Reasons associated with preservice teachers’ intention to use immersive virtual reality in education

Bower, Matt; DeWitt, Dorothy; Lai, Jennifer W. M.

doi:10.1111/bjet.13009

Cited by 110 publications

(91 citation statements)

References 48 publications

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“…In other words, increasing the enjoyment of using mobile apps for science teaching and the degree of focus on the effectiveness of using mobile apps strengthens teachers' attitudes, which in turn strengthens their intention to use mobile apps in science teaching. These results are consistent with some studies that identified the prominent role of the perceived enjoyment and concentration in explaining teachers’ technology acceptance in education (Bower et al, 2020 ; Hu et al, 2020 ). Therefore, the study made important contributions to the literature by revealing the importance of these crucial constructs’ relationships within the context of using mobile applications in science teaching.…”

Section: Discussionsupporting

confidence: 92%

“…Finally, perceived control is defined as the level of an individual’s control over the environment and the individual’s actions (Koufaris, 2002 ). The study by Bower et al ( 2020 ) and Hu et al (Hu et al, 2020 ) state that perceived enjoyment is a key motivator for influencing teachers’ attitude toward the use technology and, ultimately, teachers’ intentions to use it. Similarly, perceived control is described as one of the constructs that most influences teachers’ intentions to use technology (Somchai & Damnoen, 2020 ; Teo et al, 2016 ).…”

Section: Literature Review and Study Hypothesesmentioning

confidence: 99%

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Drivers of teachers’ intentions to use mobile applications to teach science

Ateş

Garzón

2021

Educ Inf Technol

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Using mobile applications in science education has proven to be effective as it adds multiple benefits including learning gains, motivation to learn, and collaborative learning. However, some teachers are reluctant to use this technology for reasons derived from different factors. Hence, it is important to identify what factors affect teachers’ intentions to use mobile applications, in order to take actions aiming to encourage them to use this technology in their classes. Accordingly, this study proposes a model to predict science teachers’ intentions to use mobile applications in the teaching process. Our model merges the Technology Acceptance Model, the Flow Theory, and the Theory of Planned Behavior. It includes 11 hypotheses that were tested with 1203 pre-service and in-service science teachers from different cities in Turkey. Additionally, the study investigates the mediating role of attitude and perceived usefulness on teachers’ intentions to use mobile apps. Further, it examines the moderating role of the sample type on teachers’ behavioral intentions. The results indicate that all 11 hypotheses were significant to explain teachers’ intentions to use mobile applications. Finally, the study raises theoretical and practical implications to guide stakeholders to undertake actions to enrich educational settings through the use of mobile applications.

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Section: Discussionsupporting

confidence: 92%

Section: Literature Review and Study Hypothesesmentioning

confidence: 99%

Drivers of teachers’ intentions to use mobile applications to teach science

Ateş

Garzón

2021

Educ Inf Technol

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“…Hedonistic advantages of the technology likely play a more important role in private contexts than, e.g., its usefulness. However, the hedonistic motivation was rated highest by prospective preservice teachers compared to all other aspects in the study of Bower et al [32]. Herz and Rauschnabel [33] focused their research in the consumer context on the technology-specific aspects of wearability, immersion, and user concerns.…”

Section: 2mentioning

confidence: 99%

Which Factors Promote and Inhibit the Technology Acceptance of Immersive Virtual Reality Technology in Teaching-Learning Contexts? Results of an Expert Survey

Pletz

2021

Int. J. Emerg. Technol. Learn.

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Although immersive virtual reality (IVR) is now accessible for large-scale use due to rapid technological developments, there appear to be few organizations in the German-speaking countries that are already actively using this technology on a large scale in education and training. Therefore, little is known about the technology acceptance. Questions arise as to how the technology acceptance can be explained and which technology-specific influencing factors can be identified in the field of training. 15 persons from 13 organizations, who are experienced with use of IVR in teaching-learning contexts such as training, were interviewed in an expert survey to identify promoting and inhibiting aspects of the technology acceptance of IVR in teaching-learning contexts. The results provide information about personal, organizational and technology-related promoting and inhibiting aspects for trainers and training participants. Furthermore, general aspects which are decisive for future use in the companies are derived.

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“…Even if UTAU2 was developed in 2012, it is still a fashionable framework in a large variety of fields, like Internet of Things (IoT) (Alkawsi et al , 2020), autonomous vehicles, m-banking (Lin et al , 2020) but also virtual reality (VR) in education (Bower et al , 2020), e-learning (Almaiah and Alyoussef, 2019) or m-learning (Kumar et al , 2020). Each domain we mention before has particularities, and the generic UTAUT2 requires customization in accordance.…”

Section: Introductionmentioning

confidence: 99%

Mobile learning acceptance and use in higher education during social distancing circumstances: an expansion and customization of UTAUT2

Sitar‐Tăut

Mican

2021

OIR

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PurposeThis paper investigates if the existing degree of students' acceptance and use of mobile or m-learning may face the online shift determined by SARS-CoV-2. Based on the extended unified theory of acceptance and use of technology (UTAUT2), a new comprehensive model, SD-UTAUT (social distancing-UTAUT), is developed to better understand relationships between the original constructs, plus personal innovativeness (PI) and information quality (IQ). It identifies the key factors affecting behavioral intention (BI) and use by examining the influence of revaluated hedonic motivation (HM) and learning value (LV) importance as mediators.Design/methodology/approachThe paper opted for an exploratory study involving 311 learners, using partial least squares structural equation modeling (PLS-SEM).FindingsSD-UTAUT can be a new m-learning model in higher education. It has high predictive power and confirmed 15 out of 16 hypotheses. The most powerful relationship is between performance expectancy (PE) and HM. IQ affected LV the most, since HM the behavioral use (BU). HM impacts the use behavior (UB) more than LV, but habit (HT) affects it the most.Research limitations/implicationsBecause of the pandemic context, output may lack generalizability and reproducibility.Practical implicationsTo improve usage, staff must provide better support, course creators emphasize the objectives and competencies and developers integrate innovation. The joy and pleasure of m-learning use may stimulate the LV through interesting and interactive content, like incorporating gamification.Originality/valueThe model set-up and circumstances are previously unseen. SD-UTAUT confirms ten new hypotheses and introduces the student's grade point average (GPA) as a moderator.Peer reviewThe peer review history for this article is available at https://publons.com/publon/10.1108/OIR-01-2021-0017

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Reasons associated with preservice teachers’ intention to use immersive virtual reality in education

Cited by 110 publications

References 48 publications

Drivers of teachers’ intentions to use mobile applications to teach science

Drivers of teachers’ intentions to use mobile applications to teach science

Which Factors Promote and Inhibit the Technology Acceptance of Immersive Virtual Reality Technology in Teaching-Learning Contexts? Results of an Expert Survey

Mobile learning acceptance and use in higher education during social distancing circumstances: an expansion and customization of UTAUT2

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