Associate Professor, Department of Computer Science, City University of Hong Kong
Professor Howard Leung obtained his Master and PhD from Carnegie Mellon University. His research includes 3D human motion analysis and digital handwriting assessment tools. Since 2004, he has developed many algorithms to analyse Chinese handwritings. He has been collaborating with Prof. Cecilia Li who is an experienced occupational therapist to develop computerised methods for assessing students’ Chinese handwriting performance.
He is the Principal of the Bright Future Engineering Talent Hub at City University of Hong Kong and has been in charge of organising several STEM activities to engage young talents and inspire their interests in engineering.
Handwriting is one important skill that students spend many years practicing since their young ages. This is an important step in learning their language and very helpful for Chinese learners to remember thousands of different Chinese characters taught in primary school in Hong Kong. Traditionally students use pen or pencil to produce the handwritings on paper and teachers can check if there are any errors in students' handwritings and assess the students' handwriting performance. It would be very tedious for teachers to perform detailed checking. As a result, the speaker’s team has made use of writing tablets to collect students' digital handwritings and processed them to measure the handwriting speed and detect handwriting errors by applying pattern matching algorithms.
The team has been collaborating with occupational therapist experts in projects to develop various digital handwriting assessment tools targeting primary and secondary school students. One tool known as Computerised Handwriting Speed Test System (CHSTS) has been adopted by the Hong Kong Examination and Assessment Authority (HKEAA) to assess the handwriting speed of secondary school students and determine whether and how much extra time allowance should be given during public exams to a secondary school student with handwriting difficulties.
With the digital handwriting analysis tools developed, the team can provide an objective way of assessing a student's handwriting and comparing it with the norm. The tools can also help teachers or health care professionals to screen out students who may have learning difficulties so that appropriate early intervention can be employed.