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Attention Profiling Algorithm for Video-Based Lectures

  • Josef Wachtler
  • Martin Ebner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8523)

Abstract

Due to the fact that students’ attention is the most crucial resource in a high-quality course it is from high importance to control and analyze it. This could be done by using the interaction and the communication because they are known as valuable influencing factors of the attention. In this publication we introduce a web-based information system which implements an attention-profiling algorithm for learning-videos as well as live-broadcastings of lectures. For that different methods of interaction are offered and analyzed. The evaluation points out that the attention profiling algorithm delivers realistic values.

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References

  1. 1.
    Shiffrin, R.M., Gardner, G.T.: Visual processing capacity and attentional control. Journal of Experimental Psychology 93(1), 72–82 (1972)CrossRefGoogle Scholar
  2. 2.
    Moran, J., Desimone, R.: Selective attention gates visual processing in the extrastriate cortex. Science 229, 782–784 (1985)CrossRefGoogle Scholar
  3. 3.
    Heinze, H.J., Mangun, G.R., Burchert, W., Hinrichs, H., Scholz, M., Münte, T.F., Gös, A., Scherg, M., Johannes, S., Hundeshagen, H., Gazzaniga, M.S., Hillyard, S.A.: Combined spatial and temporal imaging of brain activity during visual selective attention in humans. Nature 372, 543–546 (1994)CrossRefGoogle Scholar
  4. 4.
    Spitzer, H., Desimone, R., Moran, J.: Increased attention enhances both behavioral and neuronal performance. Science 240, 338–340 (1988)CrossRefGoogle Scholar
  5. 5.
    Ebner, M., Wachtler, J., Holzinger, A.: Introducing an information system for successful support of selective attention in online courses. In: Stephanidis, C., Antona, M. (eds.) UAHCI 2013, Part III. LNCS, vol. 8011, pp. 153–162. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  6. 6.
    Carr-Chellman, A., Duchastel, P.: The ideal online course. British Journal of Educational Technology 31(3), 229–241 (2000)CrossRefGoogle Scholar
  7. 7.
    Helmerich, J., Scherer, J.: Interaktion zwischen lehrenden und lernenden in medien unterstützten veranstaltungen. In: Breitner, M.H., Bruns, B., Lehner, F. (eds.) Neue Trends im E-Learning, pp. 197–210. Physica-Verlag HD (2007)Google Scholar
  8. 8.
    Tobin, B.: Audience response systems, stanford university school of medicine (2005), http://med.stanford.edu/irt/edtech/contacts/documents/2005-11_AAMC_tobin_audience_response_systems.pdf (online; accessed October 9, 2012)
  9. 9.
    Ebner, M.: Introducing live microblogging: how single presentations can be enhanced by the mass. Journal of Research in Innovative Teaching 2(1), 91–100 (2009)Google Scholar
  10. 10.
    Stowell, J.R., Nelson, J.M.: Benefits of electronic audience response systems on student participation, learning, and emotion. Teaching of Psychology 34(4), 253–258 (2007)CrossRefGoogle Scholar
  11. 11.
    Latessa, R., Mouw, D.: Use of an audience response system to augment interactive learning. Family Medicine 37(1), 12–14 (2005)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Josef Wachtler
    • 1
  • Martin Ebner
    • 1
  1. 1.Graz University of TechnologyAustria

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