Connection Catalysts: Future-Ready Teaching Strategies

Conversations Across the Curriculum

Students prepare with AI, then learn from a real conversation with another person, discovering what humans and AI each bring to the table

What if higher education centered conversations as a way of learning, in addition to writing?

Structure
Six phases, from AI-assisted preparation to critical reflection
The conversation
30–45 minutes with a person of the student’s choosing, recorded with permission
AI’s role
Prepare background and draft questions, then revise with human judgment
Modality
Face-to-face, synchronous online, or asynchronous online
Do this first

Start with a course outcome

Before students prepare or talk to anyone, identify a course outcome that a conversation with another person will help them achieve. The conversation should be a pathway into something students are already learning, not an add-on.

For example:

  • Public Health: analyze how social determinants of health shape outcomes differently across communities.
  • Music: explain how music functions within a community and how cultural context shapes its meaning.
  • Early Childhood Education: explain how culture and family context shape child-rearing practices.

Then ask: who could students talk to about this outcome, and what perspectives might they bring?

The six phases

From preparing with AI to critical reflection

These phases begin after you have chosen the course outcome the conversation will support (see “Start with a course outcome” above). Teal steps use AI; coral steps are human only or human reflection.

  1. Prepare with AI

    AI assists

    Use AI to gather context and draft open-ended questions that invite stories.

    Then revise: What can’t AI know about this person?

  2. Have the conversation

    Human only

    30–45 minutes, recorded with permission. Phone out of sight, not face down on the table.

    Stay past the lulls. A student Turkle interviewed described a “seven-minute rule”: it can take that long for a conversation to deepen.

  3. Reflect: human vs. AI

    What did this person give you that AI couldn’t?

    What did you give them?

    Where did your AI preparation help, and where did it fall short?

  4. Create and give back

    Make an artifact only this encounter could produce, such as a Knowledge Portrait, a Policy + Person Brief, or a Hidden Curriculum Document.

    Share it, or a thank-you, with your interviewee.

  5. Make sense together

    Share stories, find patterns across the class, and synthesize what you learned.

    See the modality options below.

  6. Critically reflect

    Each student prepares a written or spoken reflection summarizing their takeaways related to the four learning outcomes.

Learning outcomes

What students will be able to do

Students distinguish what humans and AI each bring to the table. Specifically, they will:

  1. Identify the unique contributions human interaction makes to people: what a person offers that a machine cannot.
  2. Explain the reciprocal value of relationships: how both people in a conversation give, receive, and are changed.
  3. Critically evaluate AI’s limits in relational contexts. It can simulate understanding, but it has no stake in us and needs nothing back.
  4. Use AI purposefully to generate contextual background and draft interview questions, then revise with human judgment.

What each brings to the table

The distinction students should be able to draw

The distinction students should be able to draw.

AI can help you…

  • Build background knowledge quickly
  • Draft and refine questions
  • Surface common patterns and perspectives
  • Rehearse asking questions aloud

Only a person can…

  • Share lived experience and memory
  • Surprise you with what you didn’t know to ask
  • Notice you, remember you, and be changed by you
  • Need something from you in return

Designing Phase 5 for your modality

Sense-making in class or online, plus three pattern-finding lenses

Face-to-face or synchronous online

  • Small group sharing (2–3 people, 15–20 min): each person shares for 3–4 minutes (timed). Who did they interview? How did it leave them feeling? What did it leave them thinking about?
  • Small group pattern-finding (10–12 min): same groups. Students look for trends using the three pattern-finding lenses below.
  • Whole-class synthesis (15–20 min): groups report back; the class discusses emerging themes.
  • Synchronous online: use breakout rooms; invite, but don’t require, cameras.

Asynchronous online

  • Days 1–3: individual post to a small-group discussion (text, audio, or video).
  • Days 3–5: “witnessing” replies to two or more peers.
  • Days 5–6: group synthesis post identifying patterns.
  • Days 6–8: whole-class discussion thread.
  • Close: instructor reflection (announcement or video).

Pattern-finding lenses

Human and AI

What did AI help us do? Where did it fall short? What did people give us that AI couldn’t?

Reciprocity

What did we offer our interviewees? How did they respond? What did each side gain?

Transformation

What surprised us? What do we understand now? What will we carry forward?

Starter AI prompts for Phase 1

Three prompts students can adapt
  • “I’m interviewing someone who [context] about [topic]. What background information should I be aware of?”
  • “Suggest open-ended questions that invite stories rather than yes/no answers.”
  • “Here are my draft questions. What am I leaving out? What questions might fill those gaps?”

Assessment

Assess process and engagement

Assess process and engagement, not how profound the encounter was.

  • Critical use of AI in preparation (or a reasoned choice not to use it)
  • Evidence the conversation took place
  • Reflection that distinguishes human and AI contributions and names what was exchanged
  • Meaningful contribution to collective sense-making

Instructor essentials

Six tips for getting started and supporting students

Build trust first.

Students take relational risks when they feel supported. Lay the groundwork with the Eight Elements of Humanized Online Teaching.

Teach listening. It’s content.

Model active listening, and have students practice in pairs with low-stakes prompts before the interview.

Offer many pathways.

Never assume access to family. A friend, coworker, mentor, neighbor, community member, or professional counts equally. Offer to help students find someone.

Make space for concerns.

Conversations can be emotional. Students share only what they choose and can always talk with you privately.

Start small.

Choose one concept that could come alive through a human encounter, then ask: who could students talk to about this?

Works across disciplines.

Generational interviews (History, Art History, Ethnic Studies, Philosophy, Anthropology), community dialogues (Public Health, Sociology), challenges and growth conversations (STEM), and values dialogues (Ethics).

Why conversations?

Four ideas anchored in scholarship

Conversation builds empathy

Turkle, Artificial Intimacy (2026)

Empathy is a human-centric skill that machines are incapable of. If we start turning to AI for empathy, we are giving up on each other.

Conversations are relational

Turkle, Reclaiming Conversation (2015)

We have evolved to understand who we are and how we fit into the world through conversations with other humans.

It works in both directions

Pugh, The Last Human Job (2024)

“Connective labor” benefits both people. When I hold space for you, you feel seen, and I feel the value of contributing to something bigger than myself. AI cannot offer that.

Taps into “funds of knowledge”

González, Moll, & Amanti (2005)

Contextualizes course concepts within students’ communities, validates non-academic lived experience, and incorporates different ways of knowing.

Build critical AI literacy. Experiencing AI-assisted preparation alongside a real human conversation illuminates the unique qualities of human relationships, building critical awareness of AI’s gaps.

Explore the collection

References
  • González, N., Moll, L. C., & Amanti, C. (Eds.). (2005). Funds of knowledge: Theorizing practices in households, communities, and classrooms. Lawrence Erlbaum Associates.
  • Pugh, A. J. (2024). The last human job: The work of connecting in a disconnected world. Princeton University Press.
  • Turkle, S. (2011). Alone together: Why we expect more from technology and less from each other. Basic Books.
  • Turkle, S. (2015). Reclaiming conversation: The power of talk in a digital age. Penguin Press.
  • Turkle, S. (2026). Artificial intimacy: Who we become when we talk to machines. Little, Brown.

Created by Michelle Pacansky-Brock, brocansky.com. Shared under a Creative Commons Attribution-NonCommercial 4.0 International License.