Evaluating the explainers: black-box explainable machine learning for student success prediction in MOOCs
Neural networks are ubiquitous in applied machine learning for education. Their pervasive
success in predictive performance comes alongside a severe weakness, the lack of …
success in predictive performance comes alongside a severe weakness, the lack of …
A deep learning approach for intrusion detection in internet of things using bi-directional long short-term memory recurrent neural network
Internet of Things (IoT) is one of the most rapidly evolving technologies nowadays. It has its
impact in various industrial sectors including logistics tracking, medical fields, automobiles …
impact in various industrial sectors including logistics tracking, medical fields, automobiles …
Biologically inspired protection of deep networks from adversarial attacks
A Nayebi, S Ganguli - arXiv preprint arXiv:1703.09202, 2017 - arxiv.org
Inspired by biophysical principles underlying nonlinear dendritic computation in neural
circuits, we develop a scheme to train deep neural networks to make them robust to …
circuits, we develop a scheme to train deep neural networks to make them robust to …
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 …
Improving sensor-free affect detection using deep learning
Affect detection has become a prominent area in student modeling in the last decade and
considerable progress has been made in developing effective models. Many of the most …
considerable progress has been made in developing effective models. Many of the most …
Deep knowledge tracing based on spatial and temporal representation learning for learning performance prediction
L Lyu, Z Wang, H Yun, Z Yang, Y Li - Applied Sciences, 2022 - mdpi.com
Knowledge tracing (KT) serves as a primary part of intelligent education systems. Most
current KTs either rely on expert judgments or only exploit a single network structure, which …
current KTs either rely on expert judgments or only exploit a single network structure, which …
Improving knowledge tracing with collaborative information
Knowledge tracing, which estimates students' knowledge states by predicting the probability
that they correctly answer questions, is an essential task for online learning platforms. It has …
that they correctly answer questions, is an essential task for online learning platforms. It has …
CMKT: Concept map driven knowledge tracing
In this article, we advocate for and propose a novel concept map driven knowledge tracing
(CMKT) model, which utilizes educational concept map for learner modeling. This article …
(CMKT) model, which utilizes educational concept map for learner modeling. This article …
[HTML][HTML] Learning from patient safety incidents in the emergency department: a systematic review
S Amaniyan, BO Faldaas, PA Logan… - The Journal of …, 2020 - Elsevier
Background Patient safety incidents are commonly observed in critical and high demanding
care settings, including the emergency department. There is a need to understand what …
care settings, including the emergency department. There is a need to understand what …
Multiple features fusion attention mechanism enhanced deep knowledge tracing for student performance prediction
D Liu, Y Zhang, JUN Zhang, Q Li, C Zhang… - IEEE Access, 2020 - ieeexplore.ieee.org
Student performance prediction is a fundamental task in online learning systems, which
aims to provide students with access to active learning. Generally, student performance …
aims to provide students with access to active learning. Generally, student performance …