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Research Article · Open access · Published 28 January 2023

An Analytical Survey of Difficulty Faced in an Online Lecture During COVID-19 Pandemic Using CRISP-DM

Manmohan Singh1, Vinod Patidar2, Shaheen Ayyub3, Anita Soni4, Monika Vyas5, Dharmendra Sharma6 & Amol Ranadive7

Journal of Computer Science, Volume 19, Issue 2, pp. 242–250 · doi.org/10.3844/jcssp.2023.242.250

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Abstract

COVID-19 has greatly disturbed life in many ways and has changed the way we live. Various surveys have been conducted in different fields, and the teaching-learning process has been affected to a great extent. During this pandemic, various online tools and technologies have been available for guiding students without attending school. Many governments, corporations, and research fields have officially ordered to use of online media for the teaching-learning process. Platforms such as Google Meet, Microsoft Team, and Web-e-X have allowed and arranged for online video conferencing mediums to achieve the goal of the teaching-learning process. However, as mentioned above, there are some serious issues with the online teaching-learning process. These include problems with continuous network bandwidth during sessions, physical and mental presence in the class, difficulties handling mathematics classes, and the potential for non-sense activities that may disturb the entire class. In order to discover knowledge, I am using a new approach to data mining technology called CRISP-DM. This study addresses the effectiveness of online teaching mode and learning and the challenges faced by students and teachers who are taking online classes during COVID-19. According to this study, 88.2% of students did not have proper internet or technology facilities, 58.30% of students were not satisfied with online learning, 85.3% of students complained about eyesight issues from taking online classes on devices, and 50.01% of students were unable to manage university affairs.

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Open access. This article is licensed under a Creative Commons Attribution 4.0 International Licence (CC BY 4.0), as printed on the article, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source. No permission is needed.

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Singh, M., Patidar, V., Ayyub, S., Soni, A., Vyas, M., Sharma, D. & Ranadive, A. (2023). An Analytical Survey of Difficulty Faced in an Online Lecture During COVID-19 Pandemic Using CRISP-DM. Journal of Computer Science, 19(2), 242–250. https://doi.org/10.3844/jcssp.2023.242.250

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Volume 19, Issue 2
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An Analytical Survey of Difficulty Faced in an Online Lecture During COVID-19 Pandemic Using CRISP-DMJournal of Computer Science · Volume 19, Issue 2 · pp. 242–250 · CC BY 4.0Download