CK Yeung - arXiv preprint arXiv:1904.11738, 2019 - arxiv.org
… 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 knowledgetracing …
S Pandey, G Karypis - arXiv preprint arXiv:1907.06837, 2019 - arxiv.org
… Attentive KnowledgeTracing (SAKT). Extensive experimentation on a variety of real-world dataset shows that our model outperforms the state-of-the-art models for knowledgetracing, …
… ’s knowledge by considering their forgetting behavior. We extend the deepknowledgetracing model [17], which is a state-of-the-art sequential model for knowledgetracing, to consider …
… the interaction Ii in SAINT, we will use interaction embeddings in Transformer-based variants of deepknowledgetracing models for comparison. Deep Self-Attentive Encoder-Decoder …
… We also compare it to several state-of-the-art machine learning and deep learning KnowledgeTracing 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 deepknowledgetracing that often ignore the question index and summarize learner performance as (c i t ,ri t ). This choice …
G Abdelrahman, Q Wang - Proceedings of the 42nd international ACM …, 2019 - dl.acm.org
… 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 knowledgetracing, namely …
H Nakagawa, Y Iwasawa, Y Matsuo - IEEE/WIC/ACM International …, 2019 - dl.acm.org
… knowledgetracing model as a relational inductive bias can improve its performance; however, previous methods, such as deepknowledgetracing, … benefits into knowledgetracing, we …
… Visualization of knowledgetracing results. As indicated in Figure 4, we present two … knowledgetracing results on dataset ASSIST2009. The upper part of Figure 4 gives the knowledge …