Collaborative problem solving
How groups regulate their work and make progress on complex, ill-structured problems.
Researcher · Educator
Hui Shi 时慧
Studying how people learn, solve complex problems, and build knowledge together in technology-rich environments.
Assistant Professor · Faculty of Artificial Intelligence in Education
Central China Normal University
01 / About
Learning as a sociocognitive and data-rich process.
I am an Assistant Professor in the Faculty of Artificial Intelligence in Education at Central China Normal University. My research examines collaborative problem solving and knowledge co-construction, with particular attention to how technology and AI shape learning interactions.
I also use educational data mining and learning analytics to understand patterns of learning and to inform the design of more effective educational experiences.
时慧，华中师范大学人工智能教育学部讲师，硕士生导师，美国佛罗里达州立大学（Florida State University）教学系统与学习分析专业博士。主要研究方向为人机交互，协作问题解决，教育智能体，学习分析。目前仍有2027年秋季入学硕士生指标，如对人机交互、多智能体协作、问题解决感兴趣，且动手能力、自驱力强的学生，欢迎联系：hshi@ccnu.edu.cn
02 / Research
Areas of inquiry
Knowledge co-construction
How discussion and peer interaction contribute to shared understanding.
Human–AI interaction in education
How learners and AI-supported pedagogical agents interact in educational settings.
Learning analytics and online learning
Using learning data to examine participation, student support, and digital distraction.
03 / Publications
Selected publications
Peer-reviewed journal articles. For a full and current publication list, visit Google Scholar.
Decreasing Digital Distraction in College Students: Associated Online Learning Strategies Identified by Unsupervised Data Mining Approaches
Applications of Machine Learning for At-Risk Student Prediction in Online Education: A 10-Year Systematic Review of Literature
Do Generative AI-Powered Pedagogical Agents Improve Learners’ Academic Performance Effectively? Evidence from Meta-Analysis
Data-Driven Decision-Making in Instructional Design: Instructional Designers’ Practices and Strategies
To What Extent Has Machine Learning Achieved in Predicting Online At-Risk Students? Evidence from Quantitative Meta-Analysis
From Unsuccessful to Successful Learning: Profiling Behavior Patterns and Student Clusters in Massive Open Online Courses
Instructional Strategies for Engaging Online Learners: Do Learner-Centeredness and Modality Matter?
04 / Background
Academic background
Appointments & teaching
Assistant Professor · 2025–presentCentral China Normal University
Faculty of Artificial Intelligence in Education.
Course Instructor · 2023–2025Florida State University
Undergraduate educational technology courses for preservice teachers.
Research Assistant · 2021–2025Florida State University
Education
Ph.D. · 2025Florida State University
Instructional Systems and Learning Technologies.
M.S. · 2021East China Normal University
Educational Information Technology.
Visiting · 2020Auburn University
Educational Psychology.
B.S. · 2018Jiangnan University
Education Technology.
Get in touch
Research & collaboration
Faculty of Artificial Intelligence in Education
Central China Normal University · Hubei, China