3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CY2024
Integrating Attentional Factors and Spacing in Logistic Knowledge Tracing Models to Explore the Impact of Training Sequences on Category Learning
Meng Cao, Philip I. Pavlik, Wei Chu +1
In category learning, a growing body of literature has increasingly focused on exploring the impacts of interleaving in contrast to blocking. The sequential attention hypothesis po…
cs.CY2021
Modeling the EdNet Dataset with Logistic Regression
Philip I. Pavlik, Luke G. Eglington
Many of these challenges are won by neural network models created by full-time artificial intelligence scientists. Due to this origin, they have a black-box character that makes th…
stat.AP2020★ 3 cited
Logistic Knowledge Tracing: A Constrained Framework for Learner Modeling
Philip I. Pavlik, Luke G. Eglington, Leigh M. Harrell-Williams
Adaptive learning technology solutions often use a learner model to trace learning and make pedagogical decisions. The present research introduces a formalized methodology for spec…