… framework called Joint graph convolutional network deep Knowledge Tracing (JKT), which
… information of students’ learning states at higher levels in the knowledge tracing process. …

… Deep-IRT which is a synthesis of the item response theory (IRT) model and a knowledge
tracing model that is based on the deep … ) to make deep learning based knowledge tracing …

… Attentive Knowledge Tracing (SAKT). Extensive experimentation on a variety of real-world
dataset shows that our model outperforms the state-of-the-art models for knowledge tracing, …

… ’s knowledge by considering their forgetting behavior. We extend the deep knowledge tracing
model [17], which is a state-of-the-art sequential model for knowledge tracing, to consider …

… the interaction Ii in SAINT, we will use interaction embeddings in Transformer-based
variants of deep knowledge tracing models for comparison. Deep Self-Attentive Encoder-Decoder …

… We also compare it to several state-of-the-art machine learning and deep learning
Knowledge Tracing models. To fully evaluate the performance of Bi-CLKT, we conducted a large …

… We note that this setup is different from some prior works on deep knowledge tracing that
often ignore the question index and summarize learner performance as (c i t ,ri t ). This choice …

… Although these deep learning models have shown promising … go deeper to trace how specific
concepts in a knowledge state … a novel deep learning model for knowledge tracing, namely …

… knowledge tracing model as a relational inductive bias can improve its performance; however,
previous methods, such as deep knowledge tracing, … benefits into knowledge tracing, we …

… Visualization of knowledge tracing results. As indicated in Figure 4, we present two …
knowledge tracing results on dataset ASSIST2009. The upper part of Figure 4 gives the knowledge …