Immersive Technologies in Education: Comparison
View Latest Version
Please note this is a comparison between Version 2 by Peter Tang and Version 1 by Radu Emanuil Petruse.

“Immersive technology” is a term that describes the combination of virtual elements and the real world in a way that lets the user interact naturally with both. Immersive technology is a broad and evolving term that encompasses various kinds of technologies and viewpoints, and has applications in various fields, such as education, healthcare, entertainment, the arts, and engineering.

  • teaching/learning strategies
  • post-secondary education
  • media in education
  • improving classroom teaching

1. Introduction

Immersive technology is a dynamic and emerging field that utilizes digital media to create authentic and interactive learning environments. Virtual reality (VR), augmented reality (AR), mixed reality (MR), and movie 360 are among the various technologies that fall under the umbrella of immersive technology, whose potential to enhance learning outcomes has been widely documented [1]. Immersive technology, a cross-disciplinary field, has been applied in areas like healthcare, education, and crisis management. It has also been used to develop engaging and lifelike situations that enhance learners’ cognitive, emotional, and behavioural abilities [2,3,4[2][3][4][5],5], and has been applied in a variety of sectors, including entertainment, the arts, and engineering [6,7,8,9][6][7][8][9].
While immersive technology has the potential to enhance learning outcomes and create engaging and immersive experiences for learners, it also has some drawbacks and limitations, such as technical issues and accessibility barriers, and also raises a number of ethical concerns [10,11,12][10][11][12].

2. Immersive Technologies in Education

“Immersive technology” is a term that describes the combination of virtual elements and the real world on terms that enable the user to interact naturally with both. The concept of immersive technology can be traced back to the early 1960s, when Sutherland [13] created the “Human Machine Graphic Communication System”, the first immersive prototype of human-computer interaction. Since then, many kinds of immersive technologies have been developed, including VR, AR, RM, holography, telepresence, digital twins, and FPV drone flight [1].
“Immersive technology” is a term that means different things to different researchers. Some researchers, like Slater [14], focus on the amount of sensory information delivered by the technology (to users), along with its level of success in doing so, and conclude that immersive technology can give users a large amount of high-quality sensory information. Other researchers [15] focus on how the technology can make users feel like they are in a different world, and conclude that immersive technology can blur the boundary between reality and virtuality, creating a feeling of immersion. A third group of researchers [16] consider both aspects of sensory information and immersion, and conclude that immersive technology is creating a realistic digital environment, which users feel they inhabit and interact with.
Immersive technologies can create realistic and engaging learning environments that support effective pedagogies and learning outcomes [1,8[1][8][17],17], and can foster constructivist and experiential learning, where learners construct their own knowledge, practice skills, develop creativity, and comprehend abstract concepts [18]. The Association for Medical Education in Europe argues that “Projects for effective medical e-learning must reflect the dynamics and details of real-world practice, as well as provide effective learning opportunities” [19[19][20],20], which suggests that immersive technologies can offer valuable benefits for medical education and training that can be transferred to other fields that require practical and problem-solving abilities [1,21][1][21].
Immersive technologies, such as AR, VR, and MR can enhance student learning outcomes in various educational contexts and broaden learning environments beyond primary and higher education settings by overcoming limitations in physical space, fostering collaboration and experiential learning, and offering personalised learning approaches that can support students, regardless of their knowledge level [22].
Immersive technologies has been increasingly adopted in education, and especially in health and science teaching [1[1][7][21][23],7,21,23], where they These enable students to explore complex topics and scenarios in a realistic and interactive way and, to a greater extent than conventional methods, improve their learning outcomes.
Hamilton et al. [6] reviewed 29 studies that compared immersive VR with head- mounted display and other teaching methods, and found that immersive VR usually improved learning outcomes, in opposition to some studies that did not show any difference, and two studies, which showed immersive VR had negative effects [24,25][24][25]. The review also pointed out some problems with current research, such as short duration, no memory tests, and poor evaluation methods, and also raised the focus on science as an issue [26,27][26][27].
Ryan et al. [21] analysed 29 trials (N = 2722 students) that compared the application traditional and immersive technologies (VR, AR, or MR) in medical and nursing education, and found that, while the knowledge of both groups was the same, immersive technologies produced a better learning experience. They also reported that immersive technologies increased student satisfaction, self-efficacy, and engagement, suggesting that they are ideal for education.
The effectiveness of VR/AR/MR in different domains and contexts is still being investigated, and so are the factors that influence their design and implementation. Medical education is one of the domains that has shown great potential for VR/AR/MR applications, as students have benefitted from realistic and safe simulations of anatomical structures, physiological processes, and clinical scenarios. For example, Odame and Tümler [28] found that using off-the-shelf VR software (namely Sharecare YOU VR) to teach the anatomy of the human heart was more effective and satisfying than a conventional teaching method. Similarly, Banjar et al. [29] reviewed 12 experimental studies of the use of mixed reality in higher education, and found that most focused on 3D manipulation, visualization, and understanding of 3D object layers and components, especially in the medical and health sciences. The use of VR/AR/MR also presents opportunities and some challenges for instructional design, including the fact these technologies may impose different cognitive demands and preferences on learners and instructors. Therefore, it is important to consider the principles and theories of human cognition and learning that can guide the development and evaluation of VR/AR/MR interventions. One of the most influential theories in this regard is cognitive load theory (CLT), which is based on the assumption that human cognitive architecture consists of a limited capacity working memory and an unlimited capacity long-term memory, and which also holds that instructional methods should reduce the unimportant cognitive load and facilitate the intrinsic and relevant cognitive load associated with learning complex information [30,31][30][31]. Another relevant theory is the learning style theory, which suggests that learners have different preferences in relation to different approaches to instruction, and that instructors should balance their teaching methods to accommodate the diversity of learning styles in their classes [32,33][32][33]. However, both CLT and learning style theory have received some criticisms, in the educational and psychological literature, and have also given rise to a number of controversies, so their applicability to, and validity for, VR/AR/MR contexts needs further investigation. Dowling et al. [34] performed empirical studies that examined the effects of VR/AR/MR on learning outcomes and cognitive load, along with the moderating role of learning styles and other variables.
Another domain that has been influenced by the use of VR/AR/MR is adult education, where students can access flexible and self-directed learning opportunities that suit their needs and preferences. However, the impact of different Web-based delivery formats, such as hybrid and online, on adult students’ self-directed learning readiness (SDLR) and affective learning outcomes, such as motivation, satisfaction, and attitude, is still unclear. Nikitenko [35] compared the hybrid and online groups of 563 students enrolled on courses at the University of San Francisco and found no significant differences or relationships between the delivery formats, SDLR, affective learning outcomes, prior e-learning experience, and age, before concluding that SDLR and related programming are important for enhancing adult students’ learning experiences and outcomes in Web-enhanced settings.

References

  1. Tang, Y.M.; Chau, K.Y.; Kwok, A.P.K.; Zhu, T.; Ma, X. A Systematic Review of Immersive Technology Applications for Medical Practice and Education—Trends, Application Areas, Recipients, Teaching Contents, Evaluation Methods, and Performance. Educ. Res. Rev. 2022, 35, 100429.
  2. Di Serio, Á.; Ibáñez, M.B.; Kloos, C.D. Impact of an Augmented Reality System on Students’ Motivation for a Visual Art Course. Comput. Educ. 2013, 68, 586–596.
  3. Zhao, M.; Ong, S.-K.; Nee, A.Y. An Augmented Reality-Assisted Therapeutic Healthcare Exercise System Based on Bare-Hand Interaction. Int. J. Hum.–Comput. Interact. 2016, 32, 708–721.
  4. Bacon, L.; MacKinnon, L.; Cesta, A.; Cortellessa, G. Developing a Smart Environment for Crisis Management Training. J. Ambient Intell. Humaniz. Comput. 2013, 4, 581–590.
  5. Sebillo, M.; Vitiello, G.; Paolino, L.; Ginige, A. Training Emergency Responders through Augmented Reality Mobile Interfaces. Multimed. Tools Appl. 2016, 75, 9609–9622.
  6. Hamilton, D.; McKechnie, J.; Edgerton, E.; Wilson, C. Immersive Virtual Reality as a Pedagogical Tool in Education: A Systematic Literature Review of Quantitative Learning Outcomes and Experimental Design. J. Comput. Educ. 2021, 8, 1–32.
  7. Kavanagh, S.; Luxton-Reilly, A.; Wuensche, B.; Plimmer, B. A Systematic Review of Virtual Reality in Education. Themes Sci. Technol. Educ. 2017, 10, 85–119.
  8. Khan, M.N.R.; Lippert, K.J. Immersive Technologies in Healthcare Education. In Intelligent Systems and Machine Learning for Industry; CRC Press: Boca Raton, FL, USA, 2022; pp. 115–138.
  9. Petruse, R.E.; Grecu, V.; Chiliban, B.M. Augmented Reality Applications in the Transition towards the Sustainable Organization; Springer: Berlin/Heidelberg, Germany, 2016; pp. 428–442.
  10. Van Krevelen, D.; Poelman, R. A Survey of Augmented Reality Technologies, Applications and Limitations. Int. J. Virtual Real. 2010, 9, 1–20.
  11. Grecu, V.; Deneș, C.; Ipiña, N. Creative Teaching Methods for Educating Engineers. Appl. Mech. Mater. 2013, 371, 764–768.
  12. Mallam, S.C.; Nazir, S.; Renganayagalu, S.K. Rethinking Maritime Education, Training, and Operations in the Digital Era: Applications for Emerging Immersive Technologies. J. Mar. Sci. Eng. 2019, 7, 428.
  13. Sutherland, I.E. Sketch Pad a Man-Machine Graphical Communication System. In Proceedings of the SHARE Design Automation Workshop; Association for Computing Machinery: New York, NY, USA, 1964; pp. 6–329.
  14. Slater, M. Place Illusion and Plausibility Can Lead to Realistic Behaviour in Immersive Virtual Environments. Philos. Trans. R. Soc. B Biol. Sci. 2009, 364, 3549–3557.
  15. Lee, H.-G.; Chung, S.; Lee, W.-H. Presence in Virtual Golf Simulators: The Effects of Presence on Perceived Enjoyment, Perceived Value, and Behavioral Intention. New Media Soc. 2013, 15, 930–946.
  16. Díaz-López, L.; Tarango, J.; Contreras, C.-P. Strategies for Inclusive and Safe Education Using Virtual Reality: From the Digital Library Perspective. Digit. Libr. Perspect. 2019, 35, 216–226.
  17. Butt, A.L.; Kardong-Edgren, S.; Ellertson, A. Using Game-Based Virtual Reality with Haptics for Skill Acquisition. Clin. Simul. Nurs. 2018, 16, 25–32.
  18. Salzman, M.C.; Dede, C.; Loftin, R.B.; Chen, J. A Model for Understanding How Virtual Reality Aids Complex Conceptual Learning. Presence Teleoperators Virtual Environ. 1999, 8, 293–316.
  19. Ellaway, R.; Masters, K. AMEE Guide 32: E-Learning in Medical Education Part 1: Learning, Teaching and Assessment. Med. Teach. 2008, 30, 455–473.
  20. Harden, R.M.; Laidlaw, J.M. Effective Continuing Education: The CRISIS Criteria. Med. Educ. 1992, 26, 407–422.
  21. Ryan, G.V.; Callaghan, S.; Rafferty, A.; Higgins, M.F.; Mangina, E.; McAuliffe, F. Learning Outcomes of Immersive Technologies in Health Care Student Education: Systematic Review of the Literature. J. Med. Internet Res. 2022, 24, e30082.
  22. Fortman, J.; Quintana, R. Fostering Collaborative and Embodied Learning with Extended Reality: Special Issue Introduction. Int. J. Comput.-Support. Collab. Learn. 2023, 18, 145–152.
  23. Mathew, P.S.; Pillai, A.S. Role of Immersive (XR) Technologies in Improving Healthcare Competencies: A Review. In Virtual and Augmented Reality in Education, Art, and Museums; IGI Global: Hershey, PA, USA, 2020; pp. 23–46.
  24. Makransky, G.; Terkildsen, T.S.; Mayer, R.E. Adding Immersive Virtual Reality to a Science Lab Simulation Causes More Presence but Less Learning. Learn. Instr. 2019, 60, 225–236.
  25. Parong, J.; Mayer, R.E. Learning Science in Immersive Virtual Reality. J. Educ. Psychol. 2018, 110, 785.
  26. Jensen, L.; Konradsen, F. A Review of the Use of Virtual Reality Head-Mounted Displays in Education and Training. Educ. Inf. Technol. 2018, 23, 1515–1529.
  27. Reed, D.A.; Cook, D.A.; Beckman, T.J.; Levine, R.B.; Kern, D.E.; Wright, S.M. Association between Funding and Quality of Published Medical Education Research. JAMA 2007, 298, 1002–1009.
  28. Odame, A.; Tümler, J. Is Off-the-Shelf VR Software Ready for Medical Teaching? In Proceedings of the Virtual, Augmented and Mixed Reality: Design and Development, Virtual, 16 June 2022; Chen, J.Y.C., Fragomeni, G., Eds.; Springer International Publishing: Cham, Switzerland, 2022; pp. 224–237.
  29. Banjar, A.; Xu, X.; Iqbal, M.Z.; Campbell, A. A Systematic Review of the Experimental Studies on the Effectiveness of Mixed Reality in Higher Education between 2017 and 2021. Comput. Educ. X Real. 2023, 3, 100034.
  30. Sweller, J. Cognitive Load Theory. In Psychology of Learning and Motivation; Elsevier: Amsterdam, The Netherlands, 2011; Volume 55, pp. 37–76. ISBN 0079-7421.
  31. Sweller, J. Cognitive Load Theory and Educational Technology. Educ. Technol. Res. Dev. 2020, 68, 1–16.
  32. Felder, R.M.; Silverman, L.K. Learning and Teaching Styles in Engineering Education. Eng. Educ. 1988, 78, 674–681.
  33. Felder, R.M. Opinion: Uses, Misuses, and Validity of Learning Styles. Adv. Eng. Educ. 2020, 8, 1–16.
  34. Dowling, C.; Godfrey, J.M.; Gyles, N. Do Hybrid Flexible Delivery Teaching Methods Improve Accounting Students’ Learning Outcomes? Account. Educ. 2003, 12, 373–391.
  35. Nikitenko, G. Analysis of Adult Students’ Self-Directed Learning Readiness, Affective Learning Outcomes, Prior e-Learning Experience, and Age in Hybrid and Online Courses; Association for the Advancement of Computing in Education (AACE): Chesapeake, VA, USA, 2011; pp. 2503–2513.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
ScholarVision Creations
Feedback