AIRCC's International Journal of Computer Science and Information Technology

Open Access Open Access  Restricted Access Subscription Access

Web-Based Learning in Periods of Crisis: Reflections on the Impact of COVID-19


Affiliations
1 Department of Computer Science, University of Benin, Benin City, Nigeria
2 Africa PPP Advisory Nigeria Limited, Abuja, Nigeria
 

Education systems and its actors are generally responding to quarantine and large-scale shutdown (partial) of cities with a sudden shift to Web-Based Learning. However, given that a pandemic of this nature and scale is novel, there is a knowledge gap as to how teachers and learners should respond to the shift, and what the likely impact and the key considerations should be. This study aims to extrapolate and theorize from the existing knowledgebase about the use of Web-Based Learning, as well as from an expert and practitioner wisdom and experience, to offer high-level guidance for policymakers and education system actors that are forced to make decisions in fast-moving and very challenging circumstances with little guidance or relevant experience. It is an early attempt at theorizing the impact of the pandemic on two key actors (Learners and Teachers) and one interface (Content), all across eight dimensions of learning. The analysis is based on Khan’s (2001) dimension of Web-Based Learning and Anderson’s (2011) Model of Online Learning. Overall, we posit based on experience and practice, that the pandemic has delivered severe shocks to both the demand and supply side of Web-Based Learning, with Leaners, Teachers, and Content all significantly affected. While we hypothesize a general drop in the quality of teaching and learning in the short run, we expect the opposite to be the case in the long run, when the demand and supply side self-correct, albeit guided by strong government and market institutions.

Keywords

Web-Based Learning, COVID-19, Learners.
User
Notifications
Font Size

  • Alison, G. (2017). Beyond Access: Addressing Digital Inequality in Africa. Centre for International Governance Innovation and Chatham House. Paper Series: No. 48

  • Anderson, T. (2011). The theory and practice of online learning (2nd Edition). Edmonton, AB: AU Press.

  • Anderson, T., Rourke, L., Garrison, D.R, and Archer, W. (2001). Assessing social presence in asynchronous text-based computer conferencing. Journal of Asynchronous Learning Networks, 5(2) Retrieved from: http://immagic.com/eLibrary/ARCHIVES/GENERAL/ATHAB_CA/Anderson.pdf

  • Archambault, L. (2010). Identifying and addressing teaching challenges in k-12 online environments. Distance Learning, 7(2), pp. 13-17.

  • Counted, A. and Arawole, J. (2016). We are connected, but constrained’: internet inequality and the challenges of millennials in Africa as actors in innovation. Journal in Innovation and Entrepreneurship 5(3), https://doi.org/10.1186/s13731-015-0029-1

  • Dalton, K. and Gren, I. (2015). Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions: Lessons for adopters. International Journal of Education and Development using Information and Communication Technology (IJEDICT);11(2),126-137.

  • Garrison, D. R., Anderson, T., and Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education model. The Internet and Higher Education, 2(2-3), 87-105.

  • Gennaioli, la Porta, Lopez-de-silanes and Shleifer, (2011). Human Capital and Regional Development, NBER working Paper 17158.

  • Ghavifekr, S. and Rosdy, W.A.W. (2015). Teaching and learning with technology: Effectiveness of ICT integration in schools. International Journal of Research in Education and Science (IJRES), 1(2), 175-191.

  • Harasim, L. (2012). Learning theory and online technologies. New York: Routledge/Taylor & Francis.

  • Kahn, B. H. (2001). Web-based training: An introduction. In B.H. Kahn (Ed.) Web-based Training. Englewood Cliffs, NJ.: Educational Technology Publications.

  • Kwanjai D. (2014). The design of web-based learning model using collaborative learning techniques and a scaffolding system to enhance learners’ competency in higher education. 5th World Conference on Educational Sciences - WCES 2013. Procedia - Social and Behavioral Sciences; 116, 436 – 441

  • Moeketsi Letseka, Matsephe Martha Letseka and Victor Pitsoe (November 5th 2018). The Challenges of E-learning in South Africa, Trends in E-learning, Mahmut Sinecen, IntechOpen, DOI: 10.5772/intechopen.74843. Available from: https://www.intechopen.com/books/trends-in-e-learning/the-challenges-of-e-learning-in-south-africa

  • Nagunwa, T. and Lwoga, E. 2012. “Developing eLearning technologies to implement competency based medical education: Experiences from Muhimbili University of Health and Allied Sciences”, International Journal of Education and Development using Information and Communication Technology (IJEDICT), vol. 8, no. 3, pp. 07-21.

  • Picciano, A. G. (2017). Theories and frameworks for online education: Seeking an integrated model. Online Learning, 21(3), 166-190. doi: 10.24059/olj.v21i3.1225

  • Said H. (2010). A Conceptual Framework for Using and Evaluating Web-Based Learning Resources in School Education. Journal of Information Technology Education; 9,53-79.

  • Sanga, C., Magesa, M. M., Chingonikaya, E. and Kayunze, K. A. 2013. “Can e-learning promote participation of female students in STEM disciplines in higher learning institutions of Tanzania?”, International Journal of Education and Development using Information and Communication Technology (IJEDICT), vol.9, no.3, pp. 86-102.

  • Siemens, G. (2004). Connectivism: A learning theory for the digital age. Paper retrieved from: http://www.elearnspace.org/Articles/connectivism.htm

  • Sudha, A. and Amutha S. (2015) Higher Secondary Learners’ Effectiveness towards Web Based Instruction (WBI) on Chemistry. Universal Journal of Educational Research, 3(7): 463-466. DOI:10.13189/ujer.2015.030706

  • The European-wide e-Learning Recognition Review Report (2015). Retrieved from: http://www.elearningnews.it/_resources/images/ebook/european-wide-elearning-recognitionreview.Pdf.

  • The World Bank. (2010). ICTs & education: Issues and opportunities. Report. Retrieved June 30, 2011 from http://siteresources.worldbank.org/EDUCATION/Resources/ESSU/463292-1290618190826/Background_Note_EducationStrategy2020_ICT_Edu.pdf

  • Titiana C (2019). Design of Web-Based Learning Model: Shifting the Accent from Knowledge Transmission to Knowledge Construction. Proceedings of the Central and Eastern European, 177-189 23. Todaro, M. and Smith, S. (2011). Economic Development, (11th ed.), Addison Wesley, 2011.

  • Van Reijswoud, V. (2009). Appropriate ICT as a tool to increase effectiveness in ICT4D: Theoretical considerations and illustrating cases. The Electronic Journal on Information Systems in Developing Countries, 38(9), 1–18.

  • Yongxia, D. and Peili Z. (2018). Practice and effectiveness of web-based problem-based learning approach in a large class-size system: A comparative study. Nurse Education in Practice, 31;161-164


Abstract Views: 299

PDF Views: 183




  • Web-Based Learning in Periods of Crisis: Reflections on the Impact of COVID-19

Abstract Views: 299  |  PDF Views: 183

Authors

Stella Chiemeke
Department of Computer Science, University of Benin, Benin City, Nigeria
Omokhagbo Mike Imafidor
Africa PPP Advisory Nigeria Limited, Abuja, Nigeria

Abstract


Education systems and its actors are generally responding to quarantine and large-scale shutdown (partial) of cities with a sudden shift to Web-Based Learning. However, given that a pandemic of this nature and scale is novel, there is a knowledge gap as to how teachers and learners should respond to the shift, and what the likely impact and the key considerations should be. This study aims to extrapolate and theorize from the existing knowledgebase about the use of Web-Based Learning, as well as from an expert and practitioner wisdom and experience, to offer high-level guidance for policymakers and education system actors that are forced to make decisions in fast-moving and very challenging circumstances with little guidance or relevant experience. It is an early attempt at theorizing the impact of the pandemic on two key actors (Learners and Teachers) and one interface (Content), all across eight dimensions of learning. The analysis is based on Khan’s (2001) dimension of Web-Based Learning and Anderson’s (2011) Model of Online Learning. Overall, we posit based on experience and practice, that the pandemic has delivered severe shocks to both the demand and supply side of Web-Based Learning, with Leaners, Teachers, and Content all significantly affected. While we hypothesize a general drop in the quality of teaching and learning in the short run, we expect the opposite to be the case in the long run, when the demand and supply side self-correct, albeit guided by strong government and market institutions.

Keywords


Web-Based Learning, COVID-19, Learners.

References