we propose an interpretable knowledge tracing model (KVFKT) based on key-value and forgetting. This approach keeps trace of the students' knowledge state ...

A novel deep learning-based KT model is proposed, which explicitly utilizes the theories of learning and forgetting curves in updating knowledge states.

Mar 7, 2022 · This paper provides an interpretable cognitive model named HELP-DKT, which can infer how students learn programming based on deep knowledge tracing.

In this paper, we “open the box” of deep neural network based models for knowledge tracing. We aim to provide a better understanding of the DKT model and a more ...

Nov 4, 2023 · We introduce a convolutional attention mechanism to help the model perceive contextual information better. In addition, we simulate the forgetting phenomenon ...

Apr 25, 2024 · Abstract Knowledge Tracing (KT) aims to trace changes in students' knowledge states throughout their entire learning process by analyzing ...

May 13, 2024 · In this paper, we propose an interpretable deep KT model, referred to as fuzzy deep knowledge tracing (FDKT) via fuzzy reasoning.

Deep-IRT is a synthesis of the item response theory (IRT) model and a knowledge tracing model that is based on the deep neural network architecture called ...

Nov 21, 2023 · This paper aims to tackle the fundamental challenges of KT tasks, including the knowledge state representation and the core architecture design.

Deep-learning-based KT models perform remarkably better than traditional KT and have attracted considerable attention. However, most of them lack ...