Technology acceptance of a wearable collaborative augmented reality system in learning chemistry among junior high school students
Juan Du 1, Dorothy DeWitt 1 *
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1 University Malaya, Malaysia
* Corresponding Author

Abstract

Concepts related to molecular structure are often challenging for students to visualize and comprehend. Augmented reality has emerged as a promising solution to this problem, providing students with opportunities to manipulate and visualize chemical molecular structures to improve their understanding. Furthermore, collaborative learning environments have the potential to enhance student learning by fostering knowledge sharing and collaborative authoring. However, there is a dearth of research exploring students' acceptance of augmented reality in a collaborative learning context. Therefore, this study aims to investigate the technology acceptance of a wearable collaborative augmented reality system in chemistry education among junior high school students. Specifically, 124 students used Microsoft® HoloLens 2 device to learn about chemical molecular structure. Data was collected using the Extended Technology Acceptance Questionnaire after participants used the system and analyzed using Partial Least Squares Structural Equation Modeling. The extended model takes knowledge sharing, collaborating learning, and collaborative authoring as exogenous variables with perceived ease of use and perceived usability and finally produces a structural model that leads to behavioral usage intentions. The hypotheses tested in this study were accepted as the relationships were significant. Knowledge sharing, collaborative learning, and collaborative authoring have a positive impact on perceived usefulness and perceived ease of use respectively; and perceived usefulness and perceived ease of use have significant effects on behavioral intention to use respectively. This study conclusively demonstrated the hypothesized relationships. Evidence from these results provides comprehensive insights that can help policymakers and educators better understand the factors influencing the adoption of wearable collaborative augmented reality.  

Keywords

References

  • Al-Emran, M., Mezhuyev, V., & Kamaludin, A. (2020). Towards a conceptual model for examining the impact of knowledge management factors on mobile learning acceptance. Technology in Society, 61, 101247. https://doi.org/10.1016/j.techsoc.2020.101247
  • Alam, A. (2022). Employing adaptive learning and intelligent tutoring robots for virtual classrooms and smart campuses: reforming education in the age of artificial intelligence. In R. N. Shaw, S. Das, V. Piuri, & M. Bianchini (Eds.), Advanced computing and intelligent technologies (pp. 395-406). Springer.
  • Alenazy, W. M., Mugahed, A.-R. W., & Khan, M. S. (2019). Validation of TAM model on social media use for collaborative learning to enhance collaborative authoring. IEEE Access, 7, 71550-71562. https://doi.org/10.1109/ACCESS.2019.2920242
  • Avcı, Y. U., & Gulbahar, Y. (2013). Technology acceptance model: A review of the prior predictors. Ankara University Journal of Faculty of Educational Sciences, 46(1), 89-109. https://doi.org/10.1501/Egifak_0000001275
  • Aw, J. K., Boellaard, K. C., Tan, T. K., Yap, J., Loh, Y. P., Colasson, B., Blanc, É., Lam, Y., & Fung, F. M. (2020). Interacting with three-dimensional molecular structures using an augmented reality mobile app. Journal of Chemical Education, 97(10), 3877-3881. https://doi.org/10.1021/acs.jchemed.0c00387
  • 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, 31(3), 1665-1682. https://doi.org/10.1080/10494820.2020.1855209
  • Cabero-Almenara, J., & Perez. (2018). TAM model validation adoption of augmented reality through structural equations. Estudios sobre Educación, 34, 129-153. https://core.ac.uk/reader/157758588
  • Cheung, R., & Vogel, D. (2013). Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. Computers & Education, 63, 160-175. https://doi.org/10.1016/j.compedu.2012.12.003
  • 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
  • Eiris, R., Wen, J., & Gheisari, M. (2022). iVisit-Collaborate: Collaborative problem-solving in multiuser 360-degree panoramic site visits. Computers & Education, 177, 104365. https://doi.org/10.1016/j.compedu.2021.104365
  • Feng, S., Liu, Y., Zhang, Q., He, W., Zhang, X., Wang, S., & Billinghurst, M. (2023). Parallel or cross? Effects of two collaborative modes on augmented reality co-located operations. International Journal of Human–Computer Interaction. Advance Online Publication. https://doi.org/10.1080/10447318.2023.2202574
  • Fombona-Pascual, A., Fombona, J., & Vicente, R. (2022). Augmented Reality, a Review of a Way to Represent and Manipulate 3D Chemical Structures. Journal of Chemical Information and Modeling, 62(8), 1863-1872. https://doi.org/10.1021/acs.jcim.1c01255
  • 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
  • Han, J.-H., & Sa, H. J. (2022). Acceptance of and satisfaction with online educational classes through the technology acceptance model (TAM): the COVID-19 situation in Korea. Asia Pacific Education Review, 23(3), 403-415. https://doi.org/10.1007/s12564-021-09716-7
  • Haugstvedt, A. C., & Krogstie, J. (2012). Mobile augmented reality for cultural heritage: A technology acceptance study [Paper presentation]. IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Atlanta, GA, USA.
  • He, S., Jiang, S., Zhu, R., & Hu, X. (2023). The influence of educational and emotional support on e-learning acceptance: An integration of social support theory and TAM. Education and Information Technologies, 28, 11145–11165. https://doi.org/10.1007/s10639-023-11648-1
  • Huang, H.-M., Rauch, U., & Liaw, S.-S. (2010). Investigating learners’ attitudes toward virtual reality learning environments: Based on a constructivist approach. Computers & Education, 55(3), 1171-1182. https://doi.org/10.1016/j.compedu.2010.05.014
  • Huang, T.-C., Shu, Y., Yeh, T.-C., & Zeng, P.-Y. (2016). Get lost in the library?An innovative application of augmented reality and indoor positioning technologies. The Electronic Library, 34(1), 99-115. https://doi.org/10.1108/EL-08-2014-0148
  • Ibili, E., Resnyansky, D., & Billinghurst, M. (2019). Applying the technology acceptance model to understand maths teachers’ perceptions towards an augmented reality tutoring system. Education and Information Technologies, 24(5), 2653-2675. https://doi.org/10.1007/s10639-019-09925-z
  • 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
  • Jang, J., Ko, Y., Shin, W. S., & Han, I. (2021). Augmented reality and virtual reality for learning: an examination using an extended technology acceptance model. IEEE Access, 9, 6798-6809. https://doi.org/10.1109/ACCESS.2020.3048708
  • Jovanović, A., & Milosavljević, A. (2022). VoRtex metaverse platform for gamified collaborative learning. Electronics, 11(3), 317. https://doi.org/10.3390/electronics11030317
  • Jyot, K. D., Niraja, S., & Irum, A. (2023). Technology-enabled language leaning: mediating role of collaborative learning. Journal of Language and Education, 9(1), 89-101. https://doi.org/10.17323/jle.2023.12359
  • Khan, M. N., Ashraf, M. A., Seinen, D., Khan, K. U., & Laar, R. A. (2021). Social media for knowledge acquisition and dissemination: The impact of the COVID-19 pandemic on collaborative learning driven social media adoption [Original Research]. Frontiers in Psychology, 12, 648253. https://doi.org/10.3389/fpsyg.2021.648253
  • Ko, E. G., & Lim, K. Y. (2022). Promoting english learning in secondary schools: design-based research to develop a mobile application for collaborative learning. The Asia-Pacific Education Researcher, 31(3), 307-319. https://doi.org/10.1007/s40299-021-00562-0
  • Liaw, S.-S., Chen, G.-D., & Huang, H.-M. (2008). Users’ attitudes toward Web-based collaborative learning systems for knowledge management. Computers & Education, 50(3), 950-961. https://doi.org/10.1016/j.compedu.2006.09.007
  • Lin, C.-P., Yang, S.-J., Lin, K.-Y., Looi, C.-K., & Chen, Y.-H. (2022). Explorations of two approaches to learning CT in a game environment for elementary school students. Journal of Computers in Education, 9(2), 261-290. https://doi.org/10.1007/s40692-021-00203-x
  • Lin, H.-F., & Chen, C.-H. (2017). Combining the technology acceptance model and uses and gratifications theory to examine the usage behavior of an augmented reality tour-sharing application. Symmetry, 9(7), 9070113. https://doi.org/10.3390/sym9070113
  • Liyanawatta, M., Yang, S.-H., Liu, Y.-T., Zhuang, Y., & Chen, G.-d. (2022). Audience participation digital drama-based learning activities for situational learning in the classroom. British Journal of Educational Technology, 53(1), 189-206. https://doi.org/10.1111/bjet.13160
  • Lu, J., Rong, D., Lev, B., Liang, M., Zhang, C., & Gao, Y. (2023). Constraints affecting the promotion of waste incineration power generation project in China: A perspective of improved technology acceptance model. Technological Forecasting and Social Change, 186, 122165. https://doi.org/10.1016/j.techfore.2022.122165
  • Mazzuco, A., Krassmann, A. L., Reategui, E., & Gomes, R. S. (2022). A systematic review of augmented reality in chemistry education. Review of Education, 10(1), e3325. https://doi.org/10.1002/rev3.3325
  • Natasia, S. R., Wiranti, Y. T., & Parastika, A. (2022). Acceptance analysis of NUADU as e-learning platform using the Technology Acceptance Model (TAM) approach. Procedia Computer Science, 197, 512-520. https://doi.org/10.1016/j.procs.2021.12.168
  • Okolie, U. C., Igwe, P. A., Mong, I. K., Nwosu, H. E., Kanu, C., & Ojemuyide, C. C. (2022). Enhancing students’ critical thinking skills through engagement with innovative pedagogical practices in Global South. Higher Education Research & Development, 41(4), 1184-1198. https://doi.org/10.1080/07294360.2021.1896482
  • Oyman, M., Bal, D., & Ozer, S. (2022). Extending the technology acceptance model to explain how perceived augmented reality affects consumers' perceptions. Computers in Human Behavior, 128, 107127. https://doi.org/10.1016/j.chb.2021.107127
  • Özçakır, B., & Çakıroğlu, E. (2022). Fostering spatial abilities of middle school students through augmented reality: Spatial strategies. Education and Information Technologies, 27(3), 2977-3010. https://doi.org/10.1007/s10639-021-10729-3
  • Pathania, M., Mantri, A., Kaur, D. P., Singh, C. P., & Sharma, B. (2023). A Chronological Literature Review of Different Augmented Reality Approaches in Education. Technology, Knowledge and Learning, 28(1), 329-346. https://doi.org/10.1007/s10758-021-09558-7
  • Ramirez, H. J. M., & Monterola, S. L. C. (2022). Co-creating scripts in computer-supported collaborative learning and its effects on students’ logical thinking in earth science. Interactive Learning Environments, 30(5), 908-921. https://doi.org/10.1080/10494820.2019.1702063
  • Sagnier, C., Loup-Escande, E., Lourdeaux, D., Thouvenin, I., & Valléry, G. (2020). User acceptance of virtual reality: an extended technology acceptance model. International Journal of Human–Computer Interaction, 36(11), 993-1007. https://doi.org/10.1080/10447318.2019.1708612
  • Wei, L., Shang, C., Chen, X., & Venkateswaran, N. (2022). The use of knowledge management-based information collaborative learning tool in english teaching Classroom. Wireless Communications and Mobile Computing, 2022, 1-10. https://doi.org/10.1155/2022/6367007
  • Zhang, S., Wen, Y., & Liu, Q. (2022). Exploring student teachers’ social knowledge construction behaviors and collective agency in an online collaborative learning environment. Interactive Learning Environments, 30(3), 539-551. https://doi.org/10.1080/10494820.2019.1674880
  • Zurba, M., Petriello, M. A., Madge, C., McCarney, P., Bishop, B., McBeth, S., Denniston, M., Bodwitch, H., & Bailey, M. (2022). Learning from knowledge co-production research and practice in the twenty-first century: global lessons and what they mean for collaborative research in Nunatsiavut. Sustainability Science, 17(2), 449-467. https://doi.org/10.1007/s11625-021-00996-x

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