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)
Data Science Education
Artificial Intelligence in Education
Computer Science Education
Profiling self-regulation behaviors in STEM learning of engineering designComputers & Education
Juan Zheng, et al.
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 learningComputers in Human Behavior
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 MOOCsThe Internet and Higher Education
Wanli Xing, Hengtao Tang and Bo Pei
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.