HHSKT: A learner–question interactions based heterogeneous graph neural network model for knowledge tracing

Q Ni, T Wei, J Zhao, L He, C Zheng - Expert Systems with Applications, 2023‏ - Elsevier
Abstract Knowledge tracing (KT) has evolved into a crucial component of the online
education system with the rapid development of online adaptive learning. A key component …

FDKT: Towards an interpretable deep knowledge tracing via fuzzy reasoning

F Liu, C Bu, H Zhang, L Wu, K Yu, X Hu - ACM Transactions on …, 2024‏ - dl.acm.org
In educational data mining, knowledge tracing (KT) aims to model learning performance
based on student knowledge mastery. Deep-learning-based KT models perform remarkably …

Multiple learning features–enhanced knowledge tracing based on learner–resource response channels

Z Wang, Y Hou, C Zeng, S Zhang, R Ye - Sustainability, 2023‏ - mdpi.com
Knowledge tracing is a crucial task that involves modeling learners' knowledge levels and
predicting their future learning performance. However, traditional deep knowledge tracing …

Meta multi-agent exercise recommendation: A game application perspective

F Liu, X Hu, S Liu, C Bu, L Wu - Proceedings of the 29th ACM SIGKDD …, 2023‏ - dl.acm.org
Exercise recommendation is a fundamental and important task in the E-learning system,
facilitating students' personalized learning. Most existing exercise recommendation …

Student modeling and analysis in adaptive instructional systems

J Liang, R Hare, T Chang, F Xu, Y Tang… - IEEE …, 2022‏ - ieeexplore.ieee.org
There is a growing interest in develo** and implementing adaptive instructional systems
to improve, automate, and personalize student education. A necessary part of any such …

A literature review of knowledge tracing for student modeling: research trends, models, datasets, and challenges

EH Am, I Hidayah, SS Kusumawardani - Journal of Information …, 2021‏ - jitecs.ub.ac.id
Modeling students' knowledge is a fundamental part of online learning platforms.
Knowledge tracing is an application of student modeling which renowned for its ability to …

Cognitive diagnostic model made more practical by genetic algorithm

C Bu, F Liu, Z Cao, L Li, Y Zhang… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Cognitive diagnosis has attracted increasing attention owing to the flourishing development
of online education. As one of the most widely used cognitive diagnostic models, DINA …

A probabilistic generative model for tracking multi-knowledge concept mastery probability

H Liu, T Zhang, F Li, M Yu, G Yu - Frontiers of Computer Science, 2024‏ - Springer
Abstract Knowledge tracing aims to track students' knowledge status over time to predict
students' future performance accurately. In a real environment, teachers expect knowledge …

Twenty-five years of Bayesian knowledge tracing: a systematic review

I Šarić-Grgić, A Grubišić, A Gašpar - User Modeling and User-Adapted …, 2024‏ - Springer
The quality of an artificial intelligence-based tutoring system is its ability to observe and
interpret student behaviour to infer the preferences and needs of an individual student. The …

SPAKT: A self-supervised pre-training method for knowledge tracing

Y Ma, P Han, H Qiao, C Cui, Y Yin, D Yu - IEEE Access, 2022‏ - ieeexplore.ieee.org
Knowledge tracing (KT) is the core task of computer-aided education systems, and it aims at
predicting whether a student can answer the next exercise (ie, question) correctly based on …