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Virtual reality systems enhance students’ achievements in engineering education

Alhalabi, Wadee·2016·Behaviour & Information Technology

Abstract

Virtual reality (VR) is being used for many applications, ranging from medicine to space and from entertainment to training. In this research paper, VR is applied in engineering education, the scope being to compare three major VR systems with the traditional education approach when we do not use any VR system (No-VR). The Corner Cave System (CCS) is compared with the Head Mounted Display (HMD) system. Both of these systems are using a tracking system to reflect the user movements in the virtual environment. The CCS uses only three coordinates: x-, y- and z-axis. The HMD system has six degrees of freedom, the x-, y- and z-axis, as well as the roll, pitch and yaw. Those two systems are also compared with HMD, as a standalone device (HMD-SA) without the tracking system where it has only roll, pitch and yaw. The objective of the study was to evaluate the impact of VR systems on the students’ achievements in engineering colleges. The research examined the effect of the four different methods and compared the scores of the students after each test. The experiments were ran over 48 students. Those systems show incredible results.

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Metadata

Authors
Alhalabi, W.
Venue
Behaviour & Information Technology
Published
2016-07-26
Volume
35
Issue
11
Pages
919-925
ISSN
  • 0144-929X (ISSN-L)
  • 1362-3001
OpenAlex
W2488224585
Cited by
370
References
0
FWCI
22.97
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Virtual reality systems enhance students’ achievements in engineering education. https://app.cochat.ai/papers/10.1080/0144929x.2016.1212931
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Alhalabi, W. (2016). Virtual reality systems enhance students’ achievements in engineering education. Behaviour & Information Technology. https://doi.org/10.1080/0144929x.2016.1212931

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.