Wanli Xing
Assistant Professor | University of Florida
Gainesville, FL, UNITED STATES
Wanli Xing aims to push the fundamental limits of learning analytics and AI to revolutionize STEM and online education.
Biography
Wanli Xing's research themes are: design and develop fair, accountable and transparent learning analytics and AI powered learning environments; explore and leverage educational big data in various forms and modalities to advance the basic understanding of learning processes; and create cyberinfrastructure for the advancement and transformation of learning analytics and AI research in education.
Areas of Expertise (6)
STEM Education
Data Science Education
Learning Analytics
Artificial Intelligence in Education
AI Education
Computer Science Education
Articles (3)
Profiling self-regulation behaviors in STEM learning of engineering design
Computers & EducationJuan Zheng, et al.
2020-01-01
Engineering design is a complex process which requires science, technology, engineering, and mathematic (STEM) knowledge. Students' self-regulation plays a critical role in interdisciplinary tasks. However, there is limited research investigating whether and how self-regulation leads to different learning outcomes among students in engineering design.
The effects of transformative and non-transformative discourse on individual performance in collaborative-inquiry learning
Computers in Human BehaviorWanli Xing
2019-09-01
The effectiveness of computer-supported collaborative inquiry learning in STEM education is well-documented in the literature. At the same time, research indicates that some students struggle to articulate relevant concepts, to make their reasoning explicit, and to regulate their learning—all of which are necessary for effective collaboration. In this study, 106 college students completed tasks related to Ohm's Law in a simulation-based, collaborative-inquiry learning environment.
Beyond positive and negative emotions: Looking into the role of achievement emotions in discussion forums of MOOCs
The Internet and Higher EducationWanli Xing, Hengtao Tang and Bo Pei
2019-06-11
Millions of students register for Massive Open Online Courses (MOOCs) to look for opportunities for learning and self-development. However, the learning process usually involves emotional experience, which may affect students' participation in the course, eventually resulting in dropping out along the way. In this study, we quantify this effect. Particularly, this research goes beyond focusing on only the single dimension of positive or negative emotions as many prior studies do.
