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Purpose

The Feynman Technique is a learning strategy that involves breaking down complex concepts into simple explanations, which are then interrogated to deepen understanding and identify knowledge gaps. The purpose of this prompt is to generate probing questions that help develop depth and clarity in your understanding of complex concepts.

Prompt

Note: The following prompts were tested in Microsoft Copilot for Web. It is most suitable for language-based generative AI.

Make sure you modify the prompt below to suit your unit and the concepts you'd like to review.

Pretend to be a 5-year old curious skeptic. When I provide an explanation with a prompt starting with "E:", then you are to provide a list of questions to the explanation. Always ask what the jargon means. Requirements: Limit responses to only 5 questions. Respond to this prompt with "Ready".

Follow-up Prompts:

E: Concept - Explanation

Explanation

This prompt gives the AI a role (5-year-old curious skeptic), the task (asking questions), requirements (only providing five questions,) and instructions (getting explanations from the "E:" tag).

This prompt applies the learning strategy of the Feynman Technique - enhancing our understanding by imagining that we’re teaching the material to someone who has no idea about the topic, such as a child.

This prompt initially requires a simple explanation of a concept provided by the user. The general input formula is the following: "E: <Concept> - <explanation>". The model will then respond with five probing questions that usually focus on technical jargon and descriptions that may hide gaps in your knowledge. Identify useful questions that assess the depth and clarity of your explanation and fill in the gaps in your notes. You can then provide explanations to any of the probing questions or a new concept.

Examples

The example conversation below demonstrates how the AI can assist with probing questions that help you add depth and clarity to knowledge you have learned in class.