International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12
line decor
  
line decor

 Volume 10, Issue 3 (March 2023), Pages: 37-45

----------------------------------------------

 Original Research Paper

The two-step cluster analysis of pre-COVID-19 experience and cybersecurity concerns about online education for academic staff in Saudi universities

 Author(s): 

 Hasan Beyari 1, *, Othman Alrusaini 2

 Affiliation(s):

 1Department of Administrative and Financial Sciences, Applied College, Umm Al-Qura University, Makkah 24382, Saudi Arabia
 2Department of Engineering and Applied Sciences, Applied College, Umm Al-Qura University, Makkah 24382, Saudi Arabia

  Full Text - PDF          XML

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0003-0943-0317

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2023.03.005

 Abstract:

The purpose of this research is to learn about the attitudes of the academic staff of the medical, business, humanities, and science and engineering disciplines concerning online education during the COVID-19 pandemic at Umm Al-Qura University (UQU), Saudi Arabia. While research in online education focuses on learning experiences such as facilities, learning materials, and learning interests, several elements of online education in this research were investigated, including advantages, features, and cybersecurity. The research data were gathered through a survey containing three demographic items, four items on perceptions of online education, and seven questions on perceptions of cybersecurity. Responses obtained from 238 academic staff were used for statistical analysis. After the routine descriptive analysis analyses, the response data were subjected to unsupervised k-means centroid cluster analysis. Two clusters of academic staff differing in teaching disciplines, and pre-COVID experience in online education were identified. Cluster 1 had medical and business and humanities academic staff, predominated by those without pre-COVID experience in online education, and perceived online education and cybersecurity at neutral to a slightly low level. Cluster 2 consisted of science and engineering discipline academic staff predominated by those with pre-COVID online education experience and perceived online education and cybersecurity in the range of neutral to slightly high levels. The result of this study shows that academic staff in the medical, business, and humanities disciplines have less expertise with online education software and a low level of awareness about online education security. On the other hand, academic staff of science and engineering disciplines fields has more expertise with online educational technologies and a better level of understanding of online education security.

 © 2022 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Academic staff’s perception, Saudi universities, Online learning, Custer analysis, Cybersecurity

 Article History: Received 17 August 2022, Received in revised form 9 November 2022, Accepted 30 November 2022

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Beyari H and Alrusaini O (2023). The two-step cluster analysis of pre-COVID-19 experience and cybersecurity concerns about online education for academic staff in Saudi universities. International Journal of Advanced and Applied Sciences, 10(3): 37-45

 Permanent Link to this page

 Figures

 Fig. 1 Fig. 2

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5 Table 6

----------------------------------------------    

 References (27)

  1. Adnan M and Anwar K (2020). Online learning amid the COVID-19 pandemic: Students' perspectives. Online Submission, 2(1): 45-51. https://doi.org/10.33902/JPSP.2020261309   [Google Scholar]
  2. Agung ASN, Surtikanti MW, and Quinones CA (2020). Students’ perception of online learning during COVID-19 pandemic: A case study on the English students of STKIP Pamane Talino. SOSHUM: Jurnal Sosial Dan Humaniora, 10(2): 225-235. https://doi.org/10.31940/soshum.v10i2.1316   [Google Scholar]
  3. Alghamdi AA (2021). Impact of the COVID-19 pandemic on the social and educational aspects of Saudi university students’ lives. PLOS ONE, 16(4): e0250026. https://doi.org/10.1371/journal.pone.0250026   [Google Scholar] PMid:33852627 PMCid:PMC8046245
  4. Allo MDG (2020). Is the online learning good in the midst of COVID-19 Pandemic? The case of EFL learners. Jurnal Sinestesia, 10(1): 1-10.   [Google Scholar]
  5. Azzi DV, Melo J, Neto ADAC, Castelo PM, Andrade EF, and Pereira LJ (2022). Quality of life, physical activity and burnout syndrome during online learning period in Brazilian university students during the COVID-19 pandemic: A cluster analysis. Psychology, Health and Medicine, 27(2): 466-480. https://doi.org/10.1080/13548506.2021.1944656   [Google Scholar] PMid:34192994
  6. Bączek M, Zagańczyk-Bączek M, Szpringer M, Jaroszyński A, and Wożakowska-Kapłon B (2021). Students’ perception of online learning during the COVID-19 pandemic: A survey study of Polish medical students. Medicine, 100(7): e24821. https://doi.org/10.1097/MD.0000000000024821   [Google Scholar] PMid:33607848 PMCid:PMC7899848
  7. Banfield JD and Raftery AE (1993). Model-based Gaussian and non-Gaussian clustering. Biometrics, 49(3): 803-821. https://doi.org/10.2307/2532201   [Google Scholar]
  8. Bhagat S and Kim DJ (2020). Higher education amidst COVID-19: Challenges and silver lining. Information Systems Management, 37(4): 366-371. https://doi.org/10.1080/10580530.2020.1824040   [Google Scholar]
  9. Biwer F, Wiradhany W, Oude Egbrink M, Hospers H, Wasenitz S, Jansen W, and De Bruin A (2021). Changes and adaptations: How university students self-regulate their online learning during the COVID-19 pandemic. Frontiers in Psychology, 12: 642593. https://doi.org/10.3389/fpsyg.2021.642593   [Google Scholar] PMid:33967903 PMCid:PMC8103204
  10. Budur T (2020). The role of online teaching tools on the perception of the students during the lockdown of COVID-19. International Journal of Social Sciences and Educational Studies, 7(3): 178-190. https://doi.org/10.23918/ijsses.v7i3p178   [Google Scholar]
  11. Cheah JH, Sarstedt M, Ringle CM, Ramayah T, and Ting H (2018). Convergent validity assessment of formatively measured constructs in PLS-SEM: On using single-item versus multi-item measures in redundancy analyses. International Journal of Contemporary Hospitality Management, 30(11): 3192-3210. https://doi.org/10.1108/IJCHM-10-2017-0649   [Google Scholar]
  12. Chiu T, Fang D, Chen J, Wang Y, and Jeris C (2001). A robust and scalable clustering algorithm for mixed type attributes in large database environment. In the 7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Assn for Computing Machinery, San Francisco, USA: 263-268. https://doi.org/10.1145/502512.502549   [Google Scholar] PMid:11791889
  13. Creswell JW (2012). Educational research: Planning. Conducting, and Evaluating, 260: 375-382.   [Google Scholar]
  14. Händel M, Stephan M, Gläser-Zikuda M, Kopp B, Bedenlier S, and Ziegler A (2020). Digital readiness and its effects on higher education students’ socio-emotional perceptions in the context of the COVID-19 pandemic. Journal of Research on Technology in Education, 54(2): 267-280. https://doi.org/10.1080/15391523.2020.1846147   [Google Scholar]
  15. Hernández-García F, Gómez OG, González-Velázquez VE, Pedraza-Rodríguez EM, Zamora-Fung R, and Herrera LAL (2021). Perceived stress by students of the medical sciences in Cuba toward the COVID-19 pandemic: Results of an online survey. Revista Colombiana de Psiquiatría, 50(3): 176-183. https://doi.org/10.1016/j.rcp.2021.02.011   [Google Scholar]
  16. Jayakumar P, Brohi SN, and Zaman N (2020). Top 7 lessons learned from COVID-19 pandemic. https://doi.org/10.36227/techrxiv.12264722.v1   [Google Scholar]
  17. Laili RN and Nashir M (2021). Higher education students’ perception on online learning during COVID-19 pandemic. Edukatif: Jurnal Ilmu Pendidikan, 3(3): 689-697. https://doi.org/10.31004/edukatif.v3i3.422   [Google Scholar]
  18. Mishra L, Gupta T, and Shree A (2020). Online teaching-learning in higher education during lockdown period of COVID-19 pandemic. International Journal of Educational Research Open, 1: 100012. https://doi.org/10.1016/j.ijedro.2020.100012   [Google Scholar] PMid:35059663 PMCid:PMC7832355
  19. MOE (2022). Data and statistics. Ministry of Education, Riyadh, Saudi Arabia.   
  20. Muthuprasad T, Aiswarya S, Aditya KS, and Jha GK (2021). Students’ perception and preference for online education in India during COVID-19 pandemic. Social Sciences and Humanities Open, 3(1): 100101. https://doi.org/10.1016/j.ssaho.2020.100101   [Google Scholar] PMid:34173507 PMCid:PMC7836920
  21. Nambiar D (2020). The impact of online learning during COVID-19: Students’ and teachers’ perspective. The International Journal of Indian Psychology, 8(2): 783-793.   [Google Scholar]
  22. Niemi HM and Kousa P (2020). A case study of students’ and teachers’ perceptions in a Finnish high school during the COVID pandemic. International Journal of Technology in Education and Science, 4(4): 352-369. https://doi.org/10.46328/ijtes.v4i4.167   [Google Scholar]
  23. Nugroho RA, Basari A, Suryaningtyas VW, and Cahyono SP (2020). University students’ perception of online learning in COVID-19 pandemic: A case study in a translation course. In the International Seminar on Application for Technology of Information and Communication, IEEE, Semarang, Indonesia: 225-231. https://doi.org/10.1109/iSemantic50169.2020.9234251   [Google Scholar]
  24. Ojo EO and Onwuegbuzie AJ (2020). University life in an Era of disruption of COVID-19: A meta-methods and multi-mixed methods research study of perceptions and attitudes of South African students. International Journal of Multiple Research Approaches, 12(1): 20-55. https://doi.org/10.29034/ijmra.v12n1editorial3   [Google Scholar]
  25. Shah S, Diwan S, Kohan L, Rosenblum D, Gharibo C, Soin A, and Provenzano DA (2020). The technological impact of COVID-19 on the future of education and health care delivery. Pain Physician, 23(4S): S367-S380. https://doi.org/10.36076/ppj.2020/23/S367   [Google Scholar]
  26. Sujarwo S, Sukmawati S, Akhiruddin A, Ridwan R, and Siradjuddin SSS (2020). An analysis of university students’ perspective on online learning in the midst of COVID-19 pandemic. Jurnal Pendidikan Dan Pengajaran, 53(2): 125-137. https://doi.org/10.23887/jpp.v53i2.24964   [Google Scholar]
  27. Zhang T, Ramakrishnan R, and Livny M (1996). BIRCH: An efficient data clustering method for very large databases. ACM Sigmod Record, 25(2): 103-114. https://doi.org/10.1145/235968.233324   [Google Scholar]