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A novel method for improving the perceptual learning effect in virtual reality interaction

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Abstract

The development of intellectualization trend in online education has been characterized by constructing a multi-terminal immersive learning environment. Virtual reality (VR) technology has been increasingly used in online education to create multisensory interactive learning. However, the technical features of this technology, including high immersion and strong interactions, have not been entirely played substantially. Consequently, improvements in the perceptual learning effect have been hindered. To address these issues, this study built a novel VR interaction model for perceptual learning by introducing reflective thinking variables and individual participation factors from the task-technology fit perspective. Furthermore, the deployment strategy of this model used to build a VR education system was proposed. The usability evaluation results of the proposed model show that the path hypothesis of the novel model is verified. Particularly, the path coefficients of reflective thinking, learner participation, and instructor participation factors on the perceptual learning effect were 0.238 (p < 0.01), 0.398 (p < 0.001), and 0.348 (p < 0.001), respectively. Compared to the traditional VR education system, the immersion and interaction of the VR education system using the proposed deployment strategy were enhanced by 4.9% and 10.7%, respectively. Further, learners’ perceptual learning effect improved by 5.3%.

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References

  1. Abdullah J, Mohd-Isa WN, Samsudin MA (2019) Virtual reality to improve group work skill and self-directed learning in problem-based learning narratives. Virtual Reality 23(4):461–471. https://doi.org/10.1007/s10055-019-00381-1

    Article  Google Scholar 

  2. Alavesa P, Pakanen M, Ojala T, Pouke M, Kukka H, Samodelkin A, Voroshilov A, Abdellatif M (2020) Embedding virtual environments into the physical world: memorability and co-presence in the context of pervasive location-based games. Multimed Tools Appl 79:3285–3309. https://doi.org/10.1007/s11042-018-7077-z

    Article  Google Scholar 

  3. Ang LM, Ge FL, Seng KP (2020) Big educational data & analytics: survey, architecture and challenges. IEEE Access 8:116392–116414. https://doi.org/10.1109/ACCESS.2020.2994561

  4. Arana-Llanes JY, Gabriel GS, Rodrigo PT, Víctor OP, Ricarte-Trives JJ, Latorre-Postigo JM et al (2018) Eeg lecture on recommended activities for the induction of attention and concentration mental states on e-learning students. J Intell Fuzzy Syst 34(5):3359–3371. https://doi.org/10.3233/JIFS-169517

    Article  Google Scholar 

  5. Astivia O, Kroc E, Zumbo BD (2020) The role of item distributions on reliability estimation: the case of cronbach's coefficient alpha. Educ Psychol Meas 80(5):825–846. https://doi.org/10.1177/0013164420903770

    Article  Google Scholar 

  6. Barrett AJ, Pack A, Quaid ED (2021) Understanding learners' acceptance of high-immersion virtual reality systems: insights from confirmatory and exploratory PLS-SEM analyses. Comp Educ 169:104214. https://doi.org/10.1016/j.compedu.2021.104214

    Article  Google Scholar 

  7. Checa D, Bustillo A (2020) A review of immersive virtual reality serious games to enhance learning and training. Multimed Tools Appl 79(9):5501–5527. https://doi.org/10.1007/s11042-019-08348-9

    Article  Google Scholar 

  8. Das N, Sunguh KK, Sarwar B, Ahmed A, Hassan S (2018) Technology-embedded educational policy: mediation effects of the use of virtual learning influence on learner satisfaction. J Educ Train 16(1):41–54. https://doi.org/10.5296/jet.v6i1.13856

    Article  Google Scholar 

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

    Article  Google Scholar 

  10. Dishaw MT, Strong DM (1999) Extending the technology acceptance model with task-technology fit constructs. Inf Manag 36(1):9–21. https://doi.org/10.1016/S0378-7206(98)00101-3

    Article  Google Scholar 

  11. Dunnagan CL, Gallardo-Williams MT (2020) Overcoming physical separation during covid-19 using virtual reality in organic chemistry laboratories. J Chem Educ 97(9):3060–3063. https://doi.org/10.1021/acs.jchemed.0c00548

    Article  Google Scholar 

  12. Goodhue DL, Thompson RL (1995) Task-technology fit and individual performance. MIS Q 19(2):213–236. https://doi.org/10.2307/249689

    Article  Google Scholar 

  13. Gromer D, Madeira O, Gast P et al (2018) Height simulation in a virtual reality cave system: validity of fear responses and effects of an immersion manipulation. Front Hum Neurosci 12:372. https://doi.org/10.3389/fnhum.2018.00372

    Article  Google Scholar 

  14. Guo X (2018) Evaluation of teaching effectiveness based on classroom micro-expression recognition. Int J Perform Eng 14(11):2877–2885. https://doi.org/10.23940/ijpe.18.11.p33.28772885

    Article  Google Scholar 

  15. Hai M, Tt A, Nar A, Fang HC Explaining chinese university students' continuance learning intention in the mooc setting: a modified expectation confirmation model perspective. Comput Educ 11(2):243–254. https://doi.org/10.1016/j.compedu.2020.103850

  16. Ikbal MS, Ramadoss V, Zoppi M (2020) Dynamic pose tracking performance evaluation of htc vive virtual reality system. IEEE Access, PP (99):3798–3815. https://doi.org/10.1109/ACCESS.2020.3047698

  17. Kerry T, Manis D, Choi (2019) The virtual reality hardware acceptance model (vr-ham): extending and individuating the technology acceptance model (tam) for virtual reality hardware - sciencedirect. J Bus Res 100:503–513. https://doi.org/10.1016/j.jbusres.2018.10.021

    Article  Google Scholar 

  18. Kim J, Leathem T (2018) Virtual reality as a standard in the construction management curriculum. In the proceedings of the 1st international conference on construction futures. pp. 1-13.

  19. Lee J, Kim J, Choi JY (2019) The adoption of virtual reality devices: the technology acceptance model integrating enjoyment, social interaction, and strength of the social ties. Telematics Inform 39:37–48. https://doi.org/10.1016/j.tele.2018.12.006

    Article  Google Scholar 

  20. Liu Q, Zhang S, Wang Q, Chen W (2018) Mining online discussion data for understanding teachers' reflective thinking. IEEE Trans Learn Technol 11:243–254. https://doi.org/10.1109/TLT.2017.2708115

    Article  Google Scholar 

  21. Makransky G, Lilleholt L (2018) A structural equation modeling investigation of the emotional value of immersive virtual reality in education. Educ Technol Res Dev 66:1141–1164. https://doi.org/10.1007/s11423-018-9581-2

    Article  Google Scholar 

  22. Makransky G, Peterson G (2019) Investigating the process of learning with desktop virtual reality: A structural equation modeling approach. Comput Educ 134:15–30. https://doi.org/10.1016/j.compedu.2019.02.002

    Article  Google Scholar 

  23. Maraza QB, Alejandro OM, Choquehuanca QW et al (2020) Towards a standardization of learning behavior indicators in virtual environments. Int J Adv Comput Sci Appl 11(11):146–152. https://doi.org/10.14569/IJACSA.2020.0111119

    Article  Google Scholar 

  24. McGill TJ, Klobas JE (2009) A task–technology fit view of learning management system impact. Comput Educ 52(2):496–508. https://doi.org/10.1016/j.compedu.2008.10.002

    Article  Google Scholar 

  25. Mulders M, Buchner J, Kerres M (2020) A framework for the use of immersive virtual reality learning environments. Int J Emerg Technol Learn 15(24):208–224. https://doi.org/10.3991/ijet.v15i24.16615

    Article  Google Scholar 

  26. Pan CT, Sun PY, Wang SY, Li HJ, Hoe ZY (2020) Integration of multi-axis platform with synchronous motion-sensing and virtual reality imagery for the depth of immersion. Int J Adv Manuf Technol 108(1–2):91–103. https://doi.org/10.1007/s00170-020-05360-4

    Article  Google Scholar 

  27. Puig MS, Sánchez-Martí A, Ruiz-Bueno A, Sánchez-Santamaría J (2020) The effects of learning contexts on the development of reflective thinking in university education: design and validation of a questionnaire. Sustainability 12(8):1–18. https://doi.org/10.3390/su12083298

    Article  Google Scholar 

  28. Rahmalan H (2020) Development of virtual reality training for fire safety education. Int J Adv Trends Comput Sci Eng 9(4):5906–5912. https://doi.org/10.30534/ijatcse/2020/253942020

    Article  Google Scholar 

  29. Ramos A, Fraine BD, Verschueren K (2020) Learning goal orientation in high-ability and average-ability students: developmental trajectories, contextual predictors, and long-term educational outcomes. J Educ Psychol 113(2). https://doi.org/10.1037/edu0000476

  30. Shen CW, Ho JT, Ly P, Kuo TC (2019) Behavioural intentions of using virtual reality in learning: perspectives of acceptance of information technology and learning style. Virtual Reality 23(3):313–324. https://doi.org/10.1007/s10055-018-0348-1

    Article  Google Scholar 

  31. Sun R, Wu YJ, Cai Q (2019) The effect of a virtual reality learning environment on learners' spatial ability. Virtual Reality 23:385–398. https://doi.org/10.1007/s10055-018-0355-2

    Article  Google Scholar 

  32. Sutjarittham T, Gharakheili HH, Kanhere SS, Sivaraman V (2019) Experiences with iot and ai in a smart campus for optimizing classroom usage. IEEE Internet Things J 6:7595–7607. https://doi.org/10.1109/JIOT.2019.2902410

    Article  Google Scholar 

  33. Syawaludin A, Gunarhadi, Rintayati P (2019) Development of augmented reality-based interactive multimedia to improve critical thinking skills in science learning. Int J Instr 12(4):331–344. https://doi.org/10.29333/iji.2019.12421a

    Article  Google Scholar 

  34. Syed ZA, Trabookis Z, Bertrand JW, Madathil KC, Hartley RS, Frady KK et al (2019) Evaluation of virtual reality based learning materials as a supplement to the undergraduate mechanical engineering laboratory experience. Int J Eng Educ 35(3):842–852

    Google Scholar 

  35. Tao G, Garrett B, Taverner T, Cordingley E, Sun C (2021) Immersive virtual reality health games: a narrative review of game design. J Neuroeng Rehabil 18:31. https://doi.org/10.1186/s12984-020-00801-3

    Article  Google Scholar 

  36. Wang S, Zhang K, Du M, Wang Z (2018) Development and measurement validity of an instrument for the impact of technology-mediated learning on learning processes. Comput Educ 121(JUN.:131–142. https://doi.org/10.1016/j.compedu.2018.03.006

    Article  Google Scholar 

  37. Wang D, Song M, Naqash A, Zheng Y, Xu W, Zhang Y (2019) Toward whole-hand kinesthetic feedback: a survey of force feedback gloves. IEEE Trans Haptics 12(2):189–204. https://doi.org/10.1109/TOH.2018.2879812

    Article  Google Scholar 

  38. Wenger MJ, Rhoten SE (2019) The perceptual learning produces perceptual objects. J Exp Psychol Learn Mem Cogn 46(3):455–475. https://doi.org/10.1037/xlm0000735

    Article  Google Scholar 

  39. Wu S, Xiaoming C, Jun F et al (2018) Efficient VR video representation and quality assessment. J Vis Commun Image Represent 57:107–117. https://doi.org/10.1016/j.jvcir.2018.10.018

    Article  Google Scholar 

  40. Yang G, Chen Y, Zheng X, Hwang G (2020) From experiencing to expressing: a virtual reality approach to facilitating pupils' descriptive paper writing performance and learning behavior engagement. Br J Educ Technol 52(2):807–823. https://doi.org/10.1111/bjet.13056

    Article  Google Scholar 

  41. Zanjani N, Edwards SL, Nykvist S, Geva S (2016) Lms acceptance: the instructor role. Asia Pac Educ Res 25(4):519–526. https://doi.org/10.1007/s40299-016-0277-2

    Article  Google Scholar 

  42. Zhang X, Jiang S, Patricia ODP, Lytras MD, Sun Y (2017) How virtual reality affects perceived learning effectiveness: a task–technology fit perspective. Behav Inform Technol 36(4–6):548–556. https://doi.org/10.1080/0144929X.2016.1268647

    Article  Google Scholar 

  43. Zhou Y, Ji S, Xu T, Wang Z (2018) Promoting knowledge construction: a model for using virtual reality interaction to enhance learning. Procedia Comput Sci 130:239–246. https://doi.org/10.1016/j.procs.2018.04.035

    Article  Google Scholar 

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Availability of data and material

All data generated or analyzed during this study are included in this study.

Code availability

Code generated or used during the study are available from the corresponding author by request.

Funding

This work is funded by Educational Research Project for Young Teachers of The Education Department of Fujian Province, China (JAT200029).

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Authors

Contributions

Conceptualization, Methodology, Formal analysis and investigation, Writing –original draft preparation, Writing –review and editing: Yi Lin and Yangfan Lan.

Funding acquisition: Yi Lin.

Resources: Yangfan Lan and Shunbo Wang.

Supervision: Yi Lin.

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Correspondence to Yangfan Lan.

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All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors. Informed consent was acquired from all individual participants included in the study.

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Appendix 1

Appendix 1

Table 9 Perceptual learning Questionnaire

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Lin, Y., Lan, Y. & Wang, S. A novel method for improving the perceptual learning effect in virtual reality interaction. Multimed Tools Appl 81, 21385–21416 (2022). https://doi.org/10.1007/s11042-022-12542-7

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