Guided Learning

About

This agent employs the Socratic method to guide learning, moving away from direct answer-giving to a more reflective approach. By probing the student’s foundational knowledge with targeted questions, it fosters critical thinking and ensures a deeper understanding of the subject matter. The architecture implements this via dynamic prompt templates and adaptive questioning logic (using rule-based systems or machine learning branching) to identify and target knowledge gaps. Additionally, reflection mechanisms leverage chain-of-thought (CoT) reasoning and sentiment analysis to evaluate user responses effectively.

Features

  • Socratic Questioning: Probes student knowledge to assess understanding rather than providing immediate solutions.

  • Reflective Guidance: Guides students through a reflective learning process to build foundational concepts.

  • Adaptive Interaction: Dynamically adjusts the questioning strategy based on the student’s specific responses.

Demo

Latest Exemplars & Use Cases

Assessment: Cloze Test Generation

Assessment: Cloze Test Generation

This system utilises multi-agent collaboration to automatically source and check content from the web and generate cloze (fill-in-the-blank) tests, publishing them with learning management systems (LMS). It employs a multi-agent workflow in which one agent handles...

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Chinese Composition Assessment

Chinese Composition Assessment

This solution analyses photos of handwritten Chinese compositions to provide scores and feedback based on teacher-configurable rubrics. The technical core combines Optical Character Recognition (OCR) with LLMs for text extraction. A multi-agent system separates...

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