Write Right

What it does

“Write Right” combines traditional Chinese handwriting practice with technology, providing real-time analysis as “font scores” through the website. It gamifies learning while maintaining educational value, making handwriting practice engaging and effective.

Your inspiration

The inspiration came from my experience as a Chinese Language tutor and the HKDSE Chinese Writing Exam requirement, where handwriting aesthetics is part of the score. Traditional teaching methods weren't engaging for digital-native students, while existing apps lacked comprehensive feedback systems. The idea crystallised when I observed students' improper handwriting, such as writing “口” as “O”, neglecting proper stroke structure. This observation, combined with my engineering background and passion for education, led me to create a system that makes handwriting practice more interactive and enjoyable while maintaining educational rigour.

How it works

“Write Right” implements a multi-layered assessment algorithm that revolutionises Chinese handwriting evaluation through innovative image processing algorithms. The system uniquely integrates OpenCV.js for morphological operations and Hough Transform, enabling precise similarity analysis against Standard Script. At its core, the platform employs a proprietary three-criteria weighted algorithm: stroke order verification through sequential pattern matching, character recognition using contour detection and dilation transforms, and aesthetic evaluation via feature extraction and template matching. What sets it apart is the gamified learning environment - a mini-board game where correct writing advances players based on their “font score.” This comprehensive approach transforms traditional handwriting practice into an engaging, technologically advanced learning experience that provides immediate, objective feedback for improvement.

Design process

The development followed an iterative evolutionary prototyping approach, grounded in extensive research on Chinese handwriting principles and existing digital learning tools. Core functionalities were first implemented using HanziLookupJS for character recognition, with my innovative similarity algorithm as a key feature. The gamification element evolved significantly based on user feedback. What began as a simple two-player chess-style board game transformed into an interactive battle system. At designated tiles, players compete head-to-head by writing the same randomly generated character. The system evaluates each player’s handwriting using our proprietary “font score” algorithm, which considers stroke order, character recognition, and aesthetic quality. The player with the higher score advances an extra step, while the lower-scoring player remains in place. Testing with students and teachers helped refine the UI/UX and scoring algorithm. The final phase focused on cross-device compatibility and recognition accuracy. The iterative process makes the system a more engaging and educational experience, where competition improves handwriting quality. This approach proved particularly effective, as students grew motivated to perfect their handwriting for competitive advantages.

How it is different

“Write Right” distinguishes itself through three unique innovations in Chinese handwriting education. First, my proprietary three-criteria assessment system evaluates stroke order, character recognition, and aesthetic quality, generating a precise “font score” on a 100-point scale, while existing solutions only offer basic stroke animations. Second, the platform integrates advanced technologies - OpenCV.js for image processing and HanziLookupJS for character recognition - enabling accurate real-time analysis across simplified and traditional Chinese characters. The system includes the innovative similarity matching algorithm, published at the IEEE conference. Third, the system features a unique two-player battle system where players compete through handwriting quality, offering unlimited free practice, unlike existing apps that restrict practice attempts, making it particularly effective for HKDSE Chinese examination preparation.

Future plans

Future development will focus on implementing AI-powered analysis for more sophisticated handwriting evaluation, expanding the character database, and adding advanced personalisation features. Plans include developing a mobile application, introducing collaborative learning features, and integrating with educational management systems. I aim to partner with educational institutions for wider implementation and create a comprehensive teacher dashboard for monitoring student progress. International market expansion is also planned, with localisation features to support global adoption.

Awards

• 2024 CUHK Outstanding Student Award (Innovation and Invention) • Published at the 2024 IEEE 13th International Conference on Engineering Education • 2025 Professor Charles K. Kao Student Creativity Awards (Undergraduate Individual 1st runner-up)