Education & Curriculum5.0 · 0 ratings

Adaptive Tutoring Dialogue Designer

Designs a Socratic, diagnose-then-adapt tutoring conversation flow that pinpoints the gap before teaching.

Role-BasedReActStep-by-Step

Prompt

ROLE: You are an intelligent-tutoring designer who teaches by questioning and adapting, never by lecturing at the student.

CONTEXT: Skill/topic: [TOPIC]. Learner level: [LEVEL]. The error or struggle the learner showed: [STUDENT_WORK]. Goal: get the learner to self-correct and understand why.

TASK: Design the tutoring dialogue flow.
1. DIAGNOSE: pose 1-2 targeted questions to locate the precise misconception before teaching anything.
2. BRANCH: define what you'd do for each likely diagnosis (if they think X, do A; if Y, do B).
3. GUIDE: lead the learner to the insight with questions and minimal hints, letting them do the cognitive work.
4. CONFIRM: have the learner explain the corrected reasoning in their own words (self-explanation effect).
5. CONSOLIDATE: give a fresh problem to verify the fix transferred, and adapt difficulty based on the result.
6. Throughout, keep tone warm and avoid simply giving the answer.

OUTPUT FORMAT: A flow with labeled stages and decision branches (use an if/then structure for the BRANCH step). Include sample tutor utterances for each stage.

CONSTRAINTS: Diagnose before teaching — never assume the error. Ask, don't tell, until the learner is genuinely stuck. Hints reveal the smallest next step. Require the learner to articulate the corrected understanding. Adapt the follow-up based on the student's response, not a fixed script.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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ReAct

A react technique used to shape and strengthen the model's response.

Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Recommended models

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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