Skip to main content

Monitoring Level Attention Approach in Learning Activities

  • Conference paper
  • First Online:
Methodologies and Intelligent Systems for Technology Enhanced Learning

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 478))

Abstract

In this article we focus on a new field of application of ICT techniques and technologies in learning activities. With these activities with computer platforms, attention allows us to break down the problem of understanding a speculative scenario into a series of computationally less demanding and localized lack of attention. The system considers the students’ attention level while performing a task in learning activities. The goal is to propose an archi-tecture that measures the level of attentiveness in real scenario, and detect patterns of behavior in different attention levels among different students. Measurements of attention level are obtained by a proposed model, and user for training a decision support system that in a real scenario makes recommendations for the teachers so as to prevent undesirable behavior.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Smith, L.H., Renzulli, J.S.: Learning style preferences: A practical approach for classroom teachers. Theory into Practice 23(1), 44–50 (1984). doi:10.1080/00405848409543088

    Article  Google Scholar 

  2. James, W.: The principles of Psychology – Part 1. Read Books, Ltd. pp. 220–270 (2013)

    Google Scholar 

  3. Yu-Fei M., Hong J.: Contrast-based image attention analysis by using fuzzy growing. In: ACM Multimedia, pp. 374–381 (2003)

    Google Scholar 

  4. Rodrigues, M., Gonçalves, S., Carneiro, D., Novais P., Fdez-Riverola, F.: Keystrokes and clicks: measuring stress on E-learning students. In: Management Intelligent System, vol. 220, pp. 119–126 (2013)

    Google Scholar 

  5. Pimenta, A., Carneiro, D., Neves, J., Novais, P.: A Neural Network to Classify Fatigue from Human-Computer Interaction. Neurocomputing 172, 413–426 (2015)

    Article  Google Scholar 

  6. Carneiro, D., Novais, P., Pêgo, J.M., Sousa, N., Neves, J.: Using mouse dynamics to assess during online exams. In: Hybrid Artificial Intelligent Systems, vol. 9121, pp. 345–356 (2015)

    Google Scholar 

  7. Gardell, B.: Worker Participation and Autonomy: a Multilevel Approach to Democracy at the Workplace. International Journal of Health Services 4, 527–558 (1982)

    Article  Google Scholar 

  8. Rodrigues, M., Riverola, F., Novais, P.: Na approach to Assess Stress in E-learning Students (2012)

    Google Scholar 

  9. Meijman, T.F.: Mental Fatigue and the Efficiency of Information Processing in Relation to Work Times. International Journal of Industrial Ergonomics 20(1), 31–38 (1997)

    Article  Google Scholar 

  10. Bartlett, F.C.: Ferrier Lecture: Fatigue Following Highly Skilled Work. Proceedings of the Royal Society of London. Series B-Biological Sciences 131(863), 247–257 (1943)

    Google Scholar 

  11. Faber, L.G., Maurits, N.M., Lorist, M.M.: Menatl Fatigue Affects Visual Selective Attention. PloS One 7(10), e48073 (2012)

    Article  Google Scholar 

  12. Lorist, M.M., Kleim, M., Nieuwenhuis, S., Jong, R., Mulder, G., Meijman, T.F.: Mental Fatigue and Task Control: Planning and Preparation. Psychophysiology 37(5), 614–625 (2000)

    Article  Google Scholar 

  13. Pimenta, A., Gonçalves, S., Carneiro, D., Fde-Riverola, F., Novais, P.: Mental Workload Management as a Tool in e-learning Scenarios (2015)

    Google Scholar 

  14. Van der Linden, D., Frese, M., Meijman, T.F.: Mental Fatigue and the Control of Cognitive Processes: Effects on Perseveration and Planning. Acta Psychologica 113(1), 45–65 (2003)

    Article  Google Scholar 

  15. Eysenck, M.W., Derakshan, N., Santos, R., Calvo, M.G.: American Psychological Association 7(2), 336–353 (2007)

    Google Scholar 

  16. Trigwell, K., Ellis, R., Han, F.: Relations between students’ approaches to learning, experienced emotions and outcomes of learning. Studies in Higher Education 37(7), 811–824 (2012). doi:10.1080/03075079.2010.549220

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dalila Durães .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Durães, D., Jiménez, A., Bajo, J., Novais, P. (2016). Monitoring Level Attention Approach in Learning Activities. In: Caporuscio, M., De la Prieta, F., Di Mascio, T., Gennari, R., Gutiérrez Rodríguez, J., Vittorini, P. (eds) Methodologies and Intelligent Systems for Technology Enhanced Learning . Advances in Intelligent Systems and Computing, vol 478. Springer, Cham. https://doi.org/10.1007/978-3-319-40165-2_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-40165-2_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40164-5

  • Online ISBN: 978-3-319-40165-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics