[PDF][PDF] DGCD: An Adaptive Denoising GNN for Group-level Cognitive Diagnosis
Group-level cognitive diagnosis, pivotal in intelligent education, aims to effectively assess
grouplevel knowledge proficiency by modeling the learning behaviors of individuals within …
grouplevel knowledge proficiency by modeling the learning behaviors of individuals within …
Path-Specific Causal Reasoning for Fairness-aware Cognitive Diagnosis
Cognitive Diagnosis (CD), which leverages students and exercise data to predict students'
proficiency levels on different knowledge concepts, is one of fundamental components in …
proficiency levels on different knowledge concepts, is one of fundamental components in …
A survey of models for cognitive diagnosis: New developments and future directions
Cognitive diagnosis has been developed for decades as an effective measurement tool to
evaluate human cognitive status such as ability level and knowledge mastery. It has been …
evaluate human cognitive status such as ability level and knowledge mastery. It has been …
Enhancing Fairness in Meta-learned User Modeling via Adaptive Sampling
Meta-learning has been widely employed to tackle the cold-start problem in user modeling.
Similar to a guidebook for a new traveler, meta-learning significantly affects decision-making …
Similar to a guidebook for a new traveler, meta-learning significantly affects decision-making …
HeckmanCD: Exploiting Selection Bias in Cognitive Diagnosis
Cognitive diagnosis, a fundamental task in education assessments, aims to quantify the
students' proficiency level based on the historical test logs. However, the interactions …
students' proficiency level based on the historical test logs. However, the interactions …
Model-Agnostic Adaptive Testing for Intelligent Education Systems via Meta-learned Gradient Embeddings
The field of education has undergone a significant revolution with the advent of intelligent
systems and technology, which aim to personalize the learning experience, catering to the …
systems and technology, which aim to personalize the learning experience, catering to the …
Personalized Forgetting Mechanism with Concept-Driven Knowledge Tracing
Knowledge Tracing (KT) aims to trace changes in students' knowledge states throughout
their entire learning process by analyzing their historical learning data and predicting their …
their entire learning process by analyzing their historical learning data and predicting their …
Optimizing Student Ability Assessment: A Hierarchy Constraint-Aware Cognitive Diagnosis Framework for Educational Contexts
Cognitive diagnosis (CD) aims to reveal students' proficiency in specific knowledge
concepts. With the increasing adoption of intelligent education applications, accurately …
concepts. With the increasing adoption of intelligent education applications, accurately …
Collaborative Cognitive Diagnosis with Disentangled Representation Learning for Learner Modeling
Learners sharing similar implicit cognitive states often display comparable observable
problem-solving performances. Leveraging collaborative connections among such similar …
problem-solving performances. Leveraging collaborative connections among such similar …
Multi-dimensional ability diagnosis for machine learning algorithms
Conclusion We have proposed the cognitive diagnostic framework Camilla and a multi-
dimensional metric Ability for providing both interpretable and reliable assessment of …
dimensional metric Ability for providing both interpretable and reliable assessment of …