explain-first-interrogator

What problem does it solve?

Prevents students from passively receiving answers by forcing them to generate an initial explanation in their own words before the AI judges, corrects, or extends understanding.

Core Features & Use Cases

• Explain-first cognitive gating: Requires a learner’s self-explanation attempt as the entry point, then targets the weakest part of that explanation.
• Probing questions over rewriting: Uses questions to diagnose gaps without replacing the learner’s reasoning.
• Warm-start when the learner is stuck: Provides a structured fallback protocol for learners who report they cannot explain yet.
• Self-explanation closure: Ends with a clean-synthesis prompt to consolidate learning and improve transfer readiness.
• Evidence-aligned: Grounded in the self-explanation effect (generation produces deeper understanding than reading a correct explanation).

Quick Start

Ask the AI to run explain-first interrogation on the topic "photosynthesis" for a Year 11 learner, using your session context and any prior notes.