Improving interpretability of deep sequential knowledge tracing models with question-centric cognitive representations
Abstract Knowledge tracing (KT) is a crucial technique to predict students' future
performance by observing their historical learning processes. Due to the powerful …
performance by observing their historical learning processes. Due to the powerful …
Evolutionary neural architecture search for transformer in knowledge tracing
Abstract Knowledge tracing (KT) aims to trace students' knowledge states by predicting
whether students answer correctly on exercises. Despite the excellent performance of …
whether students answer correctly on exercises. Despite the excellent performance of …
pyKT: a python library to benchmark deep learning based knowledge tracing models
Abstract Knowledge tracing (KT) is the task of using students' historical learning interaction
data to model their knowledge mastery over time so as to make predictions on their future …
data to model their knowledge mastery over time so as to make predictions on their future …
Enhancing deep knowledge tracing with auxiliary tasks
Knowledge tracing (KT) is the problem of predicting students' future performance based on
their historical interactions with intelligent tutoring systems. Recent studies have applied …
their historical interactions with intelligent tutoring systems. Recent studies have applied …
Xes3g5m: A knowledge tracing benchmark dataset with auxiliary information
Abstract Knowledge tracing (KT) is a task that predicts students' future performance based
on their historical learning interactions. With the rapid development of deep learning …
on their historical learning interactions. With the rapid development of deep learning …
HHSKT: A learner–question interactions based heterogeneous graph neural network model for knowledge tracing
Abstract Knowledge tracing (KT) has evolved into a crucial component of the online
education system with the rapid development of online adaptive learning. A key component …
education system with the rapid development of online adaptive learning. A key component …
Ability boosted knowledge tracing
Abstract Knowledge tracing (KT) has become an increasingly relevant problem in intelligent
education services, which estimates and traces the degree of learner's mastery of concepts …
education services, which estimates and traces the degree of learner's mastery of concepts …
What is wrong with deep knowledge tracing? Attention-based knowledge tracing
X Wang, Z Zheng, J Zhu, W Yu - Applied Intelligence, 2023 - Springer
Scientifically and effectively tracking student knowledge states is a significant and
fundamental task in personalized education. Many neural network-based models, eg, deep …
fundamental task in personalized education. Many neural network-based models, eg, deep …
[HTML][HTML] HiTSKT: A hierarchical transformer model for session-aware knowledge tracing
Abstract Knowledge tracing (KT) aims to leverage students' learning histories to estimate
their mastery levels on a set of pre-defined skills, based on which the corresponding future …
their mastery levels on a set of pre-defined skills, based on which the corresponding future …
Empirical evaluation of deep learning models for knowledge tracing: Of hyperparameters and metrics on performance and replicability
We review and evaluate a body of deep learning knowledge tracing (DLKT) models with
openly available and widely-used data sets, and with a novel data set of students learning to …
openly available and widely-used data sets, and with a novel data set of students learning to …