We propose CX-ToM, short for counterfactual explanations with theory-of-mind, a new
explainable AI (XAI) framework for explaining decisions made by a deep convolutional …

Laboratories in education are the ideal place where students practice the concepts by doing.
The cost-efficient laboratory enhances the learning of students by exploring the concepts …

Attention based explanations (viz. saliency maps), by providing interpretability to black box
models such as deep neural networks, are assumed to improve human trust and reliance in …

The wide avai lability of smart handheld and mobile devices has provided educators with
another opportunity to aid the teaching of electromagnetics (EM) courses with touchbased …

Undergraduate courses in electrical machines often include an introduction to their magnetic
circuits and to the various magnetic materials used in their construction and their properties …

In recent decades, artificial intelligence (AI) systems are becoming increasingly ubiquitous
from low risk environments to high risk environments such as chatbots, medical-diagnosis …

In this article, we present mobile teaching and learning of coupled-line structures using the
multiple-1D coupled-line finite-difference time-domain (M1D CL-FDTD) method. The …

This article presents the multiple 1D finite-difference time-domain (M1-D FDTD) methods for
mobile interactive teaching and learning of wave propagation in transmission lines (TLs) …

An explainable AI (XAI) model aims to provide transparency (in the form of justification,
explanation, etc) for its predictions or actions made by it. Recently, there has been a lot of …

Convenience internet access and ubiquitous computing have opened up new avenues for
learning and teaching. They are now no longer confined to the classroom walls, but are …