|
UPSI Digital Repository (UDRep)
|
|
|
|
||||||||||||||||||||||||||||||
| Abstract : Universiti Pendidikan Sultan Idris |
| The evaluation of information systems (IS) models, which are employed to research the adoption or acceptance of metaverse systems, is thought to be a subject of major significance. Studying the adoption or acceptability of the metaverse system is not a recent study area, and many academics have taken on the task. We should be acquainted with the leading IS models used in this study trend to assess these models and give academics a comprehensive understanding of this study trend. The primary goal of this research, in contrast to previous reviews, is to systematically evaluate the metaverse research in education from the viewpoint of IS theories/models to offer a thorough pointer that might help the scholars to carry out additional research in metaverse acceptance. A total of 41 research that was published between 2011 and 2022 were examined in the present systematic review. The main study results showed that the Technology Acceptance Model (TAM) is recognized as the most widely used model in forecasting people’s intentions to uphold the metaverse system. Furthermore, it was discovered that SmartPLS (PLS-SEM) is a typical tool for validating metaverse models. In addition, the key research purpose covered in the bulk of the reviewed research is to study how students adopt or accept the metaverse system and the technology that supports it. Additionally, most of the research that was gathered was done in China, Taiwan, and the USA, accordingly. Additionally, in most of the evaluated research, it was discovered that university students were the primary respondents concerning data acquisition. These findings are anticipated to significantly improve both our comprehension of metaverse system study and the utilization of IS models. © Beijing Normal University 2022. |
| References |
Al-Maroof, R., Al-Qaysi, N., Salloum, S. A., & Al-Emran, M. (2021). Blended learning acceptance: a systematic review of information systems models. Technology, Knowledge and Learning. https://doi.org/10.1007/s10758-021-09519-0 AL-Oudat, M., & Altamimi, A. (2022). Factors influencing behavior intentions to use virtual reality in education. International Journal of Data and Network Science, 6(3), 733–742. https://doi.org/10.5267/j.ijdns.2022.3.008 Alawadhi, M., Alhumaid, K., Almarzooqi, S., Aljasmi, Sh., Aburayya, A., Salloum, S. A., & Almesmari, W. (2022). Factors affecting medical students’ acceptance of the metaverse system in medical training in the United Arab Emirates. SEEJPH. https://doi.org/10.11576/seejph-5759 Ally, M. (2009). Mobile learning: Transforming the delivery of education and training. Athabasca University Press. Almarzouqi, A., Aburayya, A., & Salloum, S. A. (2022). Prediction of user’s intention to use metaverse system in medical education: a hybrid SEM-ML learning approach. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3169285 Ando, Y., Thawonmas, R., & Rinaldo, F. (2013). Inference of viewed exhibits in a metaverse museum. International Conference on Culture and Computing, 2013, 218–219. https://doi.org/10.1109/CultureComputing.2013.73 Arcila, J. B. P. (2014). Metaversos Para el máster iberoamericano en educación en entornos virtuales. Etic@ Net. Revista Científica Electrónica De Educación y Comunicación En La Sociedad Del Conocimiento, 14(2), 227–248. https://doi.org/10.30827/eticanet.v14i2.11977 Atkins, D. E., Brown, J. S., & Hammond, A. L. (2007). A review of the open educational resources (OER) movement: Achievements, challenges, and new opportunities (Vol. 164). Creative common Mountain View. Barrett, A. J., Pack, A., & Quaid, E. D. (2021). Understanding learners’ acceptance of high-immersion virtual reality systems: Insights from confirmatory and exploratory PLS-SEM analyses. Computers & Education, 169, 104214. https://doi.org/10.1016/j.compedu.2021.104214 Barrett, A., Pack, A., Guo, Y., & Wang, N. (2020). Technology acceptance model and multi-user virtual reality learning environments for Chinese language education. Interactive Learning Environments. https://doi.org/10.1080/10494820.2020.1855209 Barry, D. M., Kanematsu, H., Fukumura, Y., Ogawa, N., Okuda, A., Taguchi, R., & Nagai, H. (2009). International comparison for problem based learning in metaverse. The ICEE and ICEER, 6066. Bernhard, J. P. (2019). Investigating people’s intention to use virtual reality in the context of victimoffender mediation using the UTAUT model. NY: University of Twente. Blumenfeld, P. C., Soloway, E., Marx, R. W., Krajcik, J. S., Guzdial, M., & Palincsar, A. (1991). Motivating project-based learning: Sustaining the doing, supporting the learning. Educational Psychologist, 26(3–4), 369–398. https://doi.org/10.1080/00461520.1991.9653139 Cabero-Almenara, J., Llorente-Cejudo, C., & Martinez-Roig, R. (2022). The use of mixed, augmented and virtual reality in history of art teaching: A case study. Applied System Innovation, 5(3), 44. https://doi.org/10.3390/asi5030044 Castronova, E. (2001). Virtual worlds: A first-hand account of market and society on the cyberian frontier. Indiana University. Chang, C.-W., Yeh, S.-C., & Li, M. (2020). The adoption of a virtual reality-assisted training system for mental rotation: A partial least squares structural equation modeling approach. JMIR Serious Games, 8(1), e14548. https://doi.org/10.2196/14548 Chen, C.-Y., Shih, B.-Y., & Yu, S.-H. (2012). Disaster prevention and reduction for exploring teachers’ technology acceptance using a virtual reality system and partial least squares techniques. Natural Hazards, 62(3), 1217–1231. https://doi.org/10.1007/s11069-012-0146-0 Collins, A., & Halverson, R. (2018). Rethinking education in the age of technology: The digital revolution and schooling in America. Teachers College Press. Collins, C. (2008). Looking to the future: Higher education in the metaverse. Educause Review, 43(5), 51–63. Costa, V., & Monteiro, S. (2016). Knowledge processes, absorptive capacity and innovation: A mediation analysis. Knowledge and Process Management, 23(3), 207–218. https://doi.org/10.1002/kpm.1507 Dahan, N. A., Al-Razgan, M., Al-Laith, A., Alsoufi, M. A., Al-Asaly, M. S., & Alfakih, T. (2022). Metaverse framework: A case study on E-learning environment (ELEM). Electronics, 11(10), 1616. https://doi.org/10.3390/electronics11101616 Dewey, J. (2007). Experience and education. New York: Simon and Schuster.Díaz, J., Saldaña, C., & Avila, C. (2020). Virtual world as a resource for hybrid education. International Journal of Emerging Technologies in Learning (IJET), 15(15), 94–109. Farjami, S., Taguchi, R., Nakahira, K. T., Fukumura, Y., & Kanematsu, H. (2011). W-02 problem based learning for materials science education in metaverse. JSEE Annual Conference International Session Proceedings 2011 JSEE Annual Conference. https://doi.org/10.20549/jseeen.2011.0_20 FitzGerald, E., Kucirkova, N., Jones, A., Cross, S., Ferguson, R., Herodotou, C., Hillaire, G., & Scanlon, E. (2018). Dimensions of personalisation in technology-enhanced learning: A framework and implications for design. British Journal of Educational Technology, 49(1), 165–181. https://doi.org/10.1111/bjet.12534 Fussell, S. G., & Truong, D. (2020). Preliminary results of a study investigating aviation student’s intentions to use virtual reality for flight training. International Journal of Aviation, Aeronautics, and Aerospace, 7(3), 2. https://doi.org/10.15394/ijaaa.2020.1504 Fussell, S. G., & Truong, D. (2022). Using virtual reality for dynamic learning: An extended technology acceptance model. Virtual Reality, 26(1), 249–267. https://doi.org/10.1007/s10055-021-00554-x George, J. F., Chi, M., & Zhou, Q. (2020). American and Chinese students and acceptance of virtual reality: A replication of “the role of espoused national cultural values in technology acceptance.” AIS Transactions on Replication Research, 6(1), 1. Halverson, L. R., Spring, K. J., Huyett, S., Henrie, C. R., & Graham, C. R. (2017). Blended learning research in higher education and K-12 settings. Learning, Design, and Technology. https://doi.org/10.1007/978-3-319-17727-4_31-1 Han, H.-C. (2020). From visual culture in the immersive metaverse to visual cognition in education. In R. Z. Zheng (Ed.), Cognitive and affective perspectives on immersive technology in education (pp.67–84). IGI Global. Han, S., & Noh, Y. (2021). Analyzing higher education instructors’ perception on Metaverse-based Education. 디지털콘텐츠학회논문지 (J. DCS), 22(11), 1793–1806. Hõrak, H. (2019). Computer vision-based unobtrusive physical activity monitoring in school by roomlevel physical activity estimation: A method proposition. Information, 10(9), 269. https://doi.org/10.3390/info10090269 Huang, H.-M., & Liaw, S.-S. (2018). An analysis of learners’ intentions toward virtual reality learning based on constructivist and technology acceptance approaches. International Review of Research in Open and Distributed Learning. https://doi.org/10.19173/irrodl.v19i1.2503 Huang, H.-M., Liaw, S.-S., & Lai, C.-M. (2016a). Exploring learner acceptance of the use of virtual reality in medical education: A case study of desktop and projection-based display systems. Interactive Learning Environments, 24(1), 3–19. https://doi.org/10.1080/10494820.2013.817436 Huang, Y. C., Backman, K. F., Backman, S. J., & Chang, L. L. (2016b). Exploring the implications of virtual reality technology in tourism marketing: An integrated research framework. International Journal of Tourism Research, 18(2), 116–128. https://doi.org/10.1002/jtr.2038 Hussin, N. H., Jaafar, J., & Downe, A. G. (2011). Assessing educators’ acceptance of Virtual Reality (VR) in the classroom using the unified theory of acceptance and use of technology (UTAUT). International Visual Informatics Conference. https://doi.org/10.1007/978-3-642-25191-7_21 Iqbal, J., & Sidhu, M. S. (2022). Acceptance of dance training system based on augmented reality and technology acceptance model (TAM). Virtual Reality, 26(1), 33–54. https://doi.org/10.1007/s10055-021-00529-y Jeon, J. H. (2021). A study on education utilizing metaverse for effective communication in a convergence subject. International Journal of Internet, Broadcasting and Communication, 13(4), 129–134. https://doi.org/10.7236/IJIBC.2021.13.4.129 Jeon, J., & Jung, S. K. (2021). Exploring the educational applicability of Metaverse-based platforms. 한국정보교육학회: 학술대회논문집, 361–368. https://koreascience.kr/article/CFKO202130548299122.page Kamińska, D., Sapiński, T., Wiak, S., Tikk, T., Haamer, R. E., Avots, E., Helmi, A., Ozcinar, C., & Anbarjafari, G. (2019). Virtual reality and its applications in education: Survey. Information, 10(10), 318. https://doi.org/10.3390/info10100318 Kanematsu, H., Kobayashi, T., Ogawa, N., Barry, D. M., Fukumura, Y., & Nagai, H. (2013). Eco car project for Japan students as a virtual PBL class. Procedia Computer Science, 22, 828–835. https://doi.org/10.1016/j.procs.2013.09.165 Kanematsu, H., Kobayashi, T., Ogawa, N., Fukumura, Y., Barry, D. M., & Nagai, H. (2012). Nuclear energy safety project in metaverse. In T. Watanabe, J. Watada, N. Takahashi, R. J. Howlett, & L. C. Jain (Eds.), Intelligent interactive multimedia: Systems and services (pp. 411–418). Springer. |
| This material may be protected under Copyright Act which governs the making of photocopies or reproductions of copyrighted materials. You may use the digitized material for private study, scholarship, or research. |