Progressive knowledge tracing: Modeling learning process from abstract to concrete

J Sun, M Wei, J Feng, F Yu, Q Li, R Zou - Expert Systems with Applications, 2024 - Elsevier
Artificial intelligence has the potential to revolutionize education by providing personalized
learning experiences that support the dream of “teaching students according to their …

Learning consistent representations with temporal and causal enhancement for knowledge tracing

C Huang, H Wei, Q Huang, F Jiang, Z Han… - Expert Systems with …, 2024 - Elsevier
Abstract Knowledge tracing is a crucial component of intelligent educational systems and
deep learning technologies have significantly propelled its advancement. However, most …

Intelligent machines as information and communication technology and their influence on sustainable marketing practices for beneficial impact on business …

RK Behera, A Rehman, MS Islam, FA Abbasi… - Journal of Cleaner …, 2024 - Elsevier
Intelligent machines are the machines or devices that make use of artificial intelligence and
robotics technologies. It has the ability to accomplish a specific task in the presence of …

Heterogeneous graph-based knowledge tracing with spatiotemporal evolution

H Yang, S Hu, J Geng, T Huang, J Hu, H Zhang… - Expert Systems with …, 2024 - Elsevier
Abstract Knowledge tracing (KT), in which the future performance of students is estimated by
tracing their knowledge states based on their responses to exercises, is widely applied in …

Knowledge tracing via multiple-state diffusion representation

K Zhang, T Ji, H Zhang - Expert Systems with Applications, 2024 - Elsevier
Abstract Knowledge tracing aims to supervise students' gras** of concepts, inferring their
knowledge states, and predicting their future performance. Current research predominantly …

Fusing hybrid attentive network with self-supervised dual-channel heterogeneous graph for knowledge tracing

T Wu, Q Ling - Expert Systems with Applications, 2023 - Elsevier
Recently the large-scale influence of Covid-19 promoted the fast development of intelligent
tutoring systems (ITS). As a major task of ITS, Knowledge Tracing (KT) aims to capture a …

Explore Bayesian analysis in Cognitive-aware Key–Value Memory Networks for knowledge tracing in online learning

J Zhang, R **a, Q Miao, Q Wang - Expert Systems with Applications, 2024 - Elsevier
Abstract Knowledge Tracing is a crucial aspect of personalized learning that aims to track
the evolving knowledge states of students with respect to one or more concepts. However …

Target hierarchy-guided knowledge tracing: Fine-grained knowledge state modeling

X Sun, K Zhang, S Shen, F Wang, Y Guo… - Expert Systems with …, 2024 - Elsevier
Abstract Knowledge Tracing (KT) focuses on modeling the exercise process of students,
assessing their knowledge state changes during the exercise process, and further providing …

Heterogeneous Evolution Network Embedding with Temporal Extension for Intelligent Tutoring Systems

S Liu, S Liu, Z Yang, J Sun, X Shen, Q Li… - ACM Transactions on …, 2023 - dl.acm.org
Graph embedding (GE) aims to acquire low-dimensional node representations while
maintaining the graph's structural and semantic attributes. Intelligent tutoring systems (ITS) …

csKT: Addressing cold-start problem in knowledge tracing via kernel bias and cone attention

Y Bai, X Li, Z Liu, Y Huang, T Guo, M Hou, F **a… - Expert Systems with …, 2025 - Elsevier
Abstract Knowledge tracing (KT) is the task of predicting students' future performances
based on their past interactions in online learning systems. When new students enter the …