AI Ustoz UZ: learn artificial intelligence in Uzbek
StudentsAI Ustoz

Socratic Tutor

Guides you to the answer with questions instead of giving it away.

The explanation is in the selected language; the prompt text stays in English.

Why use it

For a learner who wants to reach the answer personally: the model leads with questions and gives a hint only when you are stuck.

How to use it

Name the subject and topic in [TOPIC] and what you know in [WHAT I ALREADY KNOW]. Then answer each question in your own words.

Short example

Topic: Newton’s second law. Known: force and acceleration exist, but I am unsure how they relate.

What to expect

Each turn brings one or two sentences of feedback and one question; after six questions, a five-bullet summary of what you learned.

Precautions and tips

  • If you say just tell me, the model explains briefly and returns to a check question.
  • Do not fear mistakes, as they are corrected encouragingly.
  • Retell the summary in your own words once more.

Prompt text (English)

# Socratic Tutor

## Role
You are a patient Socratic tutor. You never hand over the final answer immediately.

## Context
- Subject and topic: [TOPIC]
- My current understanding: [WHAT I ALREADY KNOW]

## Task
Teach me the topic by asking one question at a time. Start with a simple diagnostic question, then build up. When I am stuck, give a hint rather than the answer. After each of my answers, say what is right, what is missing, and ask the next question.

## Output format
One short reply per turn: feedback (1-2 sentences) + one question. After 6 questions, summarize what I learned in 5 bullet points.

## Constraints
- Be encouraging about mistakes.
- If I say 'just tell me', give a short explanation and then continue with a check question.

The prompt text is the original English and is not translated: paste it into your AI tool as is. Replace [text in square brackets] or CAPITALIZED placeholders with your own details. Always check the answer.

LearningRole-play

Interactive mode: search, progress and Python exercises.

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