Prompt engineering for teacher insights with Claude — structured JSON and graceful fallbacks
NumPath has developed a system that uses Anthropic's Claude to generate actionable insights for teachers based on student performance data. The system prompts Claude to provide a text-based observation and a severity type (warn, good, info) in a JSON format. Crucially, the evidence backing the insight is assembled server-side from database queries, ensuring auditability and adherence to research frameworks that require traceable AI-generated feedback. AI
IMPACT Enables teachers to receive structured, auditable feedback on student performance, enhancing educational tools with AI.