Effects of Guided and Unguided Style Learning on User Attention in a Virtual Environment

  • Jayoung J. Goo
  • Kyoung S. Park
  • Moonhoen Lee
  • Jieun Park
  • Minsoo Hahn
  • Hyungil Ahn
  • Rosalind W. Picard
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3942)


In this paper, we investigated the effects of guided and unguided style VR learning on user attention and retained knowledge. We conducted a study where users performed guided or unguided style learning in the virtual environment while user attention was measured through an eye tracking system and physiological sensors. The virtual environment contained the five specific events associated with different stimuli, but the guided task was designed to provide the specific goals whereas the unguided task asked the user to actively search for the interesting items. The results showed that the unguided task followed by the guided task made a considerable learning effect by giving a preview to the user. In addition, tactile feedback, sudden view point change, unique appearance and behavior, and sound stimuli played an important factor in increasing human attention states that also induced enhancing human memory about VR experience.


Heart Rate Variability Virtual Reality Virtual Environment Skin Conductance Response Memorable Item 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Cho, B.H., et al.: Attention Enhancement System using Virtual Reality and EEG Biofeedback. Proceedings of the IEEE Virtual Reality (2002)Google Scholar
  2. 2.
    Mantovani, F.: VR Learning: Potential and Challenges for the Use of 3D Environments in Education and Trainings. CyberPshchology (2003)Google Scholar
  3. 3.
    Bricken, M.: Virtual Reality Learning Environments: Potential and Challenges. In: Proceedings of the SIGGRAPH 1991, ACM SIGGRAPH, pp. 178–184 (1991)Google Scholar
  4. 4.
    Dede, C., Salzman, M., Loftin, R.B., Ash, K.: Using Virtual Reality Technology to Convey Abstract Scientific Concepts. Learning the Sciences of the 21st Century: research, Design and Implementing Advanced Technology Learning Environments (1997)Google Scholar
  5. 5.
    Furness, A., Winn, W., Yu, R.: The Impact of Three Dimensional Immersive Virtual Environments on Modern Pedagogy: Global Change, VR and Learning. In: Proceedings of Workshops in Seattle, Washington, and Loughborough, England (1997)Google Scholar
  6. 6.
    Salzman, M.C., Dede, C., McGlynn, D., Loftin, R.B.: ScienceSpace: Lessons for Designing Immersive Virtual Realities. In: Proceedings of the CHI 1996: ACM conference on Human Factors in Computing Systems, pp. 89–90. ACM, New York (1996)Google Scholar
  7. 7.
    Salzman, M.C., Dede, C., Loftin, R.B.: Learner-centered design of sensorily immersive microworlds using a virtual reality interface. In: Proceedings of the AI-ED 1995: 7th World Conference on Artificial Intelligence in Education, pp. 554–561. Association for Advancement of Computer Education, Charlottesville (1995)Google Scholar
  8. 8.
    Whitelock, D., Brna, P., Holland, S.: What is the Value of Virtual Reality for Conceptual Learning? Towards a Theoretical Framework. In: Proceedings of the Euro AI-Ed: European Conference on AI in Education. University of Leeds, Leeds (1996)Google Scholar
  9. 9.
    Allison, D., Hodges, L.F.: Virtual Reality for Education? In: VRST, Seoul, Korea. ACM, New York (2000) 1-58113-316-2/00/0010Google Scholar
  10. 10.
    Brown, D.J., Wilson, J.R.: LIVE: Learning in Virtual Environments, Ability. The Journal of the British Computer Society 15, 24–25 (1995)Google Scholar
  11. 11.
    Spencer, K.M., Polich, J.: Poststimulus EEG spectral analysis and P300: Attention, task, and probability. Psychophysiology 36, 220–232 (1999)CrossRefGoogle Scholar
  12. 12.
    Healey, J.A.: Wearable and Automotive Systems for Affect Recognition from Physiology. PhD thesis at the MIT (2000)Google Scholar
  13. 13.
    Tripathi, C.K., Mukundan, C., Mathew, T.L.: Attentional modulation of heart rate variability (HRV) during execution of PC based cognitive tasks. Ind J Aerospace Med 47(1) (2003)Google Scholar
  14. 14.
    Chen, D., Vertegaal, R.: Using Mental Load for Managing Interruptions. Physiologically Attentive User Interfaces (2004)Google Scholar
  15. 15.
    Raposa, J.: Biofeedback in Educational Entertainment. Master thesis at Interaction Design institute Ivrea (2003)Google Scholar
  16. 16.
    Kim, S.H., et al.: Clinical Study on Cerebral Lateralization of Attention by Using Heart Rate. Journal of Korean Neurological Association 5(2) (December 1987)Google Scholar
  17. 17.
    Youngblut, C.: Educational Uses of Virtual Reality Technology. Institute for Defense Analyses (January 1998)Google Scholar
  18. 18.
    Duchowski, A.T., et al.: Binocular Eye Tracking in VR for Visual Inspection Training. In: Proceedings of VRST (2001)Google Scholar
  19. 19.
    Yee, H., Pattanaik, S., Greenberg, D.P.: Spatiotemporal Sensitivity and Visual Attention for Efficient Rendering of Dynamic Environments. ACM Transactions on Graphics 20(1), 39–65 (2001)CrossRefGoogle Scholar
  20. 20.
    Iqbal, S.T., Zheng, X.S., Bailey, B.P.: Task-Evoked Pupillary Response to Mental Workload in Human-Computer Interaction. In: CHI 2004, Vienna, Austria, April 24-29. ACM, New York (2004) 1-58113-703-6/04/0004Google Scholar
  21. 21.
    Homan, W.J.: Virtual Reality: Real Promises and False Expectations. EMI: Educational Media International 31(4), 224–227 (1994)CrossRefGoogle Scholar
  22. 22.
    Schroeder, R.: Learning from Virtual Reality Applications in Education. Virtual Reality 1(1), 33–40 (1995)CrossRefGoogle Scholar
  23. 23.
    Cronin, P.: Report on the Applications of Virtual Reality Technology to Education. HCRC. University of Edinburgh, Edinburgh (1997), Electronic Document, http://www.cogsci.ed.ac.uk/~paulus/vr.htm
  24. 24.
    Rose, H.: Assessing Learning in VR: Towards Developing a Paradigm, Virtual Reality Roving Vehicles (VRRV) Project. HITL Publication TR-95-1: Seattle, WA: Human Interface Technology Laboratory (1995)Google Scholar
  25. 25.
    Carr, K., England, R.: Simulated and Virtual Realities: Elements of Perception. Taylor and Francis, London (1995)Google Scholar
  26. 26.
    Hjelm, S.I., Browall, C.: Brainball using brain activity for cool competition. Media lab EuropeGoogle Scholar
  27. 27.
    Schwarz, G.: Specific Problems in Interpretation of Absolute Values of Spectral Edge Frequency (SEF) in comparison to Bispectral Index (BIS) for Assessing Depth of Anesthesia. The Internet Journal of Neuromonitoring ISSN: 1531-300XGoogle Scholar
  28. 28.
    Li, Q., Sun, L., Duan, J.: Web Page Viewing Behavior of Users: An Eye-Tracking Study. IEEE, Los Alamitos (2005) 0-7803-8971-9/05/Google Scholar
  29. 29.
    Duchowski, A.T.: A Breadth-First Survey of Eye Tracking Applications, Behavior Research Methods. Instruments, and Computers (BRMIC) 34(4), 455–470 (2002)CrossRefGoogle Scholar
  30. 30.
    Picard, R.E., Vyzas, E., Healy, J.: Toward Machine Emotional Intelligence: Analysis of Affective Physiological State. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(10), 1175–1191 (2001)CrossRefGoogle Scholar
  31. 31.

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jayoung J. Goo
    • 1
  • Kyoung S. Park
    • 1
  • Moonhoen Lee
    • 1
  • Jieun Park
    • 1
  • Minsoo Hahn
    • 1
  • Hyungil Ahn
    • 2
  • Rosalind W. Picard
    • 2
  1. 1.Digital Media LabInformation and Communications UniversitySeoulRepublic of Korea
  2. 2.M.I.T. Media LaboratoryCambridgeUSA

Personalised recommendations