ArticleMultimedia tools and applications2021
Enabling remote learning system for virtual personalized preferences during COVID-19 pandemic.
Article in Multimedia tools and applications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Detection of cotton crops diseases using customized deep learning model.Scientific reports · 2025Article
- Factors influencing preclinical medical students' satisfaction with hospital teachers' instruction in a blended learning environment integrating the rain classroom platform in China.Frontiers in psychology · 2025Article
- Article
- RALF: an adaptive reinforcement learning framework for teaching dyslexic students.Multimedia tools and applications · 2022Article
- Using refined kano model and decision trees to discover learners' needs for teaching videos.Multimedia tools and applications · 2022Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The education system worldwide has been affected by the Corona Virus Diseases 2019 (COVID-19) pandemic, resulting in the interruption of all educational institutions. Moreover, as a precautionary measure, the lockdown has been imposed that has severely affected the learning processes, especially assessment activities, including exams and viva. In such challenging situations, E-learning platforms could play a vital role in conducting seamless academic activities. In spite of all the advantages of remote learning systems, many hurdles and obstacles, like a selection of suitable learning resources/material encounter by individual users based on their interests or requirements. Especially those who are not well familiar with the internet technology in developing countries and are in need of a platform that could help them in resolving the issues related to the online virtual environment. Therefore, in this work, we have proposed a mechanism that intelligently and correctly predicts the appropriate preferences for the selection of resources relevant to a specific user by considering the capabilities of diverse perspectives users to provide quality online education and to make work from home policy more effective and progressive during the pandemic. The proposed system helps teachers in providing quality online education, familiarizing them with advanced technology in the online environment. It also semantically predicts the preferences for virtual assistance of those users who are in need of learning the new tools and technologies in short time as per their institutional requirements in order to meet the quality standards of online education. The experimental and statistical results have demonstrated that the proposed virtual personalized preferences system has improved overall academic activities as compared to the current method. The proposed system enhanced user's learning abilities and facilitated them in selecting short courses while using different online education tools adopted/suggested by the institutions to conduct online classes/seminars/webinars etc., as compared to the conventional classes/activities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.