Conference paper 2024

Comparative evaluation of YouTube, Facebook, TikTok, and Instagram as online learning resources

2024 International Conference on Intelligent Systems and Computer Vision, ISCV 2024
Conference
Abstract

This paper presents a comparative analysis of the use of YouTube, Facebook, TikTok, and Instagram as learning tools. The study evaluates the applications based on parameters such as video length, user base, content type, demographics, and their respective use in learning scenarios. The research methodology involved administering a questionnaire to trainees at the regional center for education and training professions, Fez-Meknes, Morocco, soliciting their insights on the use of these platforms for learning. The results revealed that YouTube emerged as the most utilized platform for learning, followed by Facebook, Instagram, and TikTok. It was noted that the platforms cater to different learning needs and styles, emphasizing their potential as supplementary tools in digital learning. However, there were differences in the perceived quality and reliability of educational content across these platforms. A substantial portion of the learners were also found to not engage in interactive learning experiences. The study concludes with insights on how educators can leverage these platforms to enhance digital learning experiences. The findings underscore the potential of social media platforms in education while also highlighting areas for improvement. © 2024 IEEE.

Keywords

Author Keywords

Digital learning Online education social media platforms YouTube Facebook Instagram TikTok

Index Keywords

Federated learning Contrastive Learning Learning experiences Adversarial machine learning On-line education Digital-learning Tweets Comparative evaluations Facebook Instagram Platform for learning Social media platforms Tiktok YouTube
Author Affiliations
LISAC Laboratory, Faculté des Sciences Dhar El Mahraz, Université Sidi Mohamed Ben Abdellah, Fez, Fes-Meknes, Morocco
School of Applied Sciences, Université Sidi Mohamed Ben Abdellah, Fez, Fes-Meknes, Morocco
LISAC Laboratory, Faculté des Sciences Dhar El Mahraz, Université Sidi Mohamed Ben Abdellah, Fez, Fes-Meknes, Morocco, LaMSN - La Maison des Sciences Numériques, Paris, France
Funding & Acknowledgements
No funding information
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