Application of the Extended Reality Technology for Teaching New Languages: A Systematic Review

Tegoan, Noura; Wibowo, Santoso; Grandhi, Srimannarayana

doi:10.3390/app112311360

Cited by 12 publications

(6 citation statements)

References 30 publications

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“…Consequently, they are unable to replicate the experience of tradetional learning (Dwivedi et al, 2022 ). Supporting this, it is found that virtual technologies such as virtual reality (VR), augmented reality (AR), extended reality (XR), and mixed reality (MR), do not, on their own, guarantee positive learning results (Marks & Thomas, 2022 ; Tegoan et al, 2021 ) due to issues related to the multisensory experiences of students in terms of teaching content quality and the appropriateness of realistic dynamic interactions. Therefore, the utilization of metaverse technology in education has the ability to enhance the online learning experience and make it simpler for educational service providers to establish virtual classrooms that imitate traditional classrooms (Teng et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

“Extending the Technology Acceptance Model (TAM) to Predict University Students’ Intentions to Use Metaverse-Based Learning Platforms”

Al-Adwan

et al. 2023

Educ Inf Technol

174

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Metaverse, which combines a number of information technologies, is the Internet of the future. A media for immersive learning, metaverse could set future educational trends and lead to significant reform in education. Although the metaverse has the potential to improve the effectiveness of online learning experiences, metaverse-based educational implementations are still in their infancy. Additionally, what factors impact higher education students’ adoption of the educational metaverse remains unclear. Consequently, the aim of this study is to explore the main factors that affect higher education students’ behavioral intentions to adopt metaverse technology for education. This study has proposed an extended Technology Acceptance Model (TAM) to achieve this aim. The novelty of this study resides in its conceptual model, which incorporates both technological, personal, and inhibiting/enabling factors. The empirical data were collected via online questionnaires from 574 students in both private and public universities in Jordan. Based on the PLS-SEM analysis, the study identifies perceived usefulness, personal innovativeness in IT, and perceived enjoyment as key enablers of students’ behavioral intentions to adopt the metaverse. Additionally, perceived cyber risk is found as the main inhibitor of students’ metaverse adoption intentions. Surprisingly, the effect of perceived ease of use on metaverse adoption intentions is found to be insignificant. Furthermore, it is found that self-efficacy, personal innovativeness, and perceived cyber risk are the main determinants of perceived usefulness and perceived ease of use. While the findings of this study contribute to the extension of the TAM model, the practical value of these findings is significant since they will help educational authorities understand each factor’s role and enable them to plan their future strategies.

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Section: Introductionmentioning

confidence: 99%

“Extending the Technology Acceptance Model (TAM) to Predict University Students’ Intentions to Use Metaverse-Based Learning Platforms”

Al-Adwan

et al. 2023

Educ Inf Technol

174

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“…However, VR/AR/MR on its own does not ensure positive learning outcomes [53,54], and factors that affect the effectiveness of VR/AR/MR in education have been well documented in the literature. Based on the presence theory [55] and regulatory focus theory [56], Sun et al [57] found that promotion focus (i.e., the tendency focuses on the positive presence) positively affects students' satisfaction, perceived efficiency, and overall usability perception toward VR-based learning, whereas involvement (i.e., a psychological state that focuses an individual's attention on a coherent set of activities) and promotion focus positively affect students' perceived effectiveness of VR.…”

Section: Vr/ar/mr In Educationmentioning

confidence: 99%

“…Tegoan et al mentioned that although MR could enhance language learning, its effectiveness could be affected by privacy concerns, expensive costs, etc. [54].…”

Section: Vr/ar/mr In Educationmentioning

confidence: 99%

Factors Affecting Learners’ Adoption of an Educational Metaverse Platform: An Empirical Study Based on an Extended UTAUT Model

Teng

Cai

Gao

et al. 2022

Mobile Information Systems

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This study examined the factors affecting learners’ adoption of an educational metaverse platform using an extended UTAUT (unified theory of acceptance and use of technology) model and incorporating perceived risk. Data were derived from a survey of 495 respondents from China and analyzed using structural equation modeling. The results revealed that (i) performance expectancy, effort expectancy, social influence, and facilitating conditions had significantly positive effects on learners’ satisfaction with the Eduverse; (ii) learners’ satisfaction had a positive effect on their continued usage intention; (iii) learners’ intention to use the Eduverse was reduced after they perceived risks. Our study provided empirical evidence of the validity of the UTAUT model in explaining learners’ adoption of the Eduverse. Our findings have significant practical implications for enterprises, educational institutions, and governments.

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“…The Metaverse embodies a convergence of web technologies, the internet, VR, AR, mixed reality (MR), and extended reality (XR). According to [21], MR fuses the physical and digital worlds to some degree while combining the technologies of VR and AR into one, while XR universally refers to all these immersive technologies [22].…”

Section: Introductionmentioning

confidence: 99%

Prospects and challenges of Metaverse application in data‐driven intelligent transportation systems

Njoku

Nwakanma

Amaizu

et al. 2022

IET Intelligent Trans Sys

133

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The Metaverse is a concept used to refer to a virtual world that exists in parallel to the physical world. It has grown from a conceptual level to having real applications in virtual reality games. The applicability of the Metaverse in numerous sectors like marketing, education, social, and even advertising exists. However, there exists little or no work on Metaverse applicability to the transportation industry. Data‐driven intelligent transportation systems (DDITS) aim to provide more intelligent systems based on exploiting data. This paper reviews the concepts and features of the Metaverse. Also, the review goes over three dominant DDITS challenges: vehicle fault detection and repair, testing new technologies, and anti‐theft systems. In addition, it highlights prospective Metaverse solutions that apply to the DDITS. Buttressing the utility of Metaverse in DDITS, this paper presents two major case studies: the invisible to visible (I2V) and the Metaverse on Wheels (MoW) technologies. Finally, the influence, limitations, and open issues of Metaverse applications to DDITS are discussed.

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Application of the Extended Reality Technology for Teaching New Languages: A Systematic Review

Cited by 12 publications

References 30 publications

“Extending the Technology Acceptance Model (TAM) to Predict University Students’ Intentions to Use Metaverse-Based Learning Platforms”

“Extending the Technology Acceptance Model (TAM) to Predict University Students’ Intentions to Use Metaverse-Based Learning Platforms”

Factors Affecting Learners’ Adoption of an Educational Metaverse Platform: An Empirical Study Based on an Extended UTAUT Model

Prospects and challenges of Metaverse application in data‐driven intelligent transportation systems

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