Date：2025/5/9 14:20-15:30
Location：R103, CSIE
Speakers：Prof. Paul Taele
Host：陳炳宇教授
Abstract:
Students wishing to achieve strong fluency in Mandarin Chinese strongly benefit from studying Chinese characters. For students with primarily English fluency, learning Mandarin Chinese as a foreign language is challenging due to vastly distinct linguistic differences in reading and writing. In this talk, sketch recognition-based intelligent tutoring system approaches were developed for providing richer assessment and feedback that emulates human language instructors, specifically for novice students' introductory Chinese character language study. The approaches relied on various sketch recognition heuristics for evaluating the performance of students' writing technique of introductory Chinese characters through features such as metric scores and visual animations. From evaluating the proposed approaches from instructor feedback for classroom students and self-study learners, a stylus-driven solution was provided for novice language students to study and practice introductory Chinese characters with deeper assessment levels, so that they may have richer feedback to improve their writing performance.
Biography:
Dr. Paul Taele is a University Academic Alliance in Taiwan (UAAT) International Young Visiting Scholar Program research fellow and hosted by Robin Bing-Yu Chen's research lab at National Taiwan University. He was recently an instructional assistant professor and a postdoctoral research scientist in the Sketch Recognition Lab at Texas A&M University's Department of Computer Science & Engineering. He received his dual Bachelor's in Computer Sciences and in Mathematics at the University of Texas at Austin, and his Master's and Ph.D in Computer Science at Texas A&M University. During his graduate studies, he was also a National Science Foundation (NSF) research fellow in the NTU HCI Lab at National Taiwan University and the HCI Research Group at Singapore Management University, and a Japan Society for the Promotion of Science (JSPS) research fellow in the IGARASHI Laboratory's User Interface Research Group at the University of Tokyo. His prior research areas are at the intersection of human-computer interaction and artificial intelligence, such as research in intelligent tutoring systems for educational domains in languages, music, and engineering.