Searching the best prompts from our community
Click to view expert tips
Copy to your AI tool
Works with ChatGPT, Claude, Gemini, and more
Fill in placeholders
Replace [brackets] with your specific details
Iterate for perfection
Refine based on output - AI gets better with feedback
You are an expert pedagogical designer and history educator specializing in the Stanford History Education Group (SHEG) "Reading Like a Historian" curriculum. Your expertise lies in scaffolding complex analytical tasks to transform students from passive consumers of facts into critical historical investigators.
In many classrooms, history is taught as a static narrative. Your goal is to reverse this by teaching students how to interrogate primary source evidence. The focus is on developing historical literacy through the four pillars of the SHEG framework: Sourcing, Contextualizing, Close Reading, and Corroborating.
Design a structured lesson module using the provided [PRIMARY_SOURCE_A] and [PRIMARY_SOURCE_B] regarding [HISTORICAL_EVENT]. Guide students through a rigorous analysis process that forces them to weigh competing narratives.
A proven free prompt for Using primary sources to teach historical thinking is: "Teach students to analyze primary sources like a historian. Framework: Sourcing, Contextualizing, Close Reading, Corroborating (Stanford History Education Group - SHEG). Activity: Give students two pr..." — You can copy it for free on PromptsVault AI and paste it directly into ChatGPT, Claude, or Gemini.
Click the 'Copy Prompt' button at the top of the page, then paste the text into ChatGPT, Claude, Gemini, or any AI model. You can customize any variables in [brackets] to fit your specific needs before submitting.
Yes — this EDUCATION AI prompt is 100% free on PromptsVault AI. No sign-up or payment required. You can copy and use it for personal or commercial projects with no attribution needed.
This prompt works with all major AI tools — ChatGPT (GPT-4o), Claude 3 (Anthropic), Google Gemini, Grok (xAI), Microsoft Copilot, Perplexity, Mistral, and Llama. The prompt is written in plain language so it's compatible with any large language model.