Khosravi, S., Bailey, S. G., Parvizi, H. and Ghannam, R. (2022) Wearable sensors for learning enhancement in higher education. Sensors, 22(19), 7633. (doi: 10.3390/s22197633) (PMID:36236732) (PMCID:PMC9573685)
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Abstract
Wearable sensors have traditionally been used to measure and monitor vital human signs for well-being and healthcare applications. However, there is a growing interest in using and deploying these technologies to facilitate teaching and learning, particularly in a higher education environment. The aim of this paper is therefore to systematically review the range of wearable devices that have been used for enhancing the teaching and delivery of engineering curricula in higher education. Moreover, we compare the advantages and disadvantages of these devices according to the location in which they are worn on the human body. According to our survey, wearable devices for enhanced learning have mainly been worn on the head (e.g., eyeglasses), wrist (e.g., watches) and chest (e.g., electrocardiogram patch). In fact, among those locations, head-worn devices enable better student engagement with the learning materials, improved student attention as well as higher spatial and visual awareness. We identify the research questions and discuss the research inclusion and exclusion criteria to present the challenges faced by researchers in implementing learning technologies for enhanced engineering education. Furthermore, we provide recommendations on using wearable devices to improve the teaching and learning of engineering courses in higher education.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Khosravi, Sara and Ghannam, Professor Rami |
Authors: | Khosravi, S., Bailey, S. G., Parvizi, H., and Ghannam, R. |
College/School: | College of Arts & Humanities > School of Culture and Creative Arts College of Science and Engineering College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering |
Journal Name: | Sensors |
Publisher: | MDPI |
ISSN: | 1424-8220 |
ISSN (Online): | 1424-8220 |
Published Online: | 08 October 2022 |
Copyright Holders: | Copyright © 2022 by the authors |
First Published: | First published in Sensors 22(19): 7633 |
Publisher Policy: | Reproduced under a Creative Commons License |
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