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Zhaoxing Li's Outputs (3)

User-Defined Hand Gesture Interface to Improve User Experience of Learning American Sign Language (2023)
Book Chapter
Wang, J., Ivrissimtzis, I., Li, Z., Zhou, Y., & Shi, L. (2023). User-Defined Hand Gesture Interface to Improve User Experience of Learning American Sign Language. In C. Frasson, P. Mylonas, & C. Troussas (Eds.), Augmented Intelligence and Intelligent Tutoring Systems: 19th International Conference, ITS 2023, Corfu, Greece, June 2-5, 2023, Proceedings (479-490). Springer Verlag. https://doi.org/10.1007/978-3-031-32883-1_43

Sign language can make possible effective communication between hearing and deaf-mute people. Despite years of extensive pedagogical research, learning sign language remains a formidable task, with the majority of the current systems relying extensiv... Read More about User-Defined Hand Gesture Interface to Improve User Experience of Learning American Sign Language.

Fine-grained Main Ideas Extraction and Clustering of Online Course Reviews (2022)
Book Chapter
Xiao, C., Shi, L., Cristea, A., Li, Z., & Pan, Z. (2022). Fine-grained Main Ideas Extraction and Clustering of Online Course Reviews. In M. Rodrigo, N. Matsuda, A. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education (294-306). Springer, Cham. https://doi.org/10.1007/978-3-031-11644-5_24

Online course reviews have been an essential way in which course providers could get insights into students’ perceptions about the course quality, especially in the context of massive open online courses (MOOCs), where it is hard for both parties to... Read More about Fine-grained Main Ideas Extraction and Clustering of Online Course Reviews.

SimStu-Transformer: A Transformer-Based Approach to Simulating Student Behaviour (2022)
Book Chapter
Li, Z., Shi, L., Cristea, A., Zhou, Y., Xiao, C., & Pan, Z. (2022). SimStu-Transformer: A Transformer-Based Approach to Simulating Student Behaviour. In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (348-351). Springer, Cham. https://doi.org/10.1007/978-3-031-11647-6_67

Lacking behavioural data between students and an Intelligent Tutoring System (ITS) has been an obstacle for improving its personalisation capability. One feasible solution is to train “sim students”, who simulate real students’ behaviour in the ITS.... Read More about SimStu-Transformer: A Transformer-Based Approach to Simulating Student Behaviour.