Dr. Shan Li is an Assistant Professor in the College of Health at Lehigh University. He is also an affiliated faculty in the Department of Education and Human Services at Lehigh University. He received his Ph.D. in Educational Psychology (Learning Sciences) from McGill University and a B.S. in Educational Technology from Beijing Normal University. Dr. Li’s research explores the future of digital education, with a focus on the design of innovative learning environments, learning analytics, educational data mining, and Artificial Intelligence in Education (AIED).
Dr. Li is a learning scientist and educational technologist researching learning and teaching in both formal and informal settings related to the health professions. His overarching research goal is to understand and enhance health professions education (HPE) by designing intelligent learning and training applications and examining learning processes related to students’ behavioral patterns, metacognition, emotions, and other attributes. He also employs state-of-the-art computational techniques to reveal performance differences among learners.
Areas of Research
Advanced Learning Technologies, Self-regulated Learning, Learning Analytics, Artificial Intelligence in Education, STEM Education, Health Professions Education
Lajoie, S.P., & Li, S. (2023). Theory-driven design of AIED systems for enhanced interaction and problem solving. In B. du Boulay, A. Mitrovic, & K. Yacef (Eds.), Handbook of Artificial Intelligence in Education. Cheltenham (pp. 229-249), UK: Edward Elgar Press. https://doi.org/10.4337/9781800375413.00020
Zheng, J., Li, S., & Lajoie, S. P. (2023). A review of measurements and techniques to study emotion dynamics in learning. In: Kovanovic, V., Azevedo, R., Gibson, D.C., lfenthaler, D. (eds). Unobtrusive Observations of Learning in Digital Environments. Advances in Analytics for Learning and Teaching. Springer, Cham. https://doi.org/10.1007/978-3-031-30992-2_2
Li, S., Duffy, M. C., Lajoie, S.P., Zheng, J., & Lachapelle, K. (2023). Using eye tracking to examine expert-novice differences during simulated surgical training: A case study. Computers in Human Behavior, 144, 107720.https://doi.org/10.1016/j.chb.2023.107720
Zheng, J., Lajoie, S. P. & Li, S. (2023). Emotions in self-regulated learning: A critical literature review and meta-analysis. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2023.1137010
Li, S. & Lajoie, S.P. (2022). Promoting STEM education through the use of learning analytics: A paradigm shift. In F. Ouyang, P. Jiao, B. McLaren, & A. Alavi (Eds.), Artificial Intelligence in STEM Education: The paradigmatic shifts in research, education, and technology (pp. 211-224). Auerbach: CRC Press. https://doi.org/10.1201/9781003181187-18
Li, S., Zheng, J., Huang, X., & Xie, C. (2022). Self-regulated learning as a complex dynamical system: Examining students’ STEM learning in a simulation environment. Learning and Individual Differences. 95, 102144.
Li, S., Lajoie. S.P., Zheng, J., Wu, H., & Cheng, H. (2021). Automated detection of cognitive engagement to inform the art of staying engaged in problem-solving. Computers and Education. 163, 104114.
Li, S., & Lajoie, S. P. (2021). Cognitive engagement in self-regulated learning: An integrative model. European Journal of Psychology of Education. 1-20.
Li, S., Du, H., Xing, W., Zheng, J., Chen, G., & Xie, C. (2020). Examining temporal dynamics of self-regulated learning behaviors in STEM learning: A network approach. Computers and Education. 158, 103987.
For Dr. Shan Li’s publications, view them on Google Scholar >
- TLT 462 Introduction to Learning Analytics
- TLT 472 Online Teaching and Learning
- CGH 109 Introduction to Health Education
- POPH 395/495 Advanced Technology for Health