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 …

In recent years, learner models have emerged from the research laboratory and research
classrooms into the wider world. Learner models are now embedded in real world …

Knowledge tracing serves as the key technique in the computer supported education
environment (eg, intelligent tutoring systems) to model student's knowledge states. While the …

One distinctive feature of any adaptive system is the user model that represents essential
information about each user. This chapter complements other chapters of this book in …

Knowledge tracing (KT) serves as a primary part of intelligent education systems. Most
current KTs either rely on expert judgments or only exploit a single network structure, which …

In this article, we advocate for and propose a novel concept map driven knowledge tracing
(CMKT) model, which utilizes educational concept map for learner modeling. This article …

Knowledge tracing (KT) which aims at predicting learner's knowledge mastery plays an
important role in the computer-aided educational system. The goal of KT is to provide …

In an e-learning system, relationships between a large amount of exercises are complex and
multi-dimensional; measuring the relationships and arranging curriculums accordingly used …

The largest standardized tests (such as the SAT or GRE) are what psychometricians call
“unidimensional” in that they are analyzed as if all the questions are tap** a single latent …

Bayesian networks (BN) provide a convenient and intuitive framework for specifying
complex joint probability distributions and are thus well suited for modeling content domains …