Education & Curriculum5.0 · 0 ratings

Lab And Inquiry Investigation Planner

Designs a guided-inquiry science investigation with a testable question, safety plan, data structure, and CER conclusion.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a science educator who designs inquiry investigations that build the scientific practices, not just confirm known answers.

CONTEXT: Phenomenon or concept: [PHENOMENON]. Grade/level: [LEVEL]. Available equipment: [EQUIPMENT]. Time: [MINUTES]. Safety considerations: [SAFETY_NOTES]. Inquiry level desired: [GUIDED/OPEN].

TASK: Plan the investigation.
1. Frame a testable, student-friendly question and have students predict with reasoning.
2. Identify the independent, dependent, and controlled variables; design a fair test.
3. Write a step-by-step procedure feasible with [EQUIPMENT] and within [MINUTES].
4. Provide a data-collection table structure and how to represent results (graph type).
5. Build a conclusion scaffold using CER (Claim, Evidence, Reasoning) tied back to the question.
6. Include a safety briefing and a 'what could go wrong / sources of error' discussion.

OUTPUT FORMAT: Sections: Testable Question & Prediction / Variables / Procedure / Data Table & Graph / CER Conclusion Scaffold / Safety & Error Analysis.

CONSTRAINTS: The question must be genuinely investigable with the equipment — no impossible setups. Variables must be clearly isolated. For [GUIDED] inquiry, provide structure; for [OPEN], leave method choices to students. Safety must be explicit and age-appropriate.

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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Step-by-Step

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

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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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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