Learner modeling is a basis of personalized, adaptive learning. The research literature
provides a wide range of modeling approaches, but it does not provide guidance for …

Knowledge tracing (KT) refers to the problem of predicting future learner performance given
their past performance in educational applications. Recent developments in KT using …

Spaced repetition is a technique for efficient memorization which uses repeated review of
content following a schedule determined by a spaced repetition algorithm to improve long …

Spaced repetition is among the most studied learning strategies in the cognitive science
literature. It consists in temporally distributing exposure to an information so as to improve …

In a wide variety of applications, humans interact with a complex environment by means of
asynchronous stochastic discrete events in continuous time. Can we design online …

With the increasing demands of personalized learning, knowledge tracing has become
important which traces students' knowledge states based on their historical practices. Factor …

We investigate privacy-preserving, video-based action recognition in deep learning, a
problem with growing importance in smart camera applications. A novel adversarial training …

Traditional learning-based approaches to student modeling generalize poorly to
underrepresented student groups due to biases in data availability. In this paper, we …

Guiding a student through a sequence of lessons and helping them retain knowledge is one
of the central challenges in education. Online learning platforms like Khan Academy and …

The popular media's recent interest in artificial intelligence (AI) has focused on autonomous
systems that might ultimately replace people in fields as diverse as medicine, customer …