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Time series analysis for education: Methods, applications, and future directions
Recent advancements in the collection and analysis of sequential educational data have
brought time series analysis to a pivotal position in educational research, highlighting its …
brought time series analysis to a pivotal position in educational research, highlighting its …
Learning consistent representations with temporal and causal enhancement for knowledge tracing
Abstract Knowledge tracing is a crucial component of intelligent educational systems and
deep learning technologies have significantly propelled its advancement. However, most …
deep learning technologies have significantly propelled its advancement. However, most …
XKT: towards explainable knowledge tracing model with cognitive learning theories for questions of multiple knowledge concepts
Deep learning (DL) based knowledge tracing (KT) models have challenges for
uninterpretable prediction and parameter representation in educational applications, though …
uninterpretable prediction and parameter representation in educational applications, though …
PTADisc: a cross-course dataset supporting personalized learning in cold-start scenarios
The focus of our work is on diagnostic tasks in personalized learning, such as cognitive
diagnosis and knowledge tracing. The goal of these tasks is to assess students' latent …
diagnosis and knowledge tracing. The goal of these tasks is to assess students' latent …
Calibrated q-matrix-enhanced deep knowledge tracing with relational attention mechanism
With the development of online educational platforms, numerous research works have
focused on the knowledge tracing task, which relates to the problem of diagnosing the …
focused on the knowledge tracing task, which relates to the problem of diagnosing the …
Response speed enhanced fine-grained knowledge tracing: A multi-task learning perspective
The primary objective of knowledge tracing (KT) is to trace learners' changing knowledge
states and predict their future performance by analyzing their learning trajectories. One of …
states and predict their future performance by analyzing their learning trajectories. One of …
Improving academic performance predictions with dual graph neural networks
Academic performance is a crucial issue in the field of Online learning analytics. While deep
learning-based models have made significant progress in the era of big data, many of these …
learning-based models have made significant progress in the era of big data, many of these …
Fusing hybrid attentive network with self-supervised dual-channel heterogeneous graph for knowledge tracing
Recently the large-scale influence of Covid-19 promoted the fast development of intelligent
tutoring systems (ITS). As a major task of ITS, Knowledge Tracing (KT) aims to capture a …
tutoring systems (ITS). As a major task of ITS, Knowledge Tracing (KT) aims to capture a …
Deep knowledge tracing incorporating a hypernetwork with independent student and item networks
Knowledge tracing (KT), the task of tracking the knowledge state of a student over time, has
been assessed actively by artificial intelligence researchers. Recent reports have described …
been assessed actively by artificial intelligence researchers. Recent reports have described …
Educational data mining: A systematic review on the applications of classical methods and deep learning until 2022
Educational Data Mining (EDM) is a research field that focuses on extracting valuable
insights and knowledge from data in the education sector. EDM exploits Data Mining (DM) …
insights and knowledge from data in the education sector. EDM exploits Data Mining (DM) …