Journal of Education and Health Promotion

Preparedness of medical students towards e‑learning conducted during COVID‑19 lockdown: A cross‑sectional descriptive study

Document Type : Original Article

Authors

. Montosh Chakraborty
. Y. Anil Kumar Reddy 1
. Joy A. Ghoshal 1
. D. Amudharaj 2
. Mukesh Tripathi 3

1 Department of Anatomy, All India Institute of Medical Sciences, Guntur, Andhra Pradesh, India,

2 Department of Physiology, All India Institute of Medical Sciences, Guntur, Andhra Pradesh, India

3 Department of Anesthesiology, All India Institute of Medical Sciences, Guntur, Andhra Pradesh, India

Abstract
BACKGROUND: COVID-19 lockdown has mandated the medical colleges to start academics using
electronic mode. Synchronous e-learning was started by our institute to replicate traditional classes in
line with the routine academic schedule. the objective of this study attempted to assess the e-learning
readiness of the students of our institute.
MATERIALS AND METHODS: A cross-sectional descriptive study was planned using the model
proposed by Oketch et al. with local modifications. The questionnaire was designed in Google
Forms and mailed to respond using Likert scale. The nonparametric data collected from the total 84
respondents were analyzed for validity and reliability of the questionnaire, mean values to know the
readiness (mean = 3.4), and one‑step multiple regression to know the predictors.
RESULTS: The mean eLR (e-learning readiness) as evaluated from attitudinal readiness (MeanAR = 3.6),
culture readiness (MeanCR = 2.3), material and technological readiness (MeanMTR = 3.7), and mental
health readiness (MeanMHR = 2.4) is 3.03 (60.6% with n = 84). Multiple regression analysis revealed
that all the variables except MHR can significantly predict e‑learning readiness linearly (P < 0.05).
CONCLUSION: The institute is ready for e‑learning in terms of AR and MTR (mean values >3.4).
CR and MHR still need a lot of improvisation to make it acceptable for e‑learning. The model could
explain 54.9% readiness level with CR as the most important predictor. More than 73% (n = 84) of the
respondents have acknowledged the present form of online classes to be the best available option
in COVID-19 lockdown and most of them are adapted to e-classes in the institute.

Keywords

COVID‑19 lockdown
e‑learning readiness
Likert scale
medical students
questionnaire 
1. Cucinotta D, Vanelli M. WHO declares COVID‑19 a pandemic.
Acta Biomed 2020;91:157‑60.
2. Saha J, Barman BB, Chouhan P. Lockdown for COVID‑19 and its
impact on pupil mobility in India: An analysis of the COVID‑19
Community Mobility Reports, 2020. Child Youth Serv Rev
2020;116:105160.
3. Ferrel MN, Ryan JJ. The impact of COVID‑19 on medical
education. Cureus 2020;12:e7492.
4. Negash S, Wilcox MV. E‑learning classifications: Differences and
similarities. In: Handbook of Distance Learning for Real‑Time
and Asynchronous Information Technology Education. London:
Information Science Reference (an Imprint of IGI Global); 2008.
p. 1‑23.
5. Badyal DK, Sharma M. Internal assessment in new MBBS
curriculum: Methods and logistics. Int J Appl Basic Med Res
2020;10:68‑75.
6. Rohayani AH, Kurniabudi H, Sharipuddin. A literature review:
Readiness factors to measuring e‑learning readiness in higher
education. Procedia Comput Sci 2015;59:230‑4.
7. Oketch HA, Njihia JM, Wausi AN. E‑learning readiness
assessment model in Kenyas’ higher education institutions: A case
study of university of Nairobi. Int J SciKnowl 2014;5:29‑41.
8. Aydın CH, Tasci D. Measuring readiness for e‑Learning:
Reflections from an emerging country. Educ Technol Soc
2005;8:244‑57.
9. Brtnikova M, Crane LA, Allison MA, Hurley LP, Beaty BL,
Kempe A. A method for achieving high response rates in national
surveys of US primary care physicians. PLoS One 2018;13:e020275.
10. MugandaRA. E‑learning Implementation: A Survey of University
of Nairobi Academic Staff Attitudes and Readiness Towards
E‑Learning; 2006. Available from: http://erepository.uonbi.ac.ke:
8080/xmlui/handle/123456789/21880. [Last accessed on 2020
Aug 18]
11. Mohammed YA. E‑learning readiness Assessment of Medical
Students in University of Fallujah. 1st Annual International
Conference on Information and Sciences (AiCIS). IEEE; 2018.
p. 201‑7.
12. Kemp N, GrieveR. Face‑to‑face or face‑to‑screen? Undergraduates’
opinions and test performance in classroom vs. online learning.
Front Psychol 2014;5:1278.
13. Muflih S, Abuhammad S, Karasneh R, Al‑Azzam S, Alzoubi KH,
MuflihM. Online education for undergraduate health professional
education during the COVID‑19 pandemic: Attitudes, barriers,
and ethical issues. Version 1. Res Sq. Preprint. 2020 Jul 16. [Doi:
10.21203/rs.3.rs‑42336/v1].
14. Frehywot S, Vovides Y, Talib Z, Mikhail N, Ross H, Wohltjen H,
et al. E‑learning in medical education in resource constrained
low‑ and middle‑income countries. Hum Resour Health 2013;11:4. 
Journal of Education and Health Promotion
Volume 11, Issue 7
August 2021
Pages 1-6

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