Skip to main content
SpringerLink
Log in

A Comprehensive Review of Virtual E-Learning System Challenges

  • Chapter
  • First Online:
Machine Learning and the Internet of Things in Education

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1115))

Abstract

The development of advanced smart electronic devices and application in the twenty-first century has made the World Wide Web a learning platform and easy dissemination of information. This research explore some of the challenges encountered using Virtual E-Learning Systems and proposed recommendations to address some of these challenges. VE-LS has been a medium where tutors pass knowledge by training students in a non-physical form. This has created possibilities as it enhances the efficiency which traditional education and tutoring could not. The Covid-19 virus pandemic disrupted a lot of learning activities over the years, this made academic institutions to merge conventional (Face–Face) and online virtual learning. This process is been led by an instructor in an engaging manner to facilitate learning activities and assist with problem solving. However, several technological challenges were encountered as majority of users were novice and have no idea how to use such systems. In this study, we reviewed some of these challenges and proffer possible solutions to them.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Buhari, B. A., & Roko, A. (2017). An improved e-learning system. Saudi Journal of Engineering and Technology, 2(2), 114–118.

    Google Scholar 

  2. Hazwani Mohd, N., Noor Raudhiah Abu, B., & Norziah, O. (2020). E-Pembelajaran Dalam Kalangan Pelajar Di Sebuah Institusi Pengajian Tinggi Selangor. Selangor. Malaysian atas talian. Journal of Education.

    Google Scholar 

  3. Irfan, F., & Iman Hermawan Sastra, K. (2020). Teachers elementary school in atas talian learning of COVID-19 pandemic conditions. Jakarta. Jurnal Iqra’.

    Google Scholar 

  4. Ja'ashan, M. M. N. H. (2020). The challenges and prospects of using e-learning among EFL students in Bisha University. Arab World English Journal, 11(1), 124–137. https://doi.org/10.24093/awej/vol11no1.11

  5. Ali, S., Hafeez, Y., Abbas, M. A., Aqib, M., & Nawaz, A. (2021). Enabling remote learning system for virtual personalized preferences during COVID-19 pandemic. Multimedia Tools and Applications, 80, 33329–33355.

    Article  Google Scholar 

  6. Renée, C. (n.d). Getting to know the blackboard learning system. Manager: eLearning, 043704(7031), 1.

    Google Scholar 

  7. Lungu, M. (2016). Studyportalsonlinecourse. Retrieved February 3, 2023, from Distancelearningportal: https://www.distancelearningportal.com

  8. Jabr, M. A., & Al-omari, H. K. (2010). E-learning management system using service oriented architecture.

    Google Scholar 

  9. Siddiqui, A. T., & Masud, M. (2012). An e-learning system for quality education. International Journal of Computer Science Issues (IJCSI), 9(4), 375.

    Google Scholar 

  10. Salihu, A. (2013). Designed and implemented an elearning system for a vocational study Centre, Jedo Computer Institute.

    Google Scholar 

  11. Abiyev, R., Arslan, M., Bush Idoko, J., Sekeroglu, B., & Ilhan, A. (2020). Identification of epileptic EEG signals using convolutional neural networks. Applied Sciences, 10(12), 4089.

    Article  Google Scholar 

  12. Abiyev, R. H., Arslan, M., & Idoko, J. B. (2020). Sign language translation using deep convolutional neural networks. KSII Transactions on Internet & Information Systems, 14(2).

    Google Scholar 

  13. Helwan, A., Idoko, J. B., & Abiyev, R. H. (2017). Machine learning techniques for classification of breast tissue. Procedia Computer Science, 120, 402–410.

    Article  Google Scholar 

  14. Sekeroglu, B., Abiyev, R., Ilhan, A., Arslan, M., & Idoko, J. B. (2021). Systematic literature review on machine learning and student performance prediction: Critical gaps and possible remedies. Applied Sciences, 11(22), 10907.

    Article  Google Scholar 

  15. Idoko, J. B., Arslan, M., & Abiyev, R. (2018). Fuzzy neural system application to differential diagnosis of erythemato-squamous diseases. Cyprus Journal of Medical Sciences, 3(2), 90–97.

    Article  Google Scholar 

  16. Ma’aitah, M. K. S., Abiyev, R., & Bush, I. J. (2017). Intelligent classification of liver disorder using fuzzy neural system. International Journal of Advanced Computer Science and Applications, 8(12).

    Google Scholar 

  17. Bush, I. J., Abiyev, R., Ma’aitah, M. K. S., & Altıparmak, H. (2018). Integrated artificial intelligence algorithm for skin detection. In ITM Web of conferences (Vol. 16, p. 02004). EDP Sciences.

    Google Scholar 

  18. Bush, I. J., Abiyev, R., & Arslan, M. (2019). Impact of machine learning techniques on hand gesture recognition. Journal of Intelligent & Fuzzy Systems, 37(3), 4241–4252.

    Article  Google Scholar 

  19. Uwanuakwa, I. D., Idoko, J. B., Mbadike, E., Reşatoğlu, R., & Alaneme, G. (2022). Application of deep learning in structural health management of concrete structures. In Proceedings of the Institution of Civil Engineers-Bridge Engineering (pp. 1–8). Thomas Telford Ltd.

    Google Scholar 

  20. Helwan, A., Dilber, U. O., Abiyev, R., & Bush, J. (2017). One-year survival prediction of myocardial infarction. International Journal of Advanced Computer Science and Applications, 8(6). https://doi.org/10.14569/IJACSA.2017.080622

  21. Bush, I. J., Abiyev, R. H., & Mohammad, K. M. (2017). Intelligent machine learning algorithms for colour segmentation. WSEAS Transactions on Signal Processing, 13, 232–240.

    Google Scholar 

  22. Dimililer, K., & Bush, I. J. (2017). Automated classification of fruits: Pawpaw fruit as a case study. In Man-Machine Interactions 5: 5th International Conference on Man-Machine Interactions, ICMMI 2017 Held at Kraków, Poland, October 3–6, 2017 (pp. 365–374). Springer International Publishing.

    Google Scholar 

  23. Bush, I. J., & Dimililer, K. (2017). Static and dynamic pedestrian detection algorithm for visual based driver assistive system. In ITM Web of Conferences (Vol. 9, p. 03002). EDP Sciences.

    Google Scholar 

  24. Abiyev, R., Idoko, J. B., & Arslan, M. (2020). Reconstruction of convolutional neural network for sign language recognition. In 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) (pp. 1–5). IEEE.

    Google Scholar 

  25. Abiyev, R., Idoko, J. B., Altıparmak, H., & Tüzünkan, M. (2023). Fetal health state detection using interval type-2 fuzzy neural networks. Diagnostics, 13(10), 1690.

    Article  Google Scholar 

  26. Arslan, M., Bush, I. J., & Abiyev, R. H. (2019). Head movement mouse control using convolutional neural network for people with disabilities. In 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing—ICAFS-2018 (Vol. 13, pp. 239–248). Springer International Publishing.

    Google Scholar 

  27. Abiyev, R. H., Idoko, J. B., & Dara, R. (2022). Fuzzy neural networks for detection kidney diseases. In Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation: Proceedings of the INFUS 2021 Conference, held August 24–26, 2021 (Vol. 2, pp. 273–280). Springer International Publishing.

    Google Scholar 

  28. Uwanuakwa, I. D., Isienyi, U. G., Bush Idoko, J., & Ismael Albrka, S. (2020). Traffic warning system for wildlife road crossing accidents using artificial intelligence. In International Conference on Transportation and Development 2020 (pp. 194–203). American Society of Civil Engineers.

    Google Scholar 

  29. Idoko, B., Idoko, J. B., Kazaure, Y. Z. M., Ibrahim, Y. M., Akinsola, F. A., & Raji, A. R. (2022). IoT based motion detector using Raspberry Pi gadgetry. In 2022 5th Information Technology for Education and Development (ITED) (pp. 1–5). IEEE.

    Google Scholar 

  30. Idoko, J. B., Arslan, M., & Abiyev, R. H. (2019). Intensive investigation in differential diagnosis of erythemato-squamous diseases. In Proceedings of the 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing (ICAFS-2018) (Vol. 10, pp. 978–3).

    Google Scholar 

  31. Assareh, A., & Bidokht, M. H. (2011). Barriers to e-teaching and e-learning. Procedia Computer Science, 3, 791–795.

    Article  Google Scholar 

  32. Saleh, E. (2020). Using e-learning platform for enhancing teaching and learning in the field of social work at Sultan Qaboos University, Oman. In E-Learning and Digital Education in the Twenty-First Century. Intech Open.

    Google Scholar 

  33. Graydon, M., & Parks, L. (2020). ‘Connecting the unconnected’: A critical assessment of US satellite Internet services. Media, Culture & Society, 42(2), 260–276.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Applied Artificial Intelligence Research Centre, Department of Computer Engineering, Near East University, Nicosia, 99138, Turkey

    John Bush Idoko

  2. Department of Information Systems Engineering, Near East University, Nicosia, 99138, Turkey

    Joseph Palmer

Authors
  1. John Bush Idoko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joseph Palmer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to John Bush Idoko .

Editor information

Editors and Affiliations

  1. Computer Engineering Department, Near East University, Lefkosa, Cyprus

    John Bush Idoko

  2. Department of Computer Engineering, Near East University, Nicosia, Cyprus

    Rahib Abiyev

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Idoko, J.B., Palmer, J. (2023). A Comprehensive Review of Virtual E-Learning System Challenges. In: Idoko, J.B., Abiyev, R. (eds) Machine Learning and the Internet of Things in Education. Studies in Computational Intelligence, vol 1115. Springer, Cham. https://doi.org/10.1007/978-3-031-42924-8_11

Download citation

Publish with us

Policies and ethics

Search

Navigation