Skip to main content
SpringerLink
Log in

MGP: a monitoring-based VR interactive mode to support guided practice

  • Original article
  • Published:
The Visual Computer Aims and scope Submit manuscript

Abstract

Currently, VR training systems are primarily designed according to the non-directive mode supporting independent practice without a real teacher. Students must complete all system operations resulting in heavy interaction burden and confusion. In this paper, a monitoring-based VR interactive mode is designed to support guided practice in the presence of teacher resources. The mode mainly realizes the separation of teacher–student interaction tasks, environment and equipment, helping the students focus on their own interactions and tasks. It also provides multi-channel information of the students for teachers to better understand students’ training status and make precise guidance. A platform and two applications were developed based on this mode for user study. The results show that the proposed mode can improve learning efficiency and enhance the immersive experience.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Bian, Y., Wang, Q., Zhou, C., Qi, G., Yang, C., Meng, X., Shen, C.: Comparison of 3d display technologies for embodied interaction in virtual hands-on experiential learning. International Society of the Learning Sciences, Inc.[ISLS]. (2018)

  2. Wang, C.: Comparisons between non-directive teaching model and other teaching models (2019)

  3. Harvey, S., Goudvis, A.: Strategies that work: teaching comprehension for understanding and engagement. Stenhouse Publishers, Portsmouth (2007)

    Google Scholar 

  4. Albus, P., Vogt, A., Seufert, T.: Signaling in virtual reality influences learning outcome and cognitive load. Comput. Education 166, 104154 (2021)

    Article  Google Scholar 

  5. Han, J., Zheng, Q., Ding, Y.: Lost in virtual reality? cognitive load in high immersive vr environments. J. Adv. Inf. Technol. 12(4), (2021)

  6. Knierim, P., Kosch, T., Groschopp, J., Schmidt, A.: Opportunities and challenges of text input in portable virtual reality. In: Extended abstracts of the 2020 chi conference on human factors in computing systems, pp. 1– 8 ( 2020)

  7. Dunleavy, M., Dede, C., Mitchell, R.: Affordances and limitations of immersive participatory augmented reality simulations for teaching and learning. J. Sci. Educ. Technol. 18, 7–22 (2009)

    Article  Google Scholar 

  8. Liu, D., Bhagat, K.K., Gao, Y., Chang, T.-W., Huang, R.: The potentials and trends of virtual reality in education: A bibliometric analysis on top research studies in the last two decades. In: Virtual, augmented, and mixed realities in education, 105–130 (2017)

  9. 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. 60, 225–236 (2019)

    Article  Google Scholar 

  10. Kim, Y.M., Rhiu, I., Yun, M.H.: A systematic review of a virtual reality system from the perspective of user experience. Int. J. Human-Comput. Interact. 36(10), 893–910 (2020)

    Article  Google Scholar 

  11. Mäkinen, H., Haavisto, E., Havola, S., Koivisto, J.-M.: User experiences of virtual reality technologies for healthcare in learning: An integrative review. Behav. Inf. Technol. 41(1), 1–17 (2022)

    Article  Google Scholar 

  12. Wang, F., Xu, X., Feng, W., Vesga, J.B., Liang, Z., Murrell, S.: Towards an immersive guided virtual reality microfabrication laboratory training system. In: 2020 IEEE conference on virtual reality and 3d user interfaces abstracts and workshops (VRW), IEEE, pp. 796– 797 ( 2020)

  13. Zhou, L., Sato, R.: Development and application of a surgical process simulation system using vr technology. In: 2020 IEEE 9th global conference on consumer electronics (GCCE), IEEE, pp. 655– 657 ( 2020)

  14. Kojic, T., Sirotina, U., Möller, S., Voigt-Antons, J.-N.: Influence of ui complexity and positioning on user experience during vr exergames. In: 2019 eleventh international conference on quality of multimedia experience (QoMEX), IEEE, pp. 1– 6 ( 2019)

  15. Serafin, G., Serafin, S.: Sound design to enhance presence in photorealistic virtual reality. Georgia Institute of Technology ( 2004)

  16. Zhao, H., Thrash, T., Grossrieder, A., Kapadia, M., Moussaïd, M., Hölscher, C., Schinazi, V.R.: The interaction between map complexity and crowd movement on navigation decisions in virtual reality. R. Soc. Open Sci. 7(3), 191523 (2020)

    Article  Google Scholar 

  17. Sharratt, L.: Scaffolded literacy assessment and a model for teachers’ professional development. Perspectives on transitions in schooling and instructional practice ( 2013)

  18. Ghufron, M.A., Ermawati, S.: The strengths and weaknesses of cooperative learning and problem-based learning in efl writing class: teachers’ and students’ perspectives. Int. J. Instr. 11(4), 657–672 (2018)

    Google Scholar 

  19. Al Farsi, G., Yusof, A.B.M., Romli, A., Tawafak, R.M., Malik, S.I., Jabbar, J., Bin Rsuli, M.E.: A review of virtual reality applications in an educational domain. Int. j. Interact. Mobile Technol. (2021). https://doi.org/10.3991/ijim.v15i22.25003

    Article  Google Scholar 

  20. Bastug, E., Bennis, M., Médard, M., Debbah, M.: Toward interconnected virtual reality: Opportunities, challenges, and enablers. IEEE Commun. Mag. 55(6), 110–117 (2017)

    Article  Google Scholar 

  21. Seabrook, E., Kelly, R., Foley, F., Theiler, S., Thomas, N., Wadley, G., Nedeljkovic, M., et al.: Understanding how virtual reality can support mindfulness practice: mixed methods study. J. Med. Internet Res. 22(3), 16106 (2020)

    Article  Google Scholar 

  22. Ojala, S., Sirola, J., Nykopp, T., Kröger, H., Nuutinen, H.: The impact of teacher’s presence on learning basic surgical tasks with virtual reality headset among medical students. Med. Educ. Online 27(1), 2050345 (2022)

    Article  Google Scholar 

  23. Zhang, J., Zhou, Y.: Study on interactive teaching laboratory based on virtual reality. Int. J. Contin. Eng. Education Life Long Learn. 30(3), 313–326 (2020)

    Article  Google Scholar 

  24. Brough, J.E., Schwartz, M., Gupta, S.K., Anand, D.K., Kavetsky, R., Pettersen, R.: Towards the development of a virtual environment-based training system for mechanical assembly operations. Virtual Real. 11, 189–206 (2007)

    Article  Google Scholar 

  25. Urueta, S.H., Ogi, T.: A tefl virtual reality system for high-presence distance learning. In: advances in networked-based information systems: The 22nd international conference on network-based information systems (NBiS-2019), Springer, pp. 359– 368 ( 2020)

  26. Šašinka, Č, Stachoň, Z., Sedlák, M., Chmelík, J., Herman, L., Kubíček, P., Šašinková, A., Doležal, M., Tejkl, H., Urbánek, T., et al.: Collaborative immersive virtual environments for education in geography. ISPRS Int. J. Geo Inf. 8(1), 3 (2018)

  27. Stanica, I., Dascalu, M.-I., Bodea, C.N., Moldoveanu, A.D.B.: Vr job interview simulator: where virtual reality meets artificial intelligence for education. In: 2018 zooming innovation in consumer technologies conference (ZINC), IEEE, pp. 9– 12 ( 2018)

  28. Šalkevicius, J., Damaševičius, R., Maskeliunas, R., Laukienė, I.: Anxiety level recognition for virtual reality therapy system using physiological signals. Electronics 8(9), 1039 (2019)

    Article  Google Scholar 

  29. Lazorko, O., Overchuk, V., Zhylin, M., Bereziak, K., Savelchuk, I.: Modern types of psychological correction and their practical application. Syst. Rev. Pharmacy 11(11), 1316–1322 (2020)

    Google Scholar 

  30. LaViola, J.J., Jr., Kruijff, E., McMahan, R.P., Bowman, D., Poupyrev, I.P.: 3D user interfaces: theory and practice. Addison-Wesley Professional, Boston (2017)

    Google Scholar 

  31. Rheinberg, F., Engeser, S., Vollmeyer, R.: Measuring components of flow: the flow-short-scale. In: Proceedings of the 1st international positive psychology summit (2002)

  32. Witmer, B.G., Singer, M.J.: Measuring presence in virtual environments: a presence questionnaire. Presence 7(3), 225–240 (1998)

    Article  Google Scholar 

  33. Wan, B., Guo, J.: Learning immersion assessment model based on multi-dimensional physiological characteristics. In: 2020 IEEE international conference on power, intelligent computing and systems (ICPICS), IEEE, pp. 87– 90 ( 2020)

  34. Wang, X., Desalvo, N., Gao, Z., Zhao, X., Lerman, D.C., Gnawali, O., Shi, W.: Eye contact conditioning in autistic children using virtual reality technology. In: Pervasive computing paradigms for mental health: 4th international symposium, MindCare 2014, Tokyo, Japan, May 8-9, 2014, Revised Selected Papers 4, Springer, pp. 79– 89 ( 2014)

  35. Chakraborty, M., Nafukho, F.M.: Strategies for virtual learning environments: Focusing on teaching presence and teaching immediacy. J. Online Learn. Res. Pract. 4(1) (2015)

  36. Wingrave, C.A., LaViola, J.J.: Reflecting on the design and implementation issues of virtual environments. Presence 19(2), 179–195 (2010)

    Article  Google Scholar 

  37. Sandars, J., Correia, R., Dankbaar, M., Jong, P., Goh, P.S., Hege, I., Masters, K., Oh, S.-Y., Patel, R., Premkumar, K., et al.: Twelve tips for rapidly migrating to online learning during the covid-19 pandemic (2020)

  38. Thoravi Kumaravel, B., Nguyen, C., DiVerdi, S., Hartmann, B.: Tutorivr: A video-based tutorial system for design applications in virtual reality. In: Proceedings of the 2019 CHI conference on human factors in computing systems, pp. 1– 12 ( 2019)

  39. Kao, D., Magana, A.J., Mousas, C.: Evaluating tutorial-based instructions for controllers in virtual reality games. In: Proceedings of the ACM on human-computer interaction 5( CHI PLAY), pp. 1– 28 ( 2021)

Download references

Acknowledgements

We would like to thank all reviewers for their valuable comments. This work is supported by National Key R &D Program of China (2022ZD0118002) and the National Natural Science Foundation of China under Grant (62277035, 62007021 and 61972233).

Author information

Author notes

  1. Yu Wang and Hongqiu Luan have contributed equally to this work.

Authors and Affiliations

  1. School of software, Shandong University, Shunhua Road, Jinan, 250000, Shandong, China

    Yu Wang, Hongqiu Luan, Lutong Wang, Yulong Bian, Xiyu Bao, Wei Gai, Gaorong Lv & Chenglei Yang

  2. College of prison science, The National Police University for Criminal Justice, Qiyi Middle Road, Baoding, 071000, Hebei, China

    Shengzun Song

  3. Academy of fine Arts, Shandong Normal University, Wenhuadong Road, Jinan, 250000, Shandong, China

    Ran Liu

Authors
  1. Yu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hongqiu Luan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lutong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shengzun Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yulong Bian
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xiyu Bao
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ran Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Wei Gai
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Gaorong Lv
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Chenglei Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Shengzun Song, Wei Gai or Gaorong Lv.

Ethics declarations

Conflict of interest

The authors have no conflicts of interest/competing interests to declare that are relevant to the content of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, Y., Luan, H., Wang, L. et al. MGP: a monitoring-based VR interactive mode to support guided practice. Vis Comput 39, 3387–3401 (2023). https://doi.org/10.1007/s00371-023-02950-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-023-02950-7

Keywords

Search

Navigation