Tianlong Zu
Assistant Professor of Instruction - Director of Introductory Physics Labs
- tianlong.zu@northwestern.edu
- 847-491-8639
- Tech F275
I am the Director of Introductory Physics Labs in the Department of Physics & Astronomy. I will be teaching 140-1,2,3 series in the coming 2022-2023 academic year.
I got my undergraduate degree in physics from Nankai University and Ph.D. in physics from Purdue University. Before joining Northwestern in the fall of 2022, I have worked as a visiting Assistant Professor / HHMI educational specialist in the Department of Physics at Lawrence University in Wisconsin, followed by working as a tenure track Assistant Professor of Physics at Jacksonville State University in Alabama.
I am a DBER (discipline-based education research) researcher in physics. My research is mainly about exploring different ways to improve physics education at the college level. For example, I have studied how to use retrieval practice to improve physics students’ problem-solving skills and found that retrieval practice could not only improve physics problem-solving skills, but also correct typical metacognitive errors. I have also studied how to use eye-tracking technology to measure cognitive load(s) which have profound impacts towards learning. In my studies, I have found several eye-movement proxies indicating the three subtypes of cognitive load. More importantly, I found that these proxies do not depend on students’ working memory capacity indicating very robust relationships between the proxies and the corresponding cognitive loads.
Selected Publications
- Magana, A. J., Hwang, J., Feng, S., Rebello, S., Zu, T., & Kao, D. (2022). Emotional and cognitive effects of learning with computer simulations and computer videogames. Journal of Computer Assisted Learning, 38(3), 875-891.
- Zu, T., Munsell, J., & Rebello, N. S. (2021). Subjective measure of cognitive load depends on participants’ content knowledge level. Frontiers in Education, 6, 56.
- Zu, T., Hutson, J., Loschky, L.C., & Rebello, N.S. (2020). Using eye movements to measure intrinsic, extraneous, and germane load in a multimedia learning environment. Journal of Educational Psychology, 112(7), 1338–1352.
- Zu, T., Munsell, J., & Rebello, N. S. (2019). Comparing retrieval-based practice and peer instruction in physics learning. Physical Review Physics Education Research, 15(1), 010105.
- Rebello, N., Nguyen, M., Wang, Y., Zu, T., Hutson, J., & Loschky, L. (2018). Machine Learning Predicts Responses to Conceptual Questions Using Eye Movements. Proceedings of Physics Education Research Conference, Washington, DC.
My current research is supported by an NSF grant (NSF award # 211138: from Oct 01, 2022, to ~Sep 30, 2025) aiming at helping students develop superior problem-solving skills in introductory undergraduate physics courses. In this project, my collaborators and I will develop and test strategies that integrate two proven pedagogical practices -- retrieval practice and scientific argumentation -- to improve problem-solving in the introductory calculus-based physics course that is usually taken by students who intend to become scientists and engineers.