Select Publications:
2025
Ocumpaugh, J., Nasiar, N., Zambrano, A.F., Goslen, A., Bandenberg, J., Esiason, J., Rowe, J., Hutt, S. (2025). Refocusing the Lense through which we view affect dynamics: The Skills, Difficulty, Value, Efficacy, and Time (SDVET) Model. To appear in the Proceedings of the 15th International Conference on Learning Analytics and Knowledge (LAK25). (link)
Ocumpaugh, J., Liu, X., Zambrano A.F. (2025). Large Language Models and Dialect Differences: A case study on the treatment of African American Language (AAL) in grading by ChatGPT. To appear in the Proceedings of the 15th International Conference on Learning Analytics and Knowledge (LAK25). (link)
2024
Cloude, E. B., Munshi, A., Andres, J. A., Ocumpaugh, J., Baker, R. S., & Biswas, G. (2024). Exploring Confusion and Frustration as Non-linear Dynamical Systems. Proceedings of the 14th International Conference on Learning Analytics and Knowledge (LAK24). (link)
Ocumpaugh, J., Roscoe, R., Baker., R.S., Hutt, S., Aguilar, S. (2024). Toward Asset-based Instruction and Assessment in Artificial Intelligence in Education. International Journal of Artificial Intelligence in Education. (link to preprint copy)
Ocumpaugh, J. (2024). Data Driven Classroom Interviews (DDCI): Collecting contextualized data at scale. Invited Talk. Special Interest Group on Technology, Instruction, Cognition, & Learning. American Education Research Association.
Zambrano, A. F., Nasiar, N., Ocumpaugh, J., Goslen, A., Zhang, J., Rowe, J., Esiason, J., Vandenberg, J., & Hutt, S. (2024). Says Who? How different ground truth measures of emotion impact student affective modeling. In Proceedings of the 17th International Conference on Educational Data Mining (pp. 211-223).
Earlier:
Ocumpaugh, J., Baker, R.S., & Rodrigo, M. M. T. (2015). Baker Rodrigo Ocumpaugh Monitoring Protocol (BROMP) 2.0 technical and training manual. Technical Report. New York, NY: Teachers College, Columbia University. Manila, Philippines: Ateneo Laboratory for the Learning Sciences. [253 Citations as of December 2024] (link)
Ocumpaugh, J., Baker, R.S., Gowda, S., Heffernan, N., & Heffernan, C. (2014). Population validity for Educational Data Mining models: A case study in affect detection. British Journal of Educational Technology, 45(3), 487-501. [225 citations as of December 2024] (link to preprint copy)
Baker, R.S.J.d., Ocumpaugh, J. (2014) Interaction-Based Affect Detection in Educational Software. In R.A. Calvo, S.K. D'Mello, J. Gratch, A. Kappas (Eds.), The Oxford Handbook of Affective Computing. Oxford, UK: Oxford University Press. [78 Citations as of December 2024] (link)
Baker, R.S.J.d., Gowda, S. M., Wixon, M., Kalka, J., Wagner, A. Z., Salvi, A., Aleven, V., Kusbit, G., Ocumpaugh, J., & Rossi, L. (2012) Towards Sensor-free Affect Detection in Cognitive Tutor Algebra. In Proceedings of the 5th International Conference on Educational Data Mining (EDM), 126-133. [Won the 2024 Test of Time Award from the International Society of Educational Data Mining; 270 Citations as of December 2024] (link)
Teaching:
Currently teaching for both the Penn GSE MA in Learning Analytics & Artificial Intelligence and for the Penn GSE Certificate in Data Science Methods for Digital Learning Platforms.
Please see my course resource page for the Dashboards in Learning Analytics class for more resources on data visualization.
Please see CV for additional teaching experience in a range of fields.
Download CV: [link]
Service:
Co-Editor, Computer Based Learning in Context
Reviewer, multiple journals, conferences, and competitions in the Learning Sciences
Committee service and mentorship for multiple graduate students