DyGKT: Dynamic Graph Learning for Knowledge Tracing

Author:

Cheng Ke1ORCID,Peng Linzhi1ORCID,Wang Pengyang2ORCID,Ye Junchen3ORCID,Sun Leilei1ORCID,Du Bowen3ORCID

Affiliation:

1. SKLSDE Lab, Beihang University, Beijing, China

2. SKL-IOTSC, Department of Computer and Information Science, University of Macau, Macau, China

3. School of Transportation Science and Engineering, Beihang University, Beijing, China

Funder

the Start-up Research Grant of University of Macau

Natural Science Foundation of China

Science and Technology Development Fund

S\&T Program of Hebei

Publisher

ACM

Reference40 articles.

1. Evolutionary dynamics of higher-order interactions in social networks

2. F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams

3. Jiahao Chen et al. 2023. Improving Interpretability of Deep Sequential Knowledge Tracing Models with Question-Centric Cognitive Representations. In Proceedings of the 37th AAAI Conference on Artificial Intelligence.

4. Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing

5. Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer

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