A survey of knowledge graph approaches and applications in education

K Qu, KC Li, BTM Wong, MMF Wu, M Liu - Electronics, 2024 - mdpi.com
This paper presents a comprehensive survey of knowledge graphs in education. It covers
the patterns and prospects of research in this area. A total of 48 relevant publications …

Graph neural network based intelligent tutoring system: a survey

J Pu, S Li, M Guo, X Chen, Z ** rapidly driven by artificial intelligence technology. The
massive learning resources lead to information overload and low resource utilization …

[HTML][HTML] Knowledge ontology enhanced model for explainable knowledge tracing

Y Wang, Y Huo, C Yang, X Huang, D **a… - Journal of King Saud …, 2024 - Elsevier
Abstract Knowledge Tracing (KT) aims to predict learners' future learning outcomes based
on their past learning interactions. Deep Knowledge Tracing (DKT) is a technology …

Multi-Modal Parameter-Efficient Fine-tuning via Graph Neural Network

B Cheng, J Lu - arxiv preprint arxiv:2408.00290, 2024 - arxiv.org
With the advent of the era of foundation models, pre-training and fine-tuning have become
common paradigms. Recently, parameter-efficient fine-tuning has garnered widespread …

MEGKT: Multi-edge Features Enhancement for Graph-Based Knowledge Tracing

L Zhang, L Zhao, Z Zhang - Asia-Pacific Web (APWeb) and Web-Age …, 2024 - Springer
Abstract Knowledge tracing (KT) captures the mastery status and proficiency level of
students by modeling the answer information in their historical answering records, and then …

Enhancement for Graph-Based Knowledge

L Zhang, L Zhao, Z Zhang - Web and Big Data. APWeb-WAIM 2024 … - books.google.com
Knowledge tracing (KT) captures the mastery status and proficiency level of students by
modeling the answer information in their historical answering records, and then predicts …