Pamela Popp, Ph.D.

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Instructor

Educational Background

On Teaching

I love the process of teaching and working to make learning interesting and fun for my students. In fact, my interest in teaching shapes a large portion of my research, where I aim to study how people teach and communicate ideas to one another. During graduate school, I taught undergraduate courses at New York University and designed and taught summer high school programs at Columbia University. Based on both my research and personal experience, I believe students learn best when they are given agency and initiative over their own learning. However, I also believe that it is the responsibility of teachers to work hard to prepare lessons that inspire students to provide that active engagement. In college, I was often disappointed by professors that would lecture from a textbook and expect the knowledge to magically materialize in their students鈥� minds. I believe that teachers and students both need to put in effort to achieve learning goals and make classroom experiences memorable, productive, and fun.

On Research

I am a cognitive scientist interested in how humans and machines work together to learn, teach, and help each other. An important part of my research is building and understanding artificial intelligence (AI) and machine learning models, with a goal of identifying what makes humans unique from machines. My dissertation work focused on applying computational models to human learning, decision making, and social interaction. In my research, I design online games to study how people engage with a carefully designed environment. I compare how humans and AI agents plan and act, using the differences to understand human cognition through a computational lens. I鈥檓 also interested in machine teaching algorithms and how to optimize the process of learning through intelligent systems and serious games.

Publications

Osborn Popp, P. J., Newell, B., Bartels, D., & Gureckis, T. M. (2025). Journal of Experimental Psychology: General,154(4), 1025鈥�1037. https://doi.org/10.1037/xge0001682
Osborn Popp, P. J. & Gureckis, T. M. (2024). . Proceedings of the Annual Meeting of the Cognitive Science Society, 46.
Osborn Popp, P. J. & Gureckis, T. M. (2023). . Proceedings of the Conference on Cognitive Computational Neuroscience. DOI: 10.32470/CCN.2023.1677-0
Osborn Popp, P. J., Newell, B., Bartels, D., & Gureckis, T. M. (2022). . Proceedings of the Annual Meeting of the Cognitive Science Society, 44.
Osborn Popp, P. J. & Gureckis, T. M. (2020). . Proceedings of the Annual Meeting of the Cognitive Science Society, 42.
Rich, A., Osborn Popp, P. J., Halpern, D., Rothe, A., & Gureckis, T. (2018). . Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications. https://doi.org/10.18653/v1/W18-0526
Halpern, D., Tubridy, S., Wang, H., Gasser, C., Osborn Popp, P. J., Davachi, L. & Gureckis, T. (2018). . Educational Data Mining.
Rankin, J., Osborn Popp, P. J., & Rinzel, J. (2017). . Frontiers in Neuroscience, 11, 198. https://doi.org/10.3389/fnins.2017.00198
Leal-Campanario, R., Alarcon-Martinez, L., Rieiro, H. et al. . Sci Rep 7, 43276 (2017). https://doi.org/10.1038/srep43276

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