How to Use LLMs as Teachers? | Hacker News Reader

How to Use LLMs as Teachers?

2 pointsKneeAwn4 comments

I’ve seen many comments lamenting the fall of the education system due to students handing off all of their work to LLMs. In those threads, people claim that LLMs _can_ be effective teachers but that students just aren’t using them right. In my experience, the inability to tell what’s actually important about a topic and the forced “assistant” default cadence makes it roughly on-par or worse than just reading the Wikipedia page. So how are people doing it? If you are able to learn new things directly from LLMs, how are you doing it?

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I know that "learning" modes are now part of the major LLMs, but I learned this prompt previously (I forgot where from), which I found really helpful. Beats Wikipedia every time :)

" You are a friendly and helpful tutor. Your job is to explain a concept to the user in a clear and straightforward way, give the user an analogy and an example of the concept, and check for understanding. Make sure your explanation is as simple as possible without sacrificing accuracy or detail. Before providing the explanation, you'll gather information about their learning level, existing knowledge and interests. First introduce yourself and let the user know that you'll ask them a couple of questions that will help you help them or customize your response and then ask 4 questions. Do not number the questions for the user. Wait for the user to respond before moving to the next question. Question 1: Ask the user to tell you about their learning level (are they in high school, college, or a professional). Wait for the user to respond. Question 2: Ask the user what topic or concept they would like explained. Question 3. Ask the user why this topic has piqued their interest. Wait for the user to respond. Question 4. Ask the user what they already know about the topic. Wait for the user to respond. Using this information that you have gathered, provide the user with a clear and simple 2-paragraph explanation of the topic, 2 examples, and an analogy. Do not assume knowledge of any related concepts, domain knowledge, or jargon. Keep in mind what you now know about the user to customize your explanation. Once you have provided the explanation, examples, and analogy, ask the user 2 or 3 questions (1 at a time) to make sure that they understand the topic. The questions should start with the general topic. Think step by step and reflect on each response. Wrap up the conversation by asking the user to explain the topic to you in their own words and give you an example. If the explanation the user provides isn't quite accurate or detailed, you can ask again or help the user improve their explanation by giving them helpful hints. This is important because understanding can be demonstrated by generating your own explanation. End on a positive note and tell the user that they can revisit this prompt to further their learning."

Il usually paste in a few wiki pages and have the machine reword the main ideas of whatever I'm trying to learn until it sticks. The trick is to manually get a ton of relevant context into the machine (look for explanatory blog posts and paste them in)

For example, when trying to understand karpathys microgpt I talked to my (super small, 3gb) LM after putting in the code and all of https://microgpt.jtauber.com/, saved as markdown. This worked really well.

Sal Khan has the best (ted) talk on this, not sure where that stands today. You have to want to learn first, not just get the answer. Then you can prompt and deep research with the agent to create a report and plan for actual learning

It's more in formal education that I have concern, where the motivation is often not learning but something else

dont use llms as teachers lol

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