Advertisement

Self-learning System Using Lecture Information and Biological Data

  • Yurie Iribe
  • Shuji Shinohara
  • Kyoichi Matsuura
  • Kouichi Katsurada
  • Tsuneo Nitta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4252)

Abstract

One of today’s hot topics in the field of education is the learning support system. With the progress of networks and multimedia technologies, various types of web-based training (WBT) systems are being developed for distance- and self-learning. Most of the current learning support systems synchronously reproduce lecture resources such as videos, slides, and digital-ink notes written by the teacher. However, from the perspective of support for student learning, these systems provide only keyword retrieval. This paper describes a more efficient learning support system that we developed by introducing lecture information and student arousal levels extracted from biological data. We also demonstrate the effectiveness of the proposed system through a preliminary experiment.

Keywords

Arousal Level Lecture Video Learn Support System Blink Duration Lecture Slide 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lee, Y., Geller, J.: A Collaborative and Sharable Web-Based Learning System. International Journal on E-Learning 2(2), 35–45 (2003)Google Scholar
  2. 2.
    Helic, D., Krottmaier, H., Maurer, H., Scerbakov, N.: Enabling Project-Based Learning in WBT Systems. International Journal on E-Learning 4(4), 445–461 (2005)Google Scholar
  3. 3.
    e-Learning Hakusyo 2002/2003, ALIC, Ohmsha, Tokyo (2003)Google Scholar
  4. 4.
    Tamaki, M., Kuwabara, T., Yamada, K., Muto, M., Shimura, A.: Technology Trends in Human Interaction Conscious e-Learning. The Institute of Electronics, Information and Communication Engineers 86(11), 826–833 (2003)Google Scholar
  5. 5.
  6. 6.
    EZ-presentator, Hitachi Advanced Digital, http://www.hitachi-ad.co.jp/ezplat/index.html
  7. 7.
    Ikeya, H., Sato, K., Yamada, H., Nitta, T.: Activating questions and answers between a teacher and students using a web-based lecture system. In: 66th Information Processing Society of Japan, pp. 401–402 (2004)Google Scholar
  8. 8.
    Takagi, T., Miyasaka, E.: A Speech Prosody Conversion System with a High Quality Speech Analysis-Synthesis Method. In: EUROSPEECH 1993, vol. 31(3), pp. 995–998 (1993)Google Scholar
  9. 9.
    Sekiguchi, Y., Suzuki, N., Aono, M., Shinohara, S., Nakauchi, S., Horihata, S., Yasuda, Y.: Prototype System for Intelligent Human Sensing: Using EEG, ECG, EOG and TIP to Detect the State of Mental Concentration and Somnolence. In: Proceedings of the Fourth Symposium on Intelligent Human Sensing IHS 2006, pp. 27–30 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yurie Iribe
    • 1
  • Shuji Shinohara
    • 2
  • Kyoichi Matsuura
    • 2
  • Kouichi Katsurada
    • 2
  • Tsuneo Nitta
    • 2
  1. 1.Information and Media CenterToyohashi University of TechnologyToyohashi-shiJapan
  2. 2.Graduate School of EngineeringToyohashi University of TechnologyToyohashi-shiJapan

Personalised recommendations