Desktop vs. mobile: A comparative study of augmented reality systems for engineering visualizations in education

Camba, Jorge D.; Contero, Manuel; Salvador-Herranz, Gustavo

doi:10.1109/fie.2014.7044138

Cited by 35 publications

(15 citation statements)

References 25 publications

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“…One study revealed that users prefer more the use of a desktop AR system than mobile system in that the desktop AR system gained significant positive feedback in terms of responsiveness of the AR application. 24 In order to have better quality illustration by using smartphones, the users may need a higher specification smartphone which is costly. Hence, a new Vector PC AR system (VPCAR) will be proposed in this study to aid educators and students in their teaching-learning process with the following objectives.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrating augmented reality technology in education: vector personal computer augmented reality

Tan

Tay

2021

F1000Res

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Background: Educators often face difficulties in explaining abstract concepts such as vectors. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, fully online classes have also caused additional challenges to using conventional teaching methods. To explain a vector concept of more than 2 dimensions, visualization becomes a problem. Although Microsoft PowerPoint can integrate animation, the illustration is still in 2-dimensions. Augmented reality (AR) technology is recommended to aid educators and students in teaching-learning vectors, namely via a vector personal computer augmented reality system (VPCAR), to fulfil the demand for tools to support the learning and teaching of vectors. Methods: A PC learning module for vectors was developed in a 3-dimensional coordinate system by using AR technology. Purposive sampling was applied to get feedback from educators and students in Malaysia through an online survey. The supportiveness of using VPCAR based on six items (attractiveness, easiness, visualization, conceptual understanding, inspiration and helpfulness) was recorded on 5-points Likert-type scales. Findings are presented descriptively and graphically. Results: Surprisingly, both students and educators adapted to the new technology easily and provided significant positive feedback that showed a left-skewed and J-shaped distribution for each measurement item, respectively. The distributions were proven significantly different among the students and educators, where supportive level result of educators was higher than students. This study introduced a PC learning module other than mobile apps as students mostly use laptops to attend online class and educators also engage other IT tools in their teaching. Conclusions: Based on these findings, VPCAR provides a good prospect in supporting educators and students during their online teaching-learning process. However, the findings may not be generalizable to all students and educators in Malaysia as purposive sampling was applied. Further studies may focus on government-funded schools using the newly developed VPCAR system, which is the novelty of this study.

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Section: Literature Reviewmentioning

confidence: 99%

Integrating augmented reality technology in education: vector personal computer augmented reality

Tan

Tay

2021

F1000Res

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“…Abstract markers are very compatible with existing technologies such as QR codes and have an advantage over mechanical or ultrasonic markers. Abstract markers are easy to create and have been widely deployed in mixed reality environments as can be seen in Andujar et al (2011) and Camba et al (2014).…”

Section: Reclassification Into Simple Categoriesmentioning

confidence: 99%

A reclassification of markers for mixed reality environments

Onime

Uhomoibhi

Wang

et al. 2020

IJILT

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PurposeThis paper presents a reclassification of markers for mixed reality environments that is also applicable to the use of markers in robot navigation systems and 3D modelling. In the case of Augmented Reality (AR) mixed reality environments, markers are used to integrate computer generated (virtual) objects into a predominantly real world, while in Augmented Virtuality (AV) mixed reality environments, the goal is to integrate real objects into a predominantly virtual (computer generated) world. Apart from AR/AV classifications, mixed reality environments have also been classified by reality; output technology/display devices; immersiveness as well as by visibility of markers.Design/methodology/approachThe approach adopted consists of presenting six existing classifications of mixed reality environments and then extending them to define new categories of abstract, blended, virtual augmented, active and smart markers. This is supported with results/examples taken from the joint Mixed Augmented and Virtual Reality Laboratory (MAVRLAB) of the Ulster University, Belfast, Northern Ireland; the Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy and Santasco SrL, Regio Emilia/Milan, Italy.FindingsExisting classification of markers and mixed reality environments are mainly binary in nature and do not adequately capture the contextual relationship between markers and their use and application. The reclassification of markers into abstract, blended and virtual categories captures the context for simple use and applications while the categories of augmented, active and smart markers captures the relationship for enhanced or more complex use of markers. The new classifications are capable of improving the definitions of existing simple marker and markerless mixed reality environments as well as supporting more complex features within mixed reality environments such as co-location of objects, advanced interactivity, personalised user experience.Research limitations/implicationsIt is thought that applications and devices in mixed reality environments when properly developed and deployed enhances the real environment by making invisible information visible to the user. The current work only marginally covers the use of internet of things (IoT) devices in mixed reality environments as well as potential implications for robot navigation systems and 3D modelling.Practical implicationsThe use of these reclassifications enables researchers, developers and users of mixed reality environments to select and make informed decisions on best tools and environment for their respective application, while conveying information with additional clarity and accuracy. The development and application of more complex markers would contribute in no small measure to attaining greater advancements in extending current knowledge and developing applications to positively impact entertainment, business and health while minimizing costs and maximizing benefits.Originality/valueThe originality of this paper lies in the approach adopted in reclassifying markers. This is supported with results and work carried out at the MAV Reality Laboratory of Ulster University, Belfast–UK, the Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste-Italy and Santasco SrL, Regio Emilia, Milan–Italy. The value of present research lies in the definitions of new categories as well as the discussions of how they improve mixed reality environments and application especially in the health and education sectors.

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“…Thus, there is a growing interest among MAR experts to enhance the learning experience, engagement, effectiveness, acceptance of MAR use in science education. Content analysis identifies more than 20 previous studies between 2008-2019 on the application of MAR in science learning [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [49], and [50]. Though, there are studies indicated that AR in science is capable as a teaching tool which suits a classroom learning [23], [23], [24], [25], [26] and [27].…”

Section: Introductionmentioning

confidence: 99%

Development of the MARPEX App Embedding the Mobile Augmented Reality Factors for Learning Motivation in Science Experiments

Gopalan

Bakar

Zulkifli

2020

Int. J. Interact. Mob. Technol.

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Mobile Augmented Reality (MAR) has grown exponentially over the last four decades from imagination to real physical experience, especially in education. Previously, experts have completed the concepts of effectiveness, usability, acceptance and understanding in designing MAR applications to introduce and expose technological advances. However, most of these applications are addressed extensively for classroom science learning, while science experiments receive little attention. Students have to go through difficulties in understanding the phenomena of science and consequently become dissatisfied with their grasp on basic knowledge and eventually cannot pursue higher education or career related to science. This paper presents the development of Mobile Augmented Reality for Physics (MARPEX) application for high school students. The purpose of this application is to enhance the learning motivation in science experiments through the content of modern science. It aims to provide an individual learning experience for each student in science experiments. The MARPEX app design has gone through several phases of filtering and evaluation based on the specified objectives. This application needs to maintain the factors necessary to achieve this goal. This app has been designed and developed specifically for science (physics) experiments on the topic of electromagnetism. The application encrypts several experimental instances with the addition of good visualization to understand this phenomenon and has real-life experimental experience<strong>.</strong>

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Desktop vs. mobile: A comparative study of augmented reality systems for engineering visualizations in education

Cited by 35 publications

References 25 publications

Integrating augmented reality technology in education: vector personal computer augmented reality

Integrating augmented reality technology in education: vector personal computer augmented reality

A reclassification of markers for mixed reality environments

Development of the MARPEX App Embedding the Mobile Augmented Reality Factors for Learning Motivation in Science Experiments

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