AMBER
An adaptive meta-balancing framework for integrating heterogeneous graph signals in knowledge tracing.
Learning-state estimation
Knowledge Tracing
We study learner-state estimation through uncertainty, heterogeneous graph structure, and interpretable representations. This area connects the AMBER implementation and current publication records so researchers can move from a method overview to primary evidence and reproduction materials.
Projects and implementations
1 worksPublications
3 papersInterpretable Knowledge Tracing via Explicit-Implicit Alignment
E Ni, J Wang, J Luan, et al.
AMBER: Adaptive Meta Balanced Paradigm for Heterogeneous Graph-Based Knowledge Tracing
L Sun, Z Yuan, E Ni, et al.
Uncertainty-Aware Knowledge Tracing
W Cheng, H Du, C Li, et al.