Large swaths of data are readily available in various fields, and education is no exception. In
tandem, the impetus to derive meaningful insights from data gains urgency. Recent …

Knowledge Tracing (KT) aims at tracing the evolution of the knowledge states along the
learning process of a learner. It has become a crucial task for online learning systems to …

Knowledge tracing (KT) aims to model students' knowledge level based on their historical
performance, which plays an important role in computer-assisted education and adaptive …

Adaptive learning, also known as adaptive teaching, relies on learning path
recommendation, which sequentially recommends personalized learning items (eg, lectures …

Recommending suitable exercises to students in an online education system is highly
useful. Existing approaches usually rely on machine learning techniques to mine large …

We present a novel method for predicting the evolution of a student's grade in massive open
online courses (MOOCs). Performance prediction is particularly challenging in MOOC …

Abstract Knowledge tracing (KT) aims to trace students' knowledge states by predicting
whether students answer correctly on exercises. Despite the excellent performance of …

Abstract Knowledge tracing (KT) is the task of using students' historical learning interaction
data to model their knowledge mastery over time so as to make predictions on their future …

The rapid development of the technologies for online learning provides students with
extensive resources for self-learning and brings new opportunities for data-driven research …

Knowledge tracing, which dynamically estimates students' learning states by predicting their
performance on answering questions, is an essential task in online education. One typical …