Intelligent techniques in e-learning: a literature review

M Ilić, V Mikić, L Kopanja, B Vesin - Artificial Intelligence Review, 2023 - Springer
Online learning has become increasingly important, having in mind the latest events,
imposed isolation measures and closed schools and campuses. Consequently, teachers …

Hybrid models for knowledge tracing: A systematic literature review

A Zanellati, D Di Mitri, M Gabbrielli… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Knowledge tracing is a well-known problem in AI for education, consisting of monitoring how
the knowledge state of students changes during the learning process and accurately …

Enhancing deep knowledge tracing with auxiliary tasks

Z Liu, Q Liu, J Chen, S Huang, B Gao, W Luo… - Proceedings of the ACM …, 2023 - dl.acm.org
Knowledge tracing (KT) is the problem of predicting students' future performance based on
their historical interactions with intelligent tutoring systems. Recent studies have applied …

Improving interpretability of deep sequential knowledge tracing models with question-centric cognitive representations

J Chen, Z Liu, S Huang, Q Liu, W Luo - Proceedings of the AAAI …, 2023 - ojs.aaai.org
Abstract Knowledge tracing (KT) is a crucial technique to predict students' future
performance by observing their historical learning processes. Due to the powerful …

RCD: Relation map driven cognitive diagnosis for intelligent education systems

W Gao, Q Liu, Z Huang, Y Yin, H Bi, MC Wang… - Proceedings of the 44th …, 2021 - dl.acm.org
Cognitive diagnosis (CD) is a fundamental issue in intelligent educational settings, which
aims to discover the mastery levels of students on different knowledge concepts. In general …

Semantics of the black-box: Can knowledge graphs help make deep learning systems more interpretable and explainable?

M Gaur, K Faldu, A Sheth - IEEE Internet Computing, 2021 - ieeexplore.ieee.org
The recent series of innovations in deep learning (DL) have shown enormous potential to
impact individuals and society, both positively and negatively. DL models utilizing massive …

Structure-based knowledge tracing: An influence propagation view

S Tong, Q Liu, W Huang, Z Hunag… - … conference on data …, 2020 - ieeexplore.ieee.org
Knowledge Tracing (KT) is a fundamental but challenging task in online education that
traces learners' evolving knowledge states. Much attention has been drawn to this area and …

EXAIT: Educational eXplainable artificial intelligent tools for personalized learning

H Ogata, B Flanagan, K Takami… - … and Practice in …, 2024 - repository.kulib.kyoto-u.ac.jp
As artificial intelligence systems increasingly make high-stakes recommendations and
decisions automatically in many facets of our lives, the use of explainable artificial …

simpleKT: a simple but tough-to-beat baseline for knowledge tracing

Z Liu, Q Liu, J Chen, S Huang, W Luo - arxiv preprint arxiv:2302.06881, 2023 - arxiv.org
Knowledge tracing (KT) is the problem of predicting students' future performance based on
their historical interactions with intelligent tutoring systems. Recently, many works present …

Modeling context-aware features for cognitive diagnosis in student learning

Y Zhou, Q Liu, J Wu, F Wang, Z Huang… - Proceedings of the 27th …, 2021 - dl.acm.org
The contexts and cultures have a direct impact on student learning by affecting student's
implicit cognitive states, such as the preference and the proficiency on specific knowledge …