Research Associate, TELL Lab
Education and Training
PhD, University of Pittsburgh
My current research goal is to increase a student's learning when engaging with a tutorial dialogue system. My approach is to link computational models of dialogue to theories of macro and micro-adaptivity, mastery learning and student modeling. More generally, I'm interested in adapting content and textual presentations according to user needs.
Related Research Areas
Katz, S., Albacete, P., Chounta, I.A., Jordan, P., McLaren, B., & Zapata-Rivera, D. (2021). Linking dialogue with student modelling to create an adaptive tutoring system for conceptual physics. International Journal of Artificial Intelligence in Education.
Jordan, P., Albacete, P., & Katz, S. (2017). Adapting step granularity in tutorial dialogue based on pretest scores. Proceedings of the 18th International Conference on Artificial Intelligence in Education (AIED 2017).
Chounta, I-A., McLaren, B., Albacete, P., Jordan, P., & Katz, S. (2016). Analysis of human-to-human tutorial dialogues: Insights for teaching analytics. The 4thInternational Workshop on Teaching Analytics at Ec-Tel 16.
Jordan, P., Albacete, P., & Katz, S. (2016). Exploring continent step decomposition ina tutorial dialogue system. Proceedings of the 24th Conference on User Modeling, Adaptation, and Personalization (UMAP)—Late breaking papers.
Katz, S., Jordan, P., & Albacete, P. (2016). Exploring how to adaptively apply tutorial dialogue tactics. Proceedings of the 16th International Conference on Advanced Learning Technologies—ICALT2016.