An Enterprise-Grade EdTech Solution for Real-Time Handwriting Assistance: A Usability and Accessibility Approach

Abstract

The research presents Fun Letter Tracing as an educational technology system which provides real-time handwriting assistance for primary school students. The system uses React for its browser-based front end and Flask for its lightweight scoring service to create a practice loop that analyzes user input after tracing followed by tip generation and retry functionality. The system evaluates handwriting quality through a 50-dimensional feature vector which includes smoothness and consistency and spatial spread and completeness and temporal cues and uses Random Forest and small FFNN models with letter-specific geometric checks based on keypoints and pixel corridors. The system provides a limited API set which includes /analyze and /letter-info/<letter> and /progress-summary and /health endpoints to make school integration easier while maintaining privacy protection through default operation. The development team focused on creating an accessible system which follows WCAG 2.2 standards through its design of large touch areas and visible focus indicators and non-color based alerts and TTS functionality and simple language for children. The evaluation strategy combines three assessment methods which include expert walkthroughs and controlled testing and classroom-based trials involving 30-50 students and 10-15 teachers. The evaluation uses both quantitative metrics including SUS scores and completion rates and time-to-first-success and latency performance at 150 ms or below and expert rubric assessments and qualitative feedback from teachers and students. The thesis presents detailed information about system architecture and security measures and accessibility standards and testing procedures for school implementation.