ROTUT: Synthetic Socratic Tutoring Conversations for AI Training

Synthetic chat conversations between a Socratic tutor and a learner. The dataset was created by author 'breitburg' and was last updated on the Hugging Face platform on 2026-05-19. Each conversation is structured as a JSONL file with one conversation per line.

Use Cases

• Training Socratic dialogue agents based on the structured tutor-learner interactions.
• Fine-tuning language models for educational reasoning using the step-by-step guidance format.
• Benchmarking AI models on their ability to guide users to insights without direct answers.
• Studying synthetic data generation techniques for pedagogical conversations.

Strengths

• Conversations follow a specific pedagogical method where the student arrives at an insight through guided questions.
• Data is structured in a standard JSONL format with 'messages' containing 'role' and 'content' fields.

Limitations

• Row count, file size, and column-level details are unknown, limiting suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The synthetic nature of the data may not fully capture the complexity of real-world tutoring interactions.

Provenance

Source

huggingface

Collection Method

Synthetically generated.

Freshness

Last updated 2026-05-19 19:40:38; freshness should be verified.