Learning behavior-oriented knowledge tracing
Exploring how learners' knowledge states evolve during the learning activities is a critical
task in online learning systems, which can facilitate personalized services downstream, such …
task in online learning systems, which can facilitate personalized services downstream, such …
Integrating machine learning into item response theory for addressing the cold start problem in adaptive learning systems
Adaptive learning systems aim to provide learning items tailored to the behavior and needs
of individual learners. However, one of the outstanding challenges in adaptive item selection …
of individual learners. However, one of the outstanding challenges in adaptive item selection …
Generative models of visually grounded imagination
It is easy for people to imagine what a man with pink hair looks like, even if they have never
seen such a person before. We call the ability to create images of novel semantic concepts …
seen such a person before. We call the ability to create images of novel semantic concepts …
DAS3H: modeling student learning and forgetting for optimally scheduling distributed practice of skills
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 …
literature. It consists in temporally distributing exposure to an information so as to improve …
Proactive and reactive engagement of artificial intelligence methods for education: a review
S Mallik, A Gangopadhyay - Frontiers in artificial intelligence, 2023 - frontiersin.org
The education sector has benefited enormously through integrating digital technology driven
tools and platforms. In recent years, artificial intelligence based methods are being …
tools and platforms. In recent years, artificial intelligence based methods are being …
Enhancing deep knowledge tracing with auxiliary tasks
Knowledge tracing (KT) is the problem of predicting students' future performance based on
their historical interactions with intelligent tutoring systems. Recent studies have applied …
their historical interactions with intelligent tutoring systems. Recent studies have applied …
Reinforcement learning for the adaptive scheduling of educational activities
J Bassen, B Balaji, M Schaarschmidt, C Thille… - Proceedings of the …, 2020 - dl.acm.org
Adaptive instruction for online education can increase learning gains and decrease the work
required of learners, instructors, and course designers. Reinforcement Learning (RL) is a …
required of learners, instructors, and course designers. Reinforcement Learning (RL) is a …
Knowledge structure enhanced graph representation learning model for attentive knowledge tracing
W Gan, Y Sun, Y Sun - International Journal of Intelligent …, 2022 - Wiley Online Library
Abstract Knowledge tracing (KT) is a fundamental personalized‐tutoring technique for
learners in online learning systems. Recent KT methods employ flexible deep neural …
learners in online learning systems. Recent KT methods employ flexible deep neural …
Back to the basics: Bayesian extensions of IRT outperform neural networks for proficiency estimation
KH Wilson, Y Karklin, B Han, C Ekanadham - arXiv preprint arXiv …, 2016 - arxiv.org
Estimating student proficiency is an important task for computer based learning systems. We
compare a family of IRT-based proficiency estimation methods to Deep Knowledge Tracing …
compare a family of IRT-based proficiency estimation methods to Deep Knowledge Tracing …
Knowledge modeling via contextualized representations for LSTM-based personalized exercise recommendation
Intelligent education systems have enabled personalized learning (PL). In PL, students are
presented with educational contents that are consistent with their personal knowledge states …
presented with educational contents that are consistent with their personal knowledge states …