Skip to main content
Book cover

International Conference on Advanced Information Networking and Applications

AINA 2022: Advanced Information Networking and Applications pp 14–22Cite as

Machine Learning for Student QoE Prediction in Mobile Learning During COVID-19

  • 367 Accesses

Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 451)

Abstract

The emergence of COVID-19 has shaped a new type of learning that is called “digital learning”, which can be approached through e-learning and m-learning technologies. An important element in reducing student dropout rates in a virtual learning is to understand the degree of engagement and satisfaction experienced by students in meaningful activities. The major novel contribution of this study is the combination of network Quality of Service (QoS) parameters and student engagement behavior (through eye-tracking) to automatically estimate the Mean Opinion Score (MOS) for mobile learning synchronous activities. Several machine learning algorithms were compared for best QoE prediction.

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-99619-2_2
  • Chapter length: 9 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   219.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-99619-2
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   279.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.

References

  1. Alsabawy, Y.A., Cater-Steel, A., Soar, J.: Identifying the determinants of e-learning service delivery quality. In: 23rd Australian Conference on Information Systems, 3–5 Dec 2012, Greelong (2012)

    Google Scholar 

  2. Qualinet White Paper on Definitions of Quality of Experience (2012). European Network on Quality of Experience in Multimedia Systems and Services (COST Action IC 1003), Patrick Le Callet, Sebastian Möller and Andrew Perkis, eds., Lausanne, Switzerland, Version 1.2 (2013)

    Google Scholar 

  3. Ahmad, W.R.A., Kara, P.A., Atzori, L., Martini, M.G., Raake, A, Sun, L.: Challenges of future multimedia qoe monitoring for internet service providers. Multimedia Tools Appl. 76(21), 22 243–22 266 (2017)

    Google Scholar 

  4. Taha, M., Abu Ali, N., Ran Chi, H., Radwan, A.: MEC resource offloading for QoE-Aware has video streaming. In: Communications ICC 2021, pp. 1–5 (2021)

    Google Scholar 

  5. Anchuen, P., Uthansakul, P., Uthansakul, M.: QoE analysis for improving multimedia services based on different operating situations on cellular networks. Access IEEE 9, 116215–116230 (2021)

    CrossRef  Google Scholar 

  6. Seufert, M., Wehner, N., Wamser, F., Casas, P., D’Alconzo, A., TranGia, P.: Unsupervised QoE field study for mobile youtube video streaming with yomoapp. In: QoMEX, pp. 1–6 (2017)

    Google Scholar 

  7. Katsarakis, M., Teixeira, R.C., Papadopouli, M., Christophides, V.: Towards a causal analysis of video QoE from network and application QoS. In: Proceedings of the Internet QoE’16. ACM (2016)

    Google Scholar 

  8. ITU-T Rec. P.10/G.100: Vocabulary for performance and quality of service. Amendment 5: New definitions for inclusion in Recommendation ITU-T P.10/G.100 (2016)

    Google Scholar 

  9. www.mininet.org

Download references

Author information

Authors and Affiliations

  1. INNOVCOM LAB, SUPCOM, University of Carthage, Tunis, Tunisia

    Besma Korchani & Kaouthar Sethom

Authors
  1. Besma Korchani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kaouthar Sethom
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kaouthar Sethom .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Prof. Dr. Leonard Barolli

  2. University of Technology Sydney, Sydney, NSW, Australia

    Prof. Farookh Hussain

  3. Faculty of Bussiness Administration, Rissho University, Tokyo, Japan

    Prof. Tomoya Enokido

Rights and permissions

Reprints and Permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Korchani, B., Sethom, K. (2022). Machine Learning for Student QoE Prediction in Mobile Learning During COVID-19. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 451. Springer, Cham. https://doi.org/10.1007/978-3-030-99619-2_2

Download citation