AI Teaching Copilot — Learner-Aware

AI Teaching Copilot — Learner-Aware Generative AI Tutor for RRampUp (Canada)

An AI tutor that detects whether a student is struggling or excelling — and rewrites its own teaching style in real time to match.

Most AI tutoring tools give every student the same explanation regardless of level — struggling learners get lost, advanced learners disengage, and instructors have no way to personalize at scale. I built a learner-aware generative AI copilot for RRampUp (Canada) that solves this by classifying each student's level in real time and switching teaching styles automatically.

The system tracks accuracy, response time, and topic mastery per learner to detect which mode fits: Supportive Mode kicks in on low accuracy or repeated errors, delivering step-by-step scaffolding with simpler vocabulary and a worked example first. Advanced Mode kicks in on high accuracy or fast correct answers, delivering concise direct responses with follow-up challenge questions that assume fundamentals are already mastered.

Every single answer is grounded in real course material through a RAG pipeline — content is chunked, embedded, and retrieved per question — so the copilot never hallucinates an explanation untethered from the actual curriculum. Consistency across both teaching tiers was achieved through iterative system-prompt and few-shot tuning, evaluated and refined rather than shipped once and left alone.

Results: 85% response accuracy, 95% positive learner feedback, 100% RAG-grounded answers (zero hallucination), and a single engine serving both remedial and advanced learners without separate systems.

Stack: RAG pipeline with vector store (ingestion & retrieval) · learner profiling engine (accuracy, response time, topic-mastery tracking) · system-prompt & few-shot engineering per learner tier · LLM-based grounded generation.

If you're building a tutoring product, internal training tool, or any Q&A assistant where users have different skill levels, this personalization layer adapts without needing separate systems per user tier.