Keep humans in the decision loop
Assisted evaluation is separate from final judgement. Moderation makes disagreements visible and preserves a review trail.
Research2025–26
Make every mark traceable.
A human-in-the-loop marking platform connecting answer-sheet intake, AI-assisted evaluation, moderation, and QR-verifiable records.
Make every mark traceable.
01THE PROBLEM
Answer evaluation needs readable capture, correct script-to-record mapping, and a way to review differences between human and AI assessments.
02MY CONTRIBUTION
My work covers the research manuscript, literature review, cost modelling, and an ESP32-S3 CAM capture-rig architecture. The optical design considers lens calibration, lighting, and capture quality before evaluation.
Team repository03KEY DECISIONS
Assisted evaluation is separate from final judgement. Moderation makes disagreements visible and preserves a review trail.
Unreadable input undermines every later step. The capture design considers optical budget, calibration, and dual-LED illumination.
Analytical estimates guide the prototype but require empirical evaluation before operational claims.
04OUTCOME & NEXT STEPS
Research manuscript in preparation, with a documented capture architecture and evaluation workflow. Team and upstream credit are preserved.
The software works with uploaded or browser-captured answer sheets. The repository documents the physical camera provider as a planned, uncertified integration; a separate team post describes a hackathon capture-system build. The manuscript is in preparation, and measured grading accuracy and hardware performance remain to be validated.
Evaluate capture quality and review outcomes using an appropriate, permissioned test dataset.