Presenter notes outline · Afternoon
From Prompts to Possibilities: AI-Assisted Learning That Gets Students Thinking
Timothy M. Stafford, PhD · Full Professor; Program Director; Director of Graduate Online Academic Affairs; Lead Researcher and Creator of the RU Institute AI Learning Lab · St. Thomas University · 2:00–3:00 p.m. Eastern · Room 203A
Run of show
| 2:00–2:06 | Opening and theory recap | 6:00 |
| 2:06–2:20 | Four practical routines | 14:00 |
| 2:20–2:33 | Practice, adaptation, and debrief | 13:00 |
| 2:33–2:38 | Current research: CourseSpark™ | 5:00 |
| 2:38–2:45 | Three-year vision and commitment | 7:00 |
| 2:45–3:00 | Q&A (15 minutes) | 15:00 |
1. Title
0:30 · 2:00Opening and theory recap
This afternoon brings new examples, new routines, and new practice.
- Timothy M. Stafford, PhD, is from St. Thomas University in Miami Gardens.
- His STU roles include Full Professor, Program Director, and Director of Graduate Online Academic Affairs.
- He is Lead Researcher and Creator of the RU Institute AI Learning Lab.
- Returning participants will encounter different material from the morning session.
- Place the printed routine cards and the sample AI response sheet on tables before the session.
Transition: Let me start with a challenge.
2. A student hands you a flawless paragraph. What do you ask first?
1:30 · 2:00:30Opening and theory recap
When a student submits a flawless paragraph, ask a question that invites thinking and asks them to explain a decision.
- “Did you use AI?” is not necessarily wrong, but it can close the conversation by starting with suspicion.
- “Which sentence was hardest to write?” and “Why did you start here?” invite students to explain choices.
- “What would you change if your reader disagreed?” invites thinking about the reader.
- These thinking questions underpin the four routines in this session.
- Take ninety seconds to write a question, compare with a neighbor, and revise it to invite explanation rather than suspicion.
- Take two quick shares. Highlight any question that asks a student to explain a choice.
- Did you use AI? (Suspicion. Not wrong, but it closes the conversation.)
- Which sentence was hardest to write? Why did you start here? What would you change if your reader disagreed? (These invite thinking.)
Transition: Those thinking questions are what the four routines today are built on.
3. Our hour together
0:30 · 2:02Opening and theory recap
Our hour combines theory, four routines, hands-on practice, current research, and time for questions.
- The first forty-five minutes cover a short theory recap, four routines, practice, current research work, and a look ahead.
- The final fifteen minutes are reserved for questions.
- The recap stands on its own, with no morning-session background needed.
Transition: First, a standalone recap of the ideas underneath, so nobody needs the morning session.
4. AI should expand what students can think through, create, and explain.
0:30 · 2:02:30Opening and theory recap
AI should expand what students can think through, create, and explain.
- Human thinking is the target: noticing, questioning, reasoning, judging, and transferring to something new.
- If AI makes students' thinking smaller, the design is wrong.
- The aim is thinking that becomes bigger and more visible, not less necessary.
Transition: And a partnership underneath that.
5. Central theory: pedagogy and heutagogy as partners
1:00 · 2:03Opening and theory recap
Teachers design the conditions; students increasingly shape the learning.
- Pedagogy provides structure, modeling, and explanation. It stays.
- Heutagogy is self-determined learning: learners increasingly form questions, make choices, reflect, and evaluate their own learning.
- With children, these approaches are partners, not replacements for one another.
- Teachers provide boundaries and support so students take on more agency as they are ready.
Transition: Three supporting ideas, each tied to a design choice you will see in the routines.
6. Three ideas every routine uses
1:00 · 2:04Opening and theory recap
Dialogue, metacognition, and transfer each shape a concrete design choice in every routine.
- Dialogue and scaffolding: students explain and compare reasoning before accepting an AI suggestion, with support designed to fade.
- Metacognition: students monitor their thinking through a short reflection on what changed and why.
- Transfer: learning does not automatically carry into new situations, so every routine ends with a new case completed without AI.
- Full references are in the notes outline.
Transition: One distinction before the routines.
7. Established foundations and developing work
0:30 · 2:05Opening and theory recap
Established research foundations are distinct from the framework and application still under development.
- Pedagogy, heutagogy, dialogue, scaffolding, metacognition, and transfer draw on established research traditions.
- The Human Capacity/Capability Framework™ is a developing design lens, not a validated measure.
- CourseSpark™ is an application under study and an illustrative design, not a proven intervention.
Transition: And four short habits that travel with every routine.
8. Simple habits that travel with every routine
0:30 · 2:05:30Opening and theory recap
Every routine needs age-appropriate tools, privacy protection, and verification.
- For young learners, the teacher runs AI while children think, ask, and check.
- Direct student use requires institution-approved, age-appropriate tools and school guidance.
- Never put private student details into prompts. Today's examples use fictional data.
- AI can be wrong, so check trusted sources.
- Every routine also has a no-account version using printed outputs.
Transition: Here are the four routines.
9. Each one keeps the thinking with students
0:30 · 2:06Four practical routines
Each routine keeps the thinking with students.
- The four routines are question before answer; compare, challenge, justify; find and repair a flaw; and discuss, decide, reflect.
- They support inquiry, writing, problem solving, and classroom conversation.
- Each includes before, during, and after phases, a teacher prompt, student action, age adaptations, and an independent transfer check.
- Repeated practice helps students improve and take on more agency.
Transition: Routine one starts outside, on the playground.
10. Routine 1: Question before answer
1:15 · 2:06:30Four practical routines
Question before answer keeps students responsible for choosing, testing, and explaining an inquiry.
- Before: students observe playground shade, noticing where and when it appears, and write three questions each.
- During: students sort teacher-shared AI questions or ideas by whether they can test them here.
- After: students choose one question, plan a simple test, and explain their choice.
- Transfer: a week later, students independently write testable questions about a new problem, such as cafeteria noise, without AI.
Transition: What the teacher and students actually say.
11. Students sort AI questions
1:15 · 2:07:45Four practical routines
Sorting questions into testable here and not testable here is real scientific reasoning.
- The teacher writes the prompt without student names or details. The printed AI response is fictional.
- Students can compare blacktop and grass temperatures with a thermometer or mark the shadow's position each hour.
- Question 4 matters, but explaining why the climate is changing is not something students can test on a playground in a week.
- Students compare the sample questions with their own, recognizing that their questions may be better.
- Students might say: we can use a thermometer on the blacktop and the grass. Or: we could chalk where the shadow is every hour.
Transition: How does this change with age?
12. Routine 2: Compare, challenge, justify
1:15 · 2:09Four practical routines
AI suggests; students decide, and say why.
- Students first draft a paragraph and name their goal for the reader.
- They consider three AI suggestions, marking each accept, reject, or adapt.
- Students revise in their own words and justify each decision. AI never authors the final student text.
- Transfer means making and explaining revision decisions on the next piece using peer feedback alone.
Transition: A sample decision sheet.
13. Accept, reject, or adapt, with a reason
1:45 · 2:10:15Four practical routines
The reasoning column is the evidence of learning.
- The student rejects a question opening because it feels fake for the story, tying the decision to their writing goal.
- They accept “The windows hummed” as a vivid detail and adapt the statistic suggestion by adding the time the storm hit.
- Each decision requires a reason, making uncritical acceptance visible and opening a coaching opportunity.
- The same sheet supports peer collaboration: students compare reasoning rather than divide up work and copy and paste.
- Teachers may ask whether students will just accept everything. Requiring a reason for each decision makes that visible quickly, and it becomes a coaching moment.
Transition: Adapting by age.
14. Routine 3: Find and repair a flaw
1:00 · 2:12Four practical routines
Students find and repair a flaw, check by substitution, and explain the rule.
- Students solve independently first, giving them a reference point for examining someone else's solution.
- The worked error was written for this session, not presented as an actual AI output.
- Repairing the solution includes verifying the answer and naming the rule that was broken.
- Transfer means solving a new equation and checking their own answer.
Transition: Here is the flawed solution.
15. Something went wrong here. Where?
0:45 · 2:13Four practical routines
Whatever you do to one side of an equation, you must do to the other.
- The fictional solution starts with 3(x + 2) = 18, then incorrectly changes it to x + 2 = 18.
- The 3 disappears without both sides being divided by 3. Students need to explain why that step is invalid.
- The result x = 16 follows from the flawed step. Substitution gives 54, not 18, so it cannot be correct.
- Valid approaches include dividing both sides by 3 or distributing first.
- Students often notice the 3 vanished. Push them to say why that is not allowed: whatever you do to one side, you must do to the other.
Transition: Now the repair.
16. Distribute, solve, and check
1:15 · 2:13:45Four practical routines
Always check: the habit of verifying a solution transfers to checking AI output.
- Distribute: 3x + 6 = 18. Subtract 6 from both sides: 3x = 12. Divide both sides by 3: x = 4.
- An alternative is to divide both sides by 3 first: x + 2 = 6, so x = 4.
- Check by substitution: 3(4 + 2) = 18 ✓. Both solution paths give an answer that checks.
Transition: How to adapt it by age.
17. Routine 4: Discuss, decide, reflect
1:15 · 2:15Four practical routines
Students compare reasoning, agree on their own plan, and reflect on what changed.
- The fictional school has six raised beds, four interested groups, and limited water and volunteer time. There is no perfect answer.
- Students read each group's needs and rank priorities independently before considering one AI plan together.
- Groups compare reasoning rather than split up the work. Each student reflects on what changed, why, and what remains uncertain.
- Transfer means addressing a new dilemma, such as gym time, without AI and naming the tradeoff in a fair plan.
Transition: The plan they react to.
18. React to a plan, then build a better one
1:45 · 2:16:15Four practical routines
A reasonable-sounding plan can still overlook important needs and tradeoffs.
- The fictional plan gives each group one bed, assigns two extra beds to the salad program, and prioritizes watering vegetables.
- Its rationale favors feeding the most students, but it ignores pollinators' benefits to every vegetable bed and kindergartners' need for the closest bed.
- Students consider who benefits, who loses, and what the plan ignores before agreeing on their own plan with two reasons.
- Possible alternatives include a shared pollinator border or seasonal bed rotation. Each choice still requires naming what was given up.
- Groups often give pollinators a shared border instead of a full bed, or rotate beds by season. Ask them to name what they gave up.
Transition: Age adaptations.
19. Same routines, growing independence
2:00 · 2:18Four practical routines
The routines stay the same; support fades as readiness grows.
- K–2: teachers read AI ideas aloud; children think, talk, vote, and check. No accounts.
- Grades 3–5: printed AI samples, sentence frames, and paired comparisons support reasoning.
- Grades 6–12: students use approved tools within school guidance, critique AI quality, and justify choices.
- Every routine ends with a new case students handle without AI.
Transition: Now you try one, as students would.
20. Practice Routine 3 as students would
4:30 · 2:20Practice, adaptation, and debrief
Routine 3 makes reasoning visible through finding, comparing, repairing, and checking a flawed explanation.
- The fictional AI sample contains one flaw, giving students something specific to question and repair.
- Individual thinking comes before paired comparison, so each student brings reasoning to the conversation.
- The repair includes explaining how to check the answer, followed by reflection on what changed.
- Use five minutes for the practice: 1.5 minutes alone, 2.5 minutes in pairs, and 30 seconds reflecting.
- Start a visible 4 minute timer. Show the next slide for anyone without a sheet.
- Call phases: alone at 0:00, pairs at 1:30, reflect at 4:00.
- Listen for pairs who disagree; ask them to explain their reasoning to each other.
- The flaw: seasons are not mainly caused by distance from the sun. The repair: the tilt of Earth's axis changes how directly sunlight strikes each hemisphere.
Transition: Here is the sample, on screen.
21. Find the flaw in this explanation
1:00 · 2:24:30Practice, adaptation, and debrief
An AI explanation can mix a true idea with a false one.
- The flawed claim is that summer is warmer mainly because Earth is closer to the sun.
- Northern Hemisphere summer occurs when Earth is near its farthest point from the sun.
- Axial tilt changes how directly sunlight strikes each hemisphere. The sample's third sentence partly captures this.
- A science text or NASA education materials can help students check the explanation before rewriting it.
Transition: Let us debrief.
22. Adapt one routine to your grade and subject
4:00 · 2:25:30Practice, adaptation, and debrief
A classroom adaptation connects the teacher prompt, student action, reasoning evidence, and an independent transfer check.
- The routine should fit a lesson coming soon, with fictional details only in the teacher prompt.
- The student action should make clear where students make a decision and what reasoning they demonstrate.
- The transfer check asks students to handle a new case without AI.
- Use four minutes to draft one adaptation; administrators can plan coaching, observation, and support instead.
- Show the administrator slide for about 30 seconds within this block, then return.
- Circulate. Ask: where is the student's decision? What will you see them do?
- Most choose Routine 3 or 1. Encourage someone to try Routine 4 for advisory or social studies.
Transition: Administrators, your parallel path.
23. Coach and support one routine
0:30 · 2:29:30Practice, adaptation, and debrief
Review student reasoning together, not just AI usage counts.
- A team can begin with one routine to try for three weeks.
- Shared look-fors are students questioning, justifying, checking, and transferring.
- Protected planning time and approved tools or printed samples support teachers.
- Usage counts tell you about access. Reviewing reasoning samples in PLCs keeps attention on learning.
Transition: Two design details that make or break these routines.
24. Compare reasoning. Don't divide and paste.
1:30 · 2:30Practice, adaptation, and debrief
Compare reasoning. Don't divide and paste.
- Divided work can produce a combined product without anyone comparing thinking.
- Individual thinking comes first, so partners have ideas to compare and challenge.
- The group then makes a shared decision and explains why.
- The distinction matters especially with AI: pasted parts are not evidence of shared reasoning.
Transition: And reflection that actually means something.
25. Three questions worth asking every time
1:30 · 2:31:30Practice, adaptation, and debrief
Meaningful reflection asks what changed, why it changed, and what remains uncertain.
- Change can be in an answer, a plan, or the student's thinking.
- Naming the evidence or argument that changed a view makes reflection specific.
- Identifying uncertainty points toward what students need to find out next.
- These questions make metacognition routine from second through twelfth grade and support increasingly self-directed learning.
Transition: Now to our current work in this space.
26. Questions we are investigating
1:00 · 2:33Current research: CourseSpark™
These are research aims and questions, not results.
- Visible reasoning: does AI-assisted dialogue make student thinking easier to see?
- Agency and judgment: do students make and defend more decisions?
- Transfer: do routines carry into work without the tool?
- Teacher support: how much guidance is needed, and when?
- Do not mention findings, participant numbers, effect sizes, or pilot details. They are not verified for sharing.
Transition: One illustrative application is CourseSpark.
27. How the design tries to put these ideas to work
1:15 · 2:34Current research: CourseSpark™
CourseSpark’s design tries to put learning theory into practice, but design intent is not proof.
- Socratic dialogue draws on dialogic learning: the tool asks questions rather than supplies answers.
- Justify prompts ask, “Why do you think that?” to make reasoning visible.
- Reconsider prompts ask, “What might change your mind?” to invite students to check their own thinking.
- Transcripts let teachers review thinking and decide what support to offer next or fade.
- Reflection asks what changed and remains uncertain, connecting to self-regulation; whether it supports transfer is a research question.
Transition: Here is one illustrative walkthrough.
28. One illustrative walkthrough
1:45 · 2:35:15Current research: CourseSpark™
The illustrative transcript shows a student’s idea of fairness developing from equal shares toward different needs.
- “What makes that fair?” asks the student to justify equal shares.
- The salad program’s greater reach introduces new information and invites reconsideration.
- The student considers needs-based fairness while keeping one bed for pollinators, retaining a reason of their own.
- A teacher could review this development and decide whether to challenge further or step back.
- This is a written illustration, not student data or a live demonstration; mentioning CourseSpark does not imply St. Thomas University ownership or endorsement.
Transition: Being clear about what we know.
29. Asking, not claiming
1:00 · 2:37Current research: CourseSpark™
This work asks research questions rather than claims established results.
- No findings, K–12 approval, or live integration in your school are being claimed.
- What reasoning becomes visible, and where are teachers most needed?
- What evidence would show that students transfer their learning?
Transition: A brief look ahead.
30. Building capability over time
1:30 · 2:38Three-year vision and commitment
Building capability over three years is an aspiration, not a forecast.
- Year 1: try routines safely and on a small scale, and gather baselines.
- Year 2: teams refine routines and examine student reasoning together.
- Year 3: look for students questioning, judging, and transferring learning independently.
- Observations, reasoning samples, independent work, reflections, and workload notes help reveal change, but do not alone prove AI caused it.
Transition: Which brings us to next week.
31. What we hope each group can do by Year 3
1:30 · 2:39:30Three-year vision and commitment
The Year 3 aspiration is greater student independence, responsive teaching, and administrative support that makes the work sustainable.
- Students ask better questions, evaluate AI suggestions, justify choices, transfer learning, and work more independently.
- The hoped-for student growth connects questioning and choosing, explaining, judging and reflecting, and using learning somewhere new.
- Teachers design responsive challenges and interpret student thinking, with workload kept manageable.
- Administrators support teacher capacity, equitable access, and approved, age-appropriate tools.
- Quality should be judged through reasoning samples and observations, not usage counts alone.
Transition: And how would we know whether any of this is happening?
32. What we would look at, and what it cannot prove alone
1:00 · 2:41Three-year vision and commitment
Classroom evidence can show patterns worth discussing, but cannot alone prove that AI caused a change.
- Classroom observations, student reasoning samples, and independent work offer practical evidence schools can gather without new systems.
- Student reflections and teacher workload notes add perspectives on learning and sustainability.
- Year 1 baselines give later evidence something to be compared with.
- Many things change during a school year, so patterns should not be mistaken for proof of causality.
Transition: Which brings it back to one small step.
33. Next week, I will run one routine with one class and collect one piece of reasoning.
1:15 · 2:42Three-year vision and commitment
Next week, I will run one routine with one class and collect one piece of reasoning.
- The commitment stays small and specific: one routine, one class, one piece of reasoning.
- Take 45 seconds to write the routine, class, and evidence on your card.
Transition: One last thought.
34. Teachers design the conditions; students increasingly shape the learning.
1:15 · 2:43:15Three-year vision and commitment
Teachers design the conditions; students increasingly shape the learning.
- AI should expand what students can think through, create, and explain.
- Teacher design and increasing student agency belong together.
Transition: Your questions.
35. Join the RU Institute AI Learning Lab
0:30 · 2:44:30Three-year vision and commitment
Keep learning together through the RU Institute AI Learning Lab.
- The seven-day free trial lets you take a course, connect with colleagues, and explore the community.
- See whether the community adds value to your ongoing professional practice.
- Scan the QR code to join on Skool.
- Leave the code up for about 20 seconds so phones can scan it.
Transition: Now, your questions.
36. Questions and conversation
14:30 · 2:45Q&A (15 minutes)
Choose a routine that fits your students, then consider barriers and the support you need.
- Every routine works with printed samples, so devices are not required.
- Assess the reasoning column, reflection, and transfer check, not just the final product.
- For very young students, use AI only through teacher mediation: children think, talk, and check.
- Heutagogy partners with pedagogy in K–12; references are in the notes outline.
- Keep answers to about two minutes. Invite longer conversations to the STU vendor space.
- If questions slow, use the prompts on screen, or invite people to share the routine they chose.
- At 2:59:30, move to the closing slide.
- No devices: every routine works with printed samples.
- Grading: assess the reasoning column, reflection, and transfer check, not just the final product.
- Very young students: teacher-mediated use only; children think, talk, and check.
- Theory: heutagogy partners with pedagogy in K–12; references are in the notes outline.
Transition: Thank you.
37. Closing and STU booth invitation
0:30 · 2:59:30Q&A (15 minutes)
Continue the conversation and follow up for the routine cards.
- Thank you for spending your afternoon thinking with me.
- Visit the STU vendor space for further conversation.
- Email tstafford@stu.edu for follow-up and the routine cards.
Verified references
- Alexander, R. J. (2008). Towards dialogic teaching: Rethinking classroom talk (4th ed.). Dialogos.
- Blaschke, L. M. (2012). Heutagogy and lifelong learning: A review of heutagogical practice and self-determined learning. The International Review of Research in Open and Distributed Learning, 13(1), 56–71. https://doi.org/10.19173/irrodl.v13i1.1076
- Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906–911. https://doi.org/10.1037/0003-066X.34.10.906
- Hase, S., & Kenyon, C. (2000). From andragogy to heutagogy. UltiBASE. RMIT University.
- Perkins, D. N., & Salomon, G. (1992). Transfer of learning. In T. Husén & T. N. Postlethwaite (Eds.), International encyclopedia of education (2nd ed.). Pergamon Press.
- Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press.
- Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17(2), 89–100. https://doi.org/10.1111/j.1469-7610.1976.tb00381.x
- Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2
- U.S. Department of Education, Office of Educational Technology. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations. https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf
Presenter note: CourseSpark™ and the Human Capability Framework™ are described as a research context and a design lens. No findings are reported. All classroom data, sources, and AI responses in the decks are fictional samples.