Impact of the COVID-19 pandemic on IT competencies of students

Authors

  • Maria Kocot University of Economics in Katowice
  • Artur Kwasek University of Technology and Economics

DOI:

https://doi.org/10.15584/nsawg.2023.3.5

Keywords:

IT skills, COVID-19 pandemic, students

Abstract

In the current COVID-19 pandemic era, computer skills have become essential for students and academic staff who participate in remote learning or work on online projects, research, and analysis. Due to the need to shift many activities and projects to the virtual world, having computer skills has become critical for effective functioning in the current situation. The aim of the article was to investigate the level of computer competencies of students in the context of the COVID-19 pandemic. The hypothesis was that most respondents have basic computer skills, but they may have varying levels of proficiency in specific computer competencies, such as the use of new software. To achieve this goal, the authors presented empirical research results conducted in February 2021. The study sample included 649 respondents.
The research show that the majority of the respondents declared possessing computer competencies such as the use of computers, smartphones/phones, technical internet support, and mobile devices and applications. However, there were some individuals who faced difficulties in operating new software. Therefore, it was recommended to focus on developing computer competencies in the area of new software use through training or courses that will assist those who have difficulty in this area. It is also important to continue monitoring progress and the effectiveness of such actions. This will increase the level of computer competencies in the whole group of respondents, which may contribute to improving work efficiency and increasing job market opportunities. The conducted Pearson correlation allowed us to draw the following conclusions: there are strong positive correlations between all pairs of IT skills, which suggests a mutual relationship.

References

Ala-Mutka, K. (2011). Mapping Digital Competence: Towards a Conceptual Understanding. JRC Technical Reports, JRC67075, 70–75. DOI: 10.13140/RG.2.2.18046.00322.

Al-Samarrai, S., Gangwar, M., Gala, P. (2020). The Impact of the COVID-19 Pandemic on Education Financing. Economic Impact of COVID-19. World Bank. Retrieved from: http://hdl.handle.net/10986/33739 (2023.06.15).

Bao, W. (2020). COVID-19 and online teaching in higher education: A case study of Peking University. Human Behavior and Emerging Technologies, 2(1), 113–115. DOI: 10.1002/hbe2.191.

Bosch, T. E. (2009). Using online social networking for teaching and learning: Facebook use at the University of Cape Town. South African Journal for Communication Theory and Research, 35(2), 185–200. DOI: 10.1080/02500160903250648.

Bozkurt, A., Sharma, R. C., Stockdale, S. (2020). Emergency remote teaching in a time of global crisis due to CoronaVirus pandemic. Asian Journal of Distance Education, 15(1), 1–6.

Daniel, S. J. (2020). Education and the COVID-19 pandemic. Prospects, 49(1–2), 91–96. DOI: 10.1007/s11125-020-09464-3.

Eshet-Alkalai, Y. (2004). Digital Literacy: A Conceptual Framework for Survival Skills in the Digital Era. Journal of Educational Multimedia and Hypermedia, 13(1), 93–106.

Ferrari, A. (2013). DIGCOMP: A Framework for Developing and Understanding Digital Competence in Europe. Luxemburg: Publications Office of the European Union.

Gallardo-Echenique, E. E., Marqués-Molías, L., Bullen, M., Strijbos, J. W. (2015). Let’s talk about digital learners in the digital era. International Review of Research in Open and Distributed Learning, 16(3), 156–187. DOI: 10.19173/irrodl.v16i3.2196.

Gilster, P. (1997). Digital Literacy. New Jersey: Wiley Computer Publishing.

Hargittai, E. (2002). Second-level digital divide: Differences in people’s online skills. First Monday, 7(4), 1–10. DOI: 10.5210/fm.v7i4.942.

Hew, K. F., Cheung, W. S. (2014). Students’ and instructors’ use of massive open online courses (MOOCs): Motivations and challenges. Educational Research Review, 12, 45–58. DOI: 10.1016/j.edurev.2014.05.001.

Hodges, C., Moore, S., Lockee, B., Trust, T., Bond, A. (2020). The Difference Be-tween Emergency Remote Teaching and Online Learning. Educause Review, 27.03.2020. Retrieved from: https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning (2023.06.15).

Hsin, C. T., Cigas, J. (2013). Short videos improve student learning in online education. Journal of Computing Sciences in Colleges, 28(5), 253–259.

Jaggars, S. S., Xu, D. (2016). How do online course design features influence student performance? Computers & Education, 95, 270–284. DOI: 10.1016/j.compedu.2016.01.014.

Joksimović, S., Poquet, O., Kovanović, V., Dowell, N., Mills, C., Gašević, D., Brooks, C. (2018). How do we model learning at scale? A systematic review of research on MOOCs. Review of Educational Research, 88(1), 43–86. DOI: 10.3102/0034654317740335.

Kimmons, R., Veletsianos, G. (2020). Public internet data mining methods in instructional design, educational technology, and online learning research. TechTrends, 64(5), 835–847. DOI: 10.1007/s11528-020-00507-1.

Kirschner, P. A., Karpinski, A. C. (2010). Facebook® and academic performance. Computers in Human Behavior, 26(6), 1237–1245. DOI: 10.1016/j.chb.2010.03.024.

Kukolja Taradi, S., Taradi, M., Radić, K., Pokrajac, N. (2005). Blending problem-based learning with Web technology positively impacts student learning outcomes in acid-base physiology. Advances in Physiology Education, 29(1), 35–39. DOI: 10.1152/ advan.00026.2004.

Lemola, S., Perkinson-Gloor, N., Brand, S., Dewald-Kaufmann, J. F., Grob, A. (2015). Adolescents’ Electronic Media Use at Night, Sleep Disturbance, and Depressive Symptoms in the Smartphone Age. Journal of Youth and Adolescence, 44, 405–418.

Pappano, L. (2012). The Year of the MOOC. The New York Times, 2(12), 2.11.2012.

Ribble, M., Bailey, G. (2007). Digital Citizenship in Schools. Washington: ISTE.

Trust, T., Whalen, J. (2020). Should Teachers be Trained in Emergency Remote Teaching? Lessons Learned from the COVID-19 Pandemic. Journal of Technology and Teacher Education, 28(2), 189–199.

Trust, T., Krutka, D. G., Carpenter, J. P. (2016). “Together we are better”: Professional learning networks for teachers. Computers & Education, 102, 15–34. DOI: 10.1016/j.compedu.2016.06.007.

Wang, M., Shen, R., Novak, D., Pan, X. (2009). The impact of mobile learning on students’ learning behaviours and performance: Report from a large blended classroom. British Journal of Educational Technology, 40(4), 673–695. DOI: 10.1111/j. 1467-8535.2008.00846.x.

Warschauer, M. (2004). Technology and social inclusion: Rethinking the digital divide. Cambridge: MIT Press.

Weller, M. (2020). 25 Years of Ed Tech. Athabasca: Athabasca University Press.

Zawacki-Richter, O., Marín, V. I., Gouverneur, F., Bond, M. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 16–39. DOI: 10.1186/s41239-019-0171-0.

Zhang, W., Wang, Y., Yang, L., Wang, C. (2020). Suspending Classes Without Stopping Learning: China’s Education Emergency Management Policy in the COVID-19 Outbreak. Journal of Risk and Financial Management, 13(3), 55. DOI: 10.3390/ jrfm13030055.

Downloads

Published

2023-09-30

How to Cite

Kocot, M., & Kwasek, A. (2023). Impact of the COVID-19 pandemic on IT competencies of students. Social Inequalities and Economic Growth, (75), 90–101. https://doi.org/10.15584/nsawg.2023.3.5

Issue

Section

Articles