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Education and Information Technologies

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03-11-2020

Google glass adoption in the educational environment: A case study in the Gulf area

Authors: Rana Saeed Al-Maroof, Aseel M. Alfaisal, Said A. Salloum

Published in: Education and Information Technologies | Issue 3/2021

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Abstract

The rapid changes in recent years witnessed the development of technology-based education environment where teachers and learners can interact by adopting Information and Communication Technology (ICT) such as Google Glass. However, few educational universities and colleges have adopted Google Glass in their educational institutions. The reason behind this tendency is that the integration of the technology phenomenon has not been widely explored. This study is an attempt to investigate Google Glass adoption in the Gulf area. We hypothesized that presenting the teachers and learners with the influential features of Google Glass would change their attitudes towards using Google Glass in educational institutions. This paper reports on the design of a framework that links TAM with other influential factors. In other words, this study examines the integration of the Technology Acceptance Model (TAM) with the well-known effective features of the device, including teaching and learning facilitator and learning motivator, ‘functionality’, and trust and information privacy to enhance communication between teachers and students in the classroom. The total number of questionnaires collected was 968 different universities. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was utilized to investigate the research model based on the student’s data gathered through a survey. The results that motivation, trust & privacy have a significant relationship with perceived usefulness and perceived ease of use of Google Glass. The results also suggested that functionality was significantly associated with the perceived ease of use. Further, perceived usefulness and perceived ease of use were significantly related to the Google Glass adoption. Finally, trust & privacy and the perceived ease of use have a crucial role in supporting the adoption of Google Glass. The practical implications of these findings in relation to future work also presented.

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Adapa, A., Nah, F. F.-H., Hall, R. H., Siau, K., & Smith, S. N. (2018). Factors influencing the adoption of smart wearable devices. International Journal of Human Computer Interaction, 34(5), 399–409. https://doi.org/10.1080/10447318.2017.1357902.CrossRef

Al-Emran, M., & Salloum, S. A. (2017). Students’ attitudes towards the use of Mobile technologies in e-evaluation. International Journal of Interactive Mobile Technologies (IJIM), 11(5), 195–202.CrossRef

Al-Emran, M., Arpaci, I., & Salloum, S. A. (2020a). An empirical examination of continuous intention to use m-learning: An integrated model. Education and Information Technologies, 25, 2899–2918. https://doi.org/10.1007/s10639-019-10094-2.CrossRef

Al-Emran, M., Al-Maroof, R., Al-Sharafi, M. A., & Arpaci, I. (2020b). What impacts learning with wearables? An integrated theoretical model. Interactive Learning Environments, 1–21. https://doi.org/10.1080/10494820.2020.1753216.

Al-Emran M., Malik S. I. Al-Kabi M. N. (2020c) A Survey of Internet of Things (IoT) in education: Opportunities and challenges. In A. Hassanien, R. Bhatnagar, N. Khalifa, & M. Taha (Eds.), Toward Social Internet of Things (SIoT): Enabling technologies, architectures and applications. studies in Computational Intelligence, vol 846. Cham: Springer. https://doi.org/10.1007/978-3-030-24513-9_12.

Alshurideh, M., Al Kurdi, B., Salloum, S. A., Arpaci, I., & Al-Emran, M. (2020). Predicting the actual use of M-learning systems: A comparative approach using PLS-SEM and machine learning algorithms. Interactive Learning Environments, 1–15. https://doi.org/10.1080/10494820.2020.1826982.

Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to casual modeling: Personal computer adoption and use as an illustration. Technology Studies, Special Issue on Research Methodology, 2(2), 285–309.

Basoglu, N., Ok, A. E., & Daim, T. U. (2017). What will it take to adopt smart glasses: A consumer choice based review? Technology in Society, 50, 50–56. https://doi.org/10.1016/j.techsoc.2017.04.005.CrossRef

Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. https://doi.org/10.1037/0033-2909.88.3.588.CrossRef

Berque, D. A., & Newman, J. T. (2015). GlassClass: Exploring the design, implementation, and acceptance of google glass in the classroom. In R. Shumaker & S. Lackey (Eds.), Virtual, augmented and mixed reality. VAMR 2015. Lecture notes in computer science (vol. 9179). Cham: Springer. https://doi.org/10.1007/978-3-319-21067-4_25.

Bola, S., Brighton, G., Shukla, R., & Powles, J. (2015). Can google glass be used as a training and assessment tool? International Journal of Surgery, 1(23), S103. https://doi.org/10.1016/j.ijsu.2015.07.479.CrossRef

Boykin, E. (2014). Google glass in the class: Wearable technology of the educational future. Retrieved January, 9, 2018.

Brewer, Z. E., Fann, H. C., Ogden, W. D., Burdon, T. A., & Sheikh, A. Y. (2016). Inheriting the learner’s view: A Google glass-based wearable computing platform for improving surgical trainee performance. Journal of Surgical Education, 73(4), 682–688. https://doi.org/10.1016/j.jsurg.2016.02.005.CrossRef

Burke, M. (5AD) (n.d.). Ways google glass can be used in education.

Cheng, Y.-M., Lou, S.-J., Kuo, S.-H., & Shih, R.-C. (2013). Investigating elementary school students’ technology acceptance by applying digital game based learning to environmental education. Australasian Journal of Educational Technology, 29(1), 96–110. https://doi.org/10.14742/ajet.65.CrossRef

Chuan, C. L., & Penyelidikan, J. (2006). Sample size estimation using Krejcie and Morgan and Cohen statistical power analysis: A comparison. Jurnal Penyelidikan IPBL, 7, 78–86.

Dafoulas, G. A., Maia, C., & Loomes, M. (2016). Using optical head-mounted devices (OHMD) for provision of feedback in education. In 2016 12th International Conference on Intelligent Environments (IE) (pp. 159–162). IEEE. https://doi.org/10.1109/IE.2016.34.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008.CrossRef

Dehghani, M. (2016). An assessment towards adoption and diffusion of smart wearable technologies by consumers: The cases of smart watch and fitness wristband products. In HT (Extended Proceedings) (pp. 1–6).

Dickey, R. M., Srikishen, N., Lipshultz, L. I., Spiess, P. E., Carrion, R. E., & Hakky, T. S. (2016). Augmented reality assisted surgery: A urologic training tool. Asian Journal of Andrology, 18(5), 732–734.CrossRef

Dijkstra, T. K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computational Statistics & Data Analysis, 81, 10–23. https://doi.org/10.1016/j.csda.2014.07.008.MathSciNetCrossRefMATH

Dingfield, L., Kassutto, S., & Dine, J. (2017). Use of Google glass to enhance communication education. Journal of Pain and Symptom Management, 53(2), 390–391. https://doi.org/10.1016/j.jpainsymman.2016.12.172.CrossRef

Drummond, H. (2008). The Icarus paradox: An analysis of a totally destructive system. Journal of Information Technology, 23(3), 176–184. https://doi.org/10.1057/palgrave.jit.2000119.CrossRef

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312.CrossRef

Göken, M., Başoğlu, A. N., & Dabic, M. (2016). Exploring adoption of smart glasses: Applications in medical industry. In 2016 Portland International Conference on Management of Engineering and Technology (PICMET) (pp. 3175–3184). IEEE. https://doi.org/10.1109/PICMET.2016.7806835.

Goodhue, D. L., Lewis, W., & Thompson, R. (2012). Does PLS have adavantages for small sample size or non-normal data? MIS Quaterly, 36, 891–1001. https://doi.org/10.2307/41703490.CrossRef

Haesner, M., Wolf, S., Steinert, A., & Steinhagen-Thiessen, E. (2018). Touch interaction with Google glass–is it suitable for older adults? International Journal of Human-Computer Studies, 110, 12–20. https://doi.org/10.1016/j.ijhcs.2017.09.006.CrossRef

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202.CrossRef

Hair Jr., J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: Sage Publications.

Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442–458. https://doi.org/10.1108/IMDS-04-2016-0130.CrossRef

Hansen, M. H. (1994). Trustworthiness as a source of competitive advantage. Strategic Management Journal, 15(8), 175–190. https://doi.org/10.1002/smj.4250150912.CrossRef

He, J., McCarley, J. S., Crager, K., Jadliwala, M., Hua, L., & Huang, S. (2018). Does wearable device bring distraction closer to drivers? Comparing smartphones and Google glass. Applied Ergonomics, 70, 156–166. https://doi.org/10.1016/j.apergo.2018.02.022.CrossRef

Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing 22 (pp. 277–319). Emerald Group Publishing Limited. https://doi.org/10.1108/S1474-7979(2009)0000020014.

Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen Jr., D. J., Hair, J. F., Hult, G. T. M., & Calantone, R. J. (2014). Common beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013). Organizational Research Methods, 17(2), 182–209. https://doi.org/10.1177/1094428114526928.CrossRef

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8.CrossRef

Higgins, S., Xiao, Z., & Katsipataki, M. (2012). The impact of digital technology on learning: A summary for the education endowment foundation. Durham: Education Endowment Foundation and Durham University.

Hsu, J.-Y., Chen, C.-C., & Ting, P.-F. (2018). Understanding MOOC continuance: An empirical examination of social support theory. Interactive Learning Environments, 26(8), 1100–1118. https://doi.org/10.1080/10494820.2018.1446990.CrossRef

Hu, L., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to under parameterized model misspecification. Psychological Methods, 3(4), 424–453. https://doi.org/10.1037/1082-989X.3.4.424.CrossRef

Huang, J., Lin, Y., & Chuang, S. (2007). Elucidating user behavior of mobile learning. The Electronic Library, Elucidating User Behavior of Mobile Learning., 25(5), 585–598. https://doi.org/10.1108/02640470710829569.CrossRef

Keskin, S., Şahin, M., & Yurdugül, H. (2019). Online learners’ navigational patterns based on data mining in terms of learning achievement. In D. Sampson, J. Spector, D. Ifenthaler, P. Isaías, & S. Sergis (Eds.), Learning technologies for transforming large-scale teaching, learning, and assessment (pp. 105–121). Cham: Springer. https://doi.org/10.1007/978-3-030-15130-0_7.CrossRef

Khlaisang, J., Teo, T., & Huang, F. (2019). Acceptance of a flipped smart application for learning: A study among Thai University students. Interactive Learning Environments, 1–18. https://doi.org/10.1080/10494820.2019.1612447.

Kinsella, B. (2016). 46.3 Artificial intelligence: Utilizing Google glass and other mobile applications for social skills training in autism spectrum disorders. Journal of the American Academy of Child & Adolescent Psychiatry, 10(55), S70–S71. https://doi.org/10.1016/j.jaac.2016.07.715.CrossRef

Kirkham, R., & Greenhalgh, C. (2015). Social access vs. privacy in wearable computing: A case study of autism. IEEE Pervasive Computing, 14(1), 26–33. https://doi.org/10.1109/MPRV.2015.14.CrossRef

Kline, R. B. (2015). Principles and practice of structural equation modeling. New York: Guilford Publications.MATH

Knight, H. M., Gajendragadkar, P. R., & Bokhari, A. (2015). Wearable technology: Using Google glass as a teaching tool. Case Reports, 2015, 1–3. https://doi.org/10.1136/bcr-2014-208768.CrossRef

Koelle, M., El Ali, A., Cobus, V., Heuten, W., & Boll, S. C. J. (2017). All about acceptability? Identifying factors for the adoption of data glasses. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (pp. 295–300). https://doi.org/10.1145/3025453.3025749.CrossRef

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610. https://doi.org/10.1177/001316447003000308.CrossRef

Kumar, N. M., Krishna, P. R., Pagadala, P. K., & Kumar, N. M. S. (2018). Use of smart glasses in education-a study. In 2018 2nd International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC) I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC), 2018 2nd International Conference on (pp. 56–59). IEEE. https://doi.org/10.1109/I-SMAC.2018.8653666.

Larabi Marie-Sainte, S., Alrazgan, M. S., Bousbahi, F., Ghouzali, S., & Abdul, W. (2016). From mobile to wearable system: A wearable RFID system to enhance teaching and learning conditions. Mobile Information Systems, 2016, 1–10. https://doi.org/10.1155/2016/8364909.CrossRef

Leue M.C., Jung T., Tom Dieck D. (2015) Google glass augmented reality: generic learning outcomes for art galleries. In: Tussyadiah I., Inversini A. (eds.), Information and Communication Technologies in Tourism 2015 (pp. 463–476). Springer, Cham. https://doi.org/10.1007/978-3-319-14343-9_34

Lindberg, R., Seo, J., & Laine, T. H. (2016). Enhancing physical education with exergames and wearable technology. IEEE Transactions on LearningTechnologies, 9(4), 328–341. https://doi.org/10.1109/TLT.2016.2556671.CrossRef

Liu, S.-H., Liao, H.-L., & Pratt, J. A. (2009). Impact of media richness and flow on E-learning technology acceptance. Computers & Education, 52(3), 599–607. https://doi.org/10.1016/j.compedu.2008.11.002.CrossRef

Lohmöller, J. B. (1989). Predictive vs. structural modeling: PLS vs. ML. In Latent variable path modeling with partial least squares (pp. 199–226). Physica, Heidelberg. https://doi.org/10.1007/978-3-642-52512-4_5.

Marakhimov, A., & Joo, J. (2017). Consumer adaptation and infusion of wearable devices for healthcare. Computers in Human Behavior, 76, 135–148. https://doi.org/10.1016/j.chb.2017.07.016.CrossRef

Nicosia, S. N. (2015). Google glass in the classroom. http://hdl.handle.net/1951/65851

Nunes, G. S., & Arruda Filho, E. J. M. (2018). Consumer behavior regarding wearable technologies: Google glass. Innovation & Management Review, 15(3), 230–246. https://doi.org/10.1108/INMR-06-2018-0034.CrossRef

Nunnally, J. C, & Bernstein, I. H. (1978). Psychometric theory.

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (vol. 24, p. 599). New York: McGraw-Hill. https://doi.org/10.1037/018882.

Pace, S. (2013). Looking at innovation through CCT glasses: Consumer culture theory and Google glass innovation. Journal of Innovation Management, 1(1), 38–54. https://doi.org/10.24840/2183-0606_001.001_0005.CrossRef

Park, Y. J., & Skoric, M. (2017). Personalized ad in your google glass? Wearable technology, hands-off data collection, and new policy imperative. Journal of Business Ethics, 142, 71–82. https://doi.org/10.1007/s10551-015-2766-2.CrossRef

Parslow, G. R. (2014). Commentary: Google glass: A head-up display to facilitate teaching and learning. Biochemistry and Molecular Biology Education, 42(1), 91–92. https://doi.org/10.1002/bmb.20751.CrossRef

Rauschnabel, P. A., & Ro, Y. K. (2016). Augmented reality smart glasses: An investigation of technology acceptance drivers. International Journal of Technology Marketing, 11(2), 123–148. https://doi.org/10.1504/IJTMKT.2016.075690.CrossRef

Rauschnabel, P. A., Brem, A., & Ivens, B. S. (2015a). Who will buy smart glasses? Empirical results of two pre-market-entry studies on the role of personality in individual awareness and intended adoption of Google glass wearables. Computers in Human Behavior, 49, 635–647. https://doi.org/10.1016/j.chb.2015.03.003.CrossRef

Rauschnabel, P. A., Brem, A., & Ro, Y. (2015b). Augmented reality smart glasses: Definition, conceptual insights, and managerial importance. Unpublished working paper. The University of Michigan-Dearborn, College of Business.

Rauschnabel, P. A., Hein, D. W. E., He, J., Ro, Y. K., Rawashdeh, S., & Krulikowski, B. (2016). Fashion or technology? A fashnology perspective on the perception and adoption of augmented reality smart glasses. I-Com, 15(2), 179–194. https://doi.org/10.1515/icom-2016-0021.CrossRef

Rauschnabel, P. A., He, J., & Ro, Y. K. (2018). Antecedents to the adoption of augmented reality smart glasses: A closer look at privacy risks. Journal of Business Research, 92, 374–384. https://doi.org/10.1016/j.jbusres.2018.08.008.CrossRef

Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Bönningstedt: SmartPLS.

Sahin, N. T., Keshav, N. U., Salisbury, J. P., & Vahabzadeh, A. (2017). Cool enough for school: Second version of Google glass rated by children facing challenges to social integration as desirable to wear at school (p. 171033). BioRxiv. https://doi.org/10.1101/171033.

Salamin, A.-D. (2014). Using Google glass to enrich printed textbooks in a blended learning environment to meet digital natives’ expectations. In E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 1741–1748). Association for the Advancement of Computing in Education (AACE).

Salloum, S. A., Al-Emran, M., Shaalan, K., et al. (2019). Factors affecting the E-learning acceptance: A case study from UAE. Education and Information Technologies, 24, 509–530. https://doi.org/10.1007/s10639-018-9786-3.CrossRef

Sidiya, K., Alzanbagi, N., & Bensenouci, A. (2015). Google glass and apple watch will they become our learning tools? In 2015 12th Learning and Technology Conference (pp. 6–8). IEEE. https://doi.org/10.1109/LT.2015.7587222

Silva, M., Freitas, D., Neto, E., Lins, C., Teichrieb, V., & Teixeira, J. M. (2014). Glassist: Using augmented reality on Google glass as an aid to classroom management. In 2014 XVI symposium on virtual and augmented reality (pp. 37–44). IEEE. https://doi.org/10.1109/SVR.2014.41.

Sivakumar, R. (2014). Google glass in education. Journal of Cognitive Discourses, 2(02), 24–27.

Trial, D. (n.d.). Model fit.

Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Journal of Information Technology, Theory and Applications, 11(2), 5–40. https://doi.org/10.1037/0021-9010.90.4.710.CrossRef

Voo, B. (2014). Everything you need to know about Google glass. Retrieved, 11(8), 2014.

Woodside, J. M. (2015). Wearable technology acceptance model: Google glass. In Society for Information Technology & Teacher Education International Conference (pp. 1800–1802). Association for the Advancement of Computing in Education (AACE).

Wu, T., Dameff, C., & Tully, J. (2014). Integrating Google glass into simulation-based training: Experiences and future directions. Journal of Biomedical Graphics and Computing, 4(2), 49.CrossRef

Zarraonandia, T., Díaz, P., Montero, Á., Aedo, I., & Onorati, T. (2019). Using a Google glass-based classroom feedback system to improve students to teacher communication. IEEE Access, 7, 16837–16846. https://doi.org/10.1109/ACCESS.2019.2893971.CrossRef

Title: Google glass adoption in the educational environment: A case study in the Gulf area
Authors: Rana Saeed Al-Maroof
Aseel M. Alfaisal
Said A. Salloum
Publication date: 03-11-2020
Publisher: Springer US
Published in: Education and Information Technologies / Issue 3/2021
Print ISSN: 1360-2357
Electronic ISSN: 1573-7608
DOI: https://doi.org/10.1007/s10639-020-10367-1

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