Support for Reluctant or Underprepared Students

Online students come to the work with widely varying levels of readiness. Some arrive with a quote in hand and an argument forming. Others are stuck before they begin.

QuoteWeaver is designed to adapt. If a student doesn’t have a proper source, the bot helps them trace attribution or find an alternative. If they give minimal answers (“I don’t know,” “not sure”), it shifts to scaffolded questions:

• What’s the topic of your paper?

• What is this quote basically about?

• What’s one part of the quote you do understand?

And when students are completely stuck, the bot offers choices:

• Pause and come back later with more preparation

• Practice with quote analysis only

• Work on quote-finding strategies

This approach keeps students engaged without penalizing uncertainty. In an asynchronous class—where real-time intervention isn’t possible—that flexibility matters.

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Peer Learning in Canvas

To bring this process into community, the final step is a Canvas discussion post. Students:

1. Share both paragraph versions

2. Reflect on what they learned about their topic and writing process

3. Respond to a classmate’s post with encouragement or curiosity

This turns solo reflection into collaborative meaning-making. Even in an asynchronous environment, students get to witness how their peers think through a quote, make language choices, and discover insights they didn’t expect.

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How I Built the Bot (and You Can Too)

QuoteWeaver started, like many teaching experiments, with a hunch and a few scraps of language. I knew I wanted a tool that would help students move beyond dropping a quote into their paper—and into something closer to a one-on-one conversation about why that quote mattered.

I began drafting the script in Claude.ai, outlining the core moves I make when conferencing with students. I then plugged that thinking into the PlayLab scripting template, which makes bot-building surprisingly accessible—no coding required, just clearly labeled sections written in natural language. Anyone curious about dialogue-driven teaching can start there.

But what took this iteration of QuoteWeaver to the next level was running full simulations in Gemini with the draft script. I asked for 10 student personas with varying levels of preparation, language fluency, and engagement. Watching how the bot interacted with each of them helped me surface blind spots much faster than my usual solo testing process.

These simulations helped me:

• Identify stuck points for reluctant or underprepared students

• Add support pathways for students missing a source or unsure of their quote

• Break down long interactions into shorter, mobile-friendly chunks

• Refine scaffolding for complex tasks like topic sentences and cohesion checks

• Incorporate more varied output—academic and spoken-word—that invites students to reflect on tone, audience, and authenticity

Once the core design felt sound, I moved into the PlayLab builder and tested the app as thoroughly as ever. But I was already 500 miles further down the road than I would have been. The simulations made my design sharper, more adaptive, and far more student-centered.

If you’re teaching writing—especially in an asynchronous class—and wondering how AI might support, not shortcut, the thinking process, I encourage you to explore PlayLab.

Tools don’t replace teaching. But they can extend the kinds of conversations we want students to have, especially when we’re not in the room.

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Why This Matters

In live writing classrooms, we often pause class to say, “Let’s talk about that quote.” We sit next to a student and ask, “What are you really trying to say here?” Those moments are where real writing growth happens.

In asynchronous spaces, we don’t get that moment unless we design for it.

QuoteWeaver is one attempt to recreate that moment. It’s not a shortcut or an auto-writer. It’s a slow-thinking partner. A virtual writing coach that helps students pause, reflect, and move from quoting to thinking with the quote.

If you’re curious, you can try it here:

👉 QuoteWeaver – PlayLab

Have you tried something like this in your own teaching, or want to? I’d love to hear about it.