This update is about the moment that convinced us this project was worth building: watching the agent catch a misconception a normal AI tutor would sail right past.
What's new
Diagnostic-first flow — the agent now teaches a concept, then asks a targeted diagnostic question before moving to practice, rather than assuming understanding just because a student didn't ask a follow-up. Misconception detection — when a student answers "the net force is downward, gravity is still acting" at terminal velocity, the agent identifies the specific confusion (zero net force vs. zero gravitational force) instead of just marking it wrong. Persistent mastery state — every interaction now updates a per-topic mastery score (Proficient / Developing / Needs Review) that carries across sessions, not just within one conversation. Structured numerical problem-solving — quantitative problems now walk through units → formula → substitution → calculation → final answer, matching the format examiners expect.
What's next
Expanding the diagnostic loop beyond terminal velocity to the full mechanics unit, and turning the Mastery Map mockup above into a real, persistent student-facing dashboard.
Live demo: https://eduphysics-physics-mastery-agent-poqvtgavdq-el.a.run.app Code: https://github.com/Rajansmoorthy/eduphysics-physics-mastery-agent
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