inis 18: e1

Research Article

Student’s Perception towards Mobile learning using Interned Enabled Mobile devices during COVID-19

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  • @ARTICLE{10.4108/eai.16-9-2021.170958,
        author={Pooja Gupta and Vimal Kumar and Vikash Yadav},
        title={Student’s Perception towards Mobile learning using  Interned Enabled Mobile devices during COVID-19},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={INIS},
        year={2021},
        month={9},
        keywords={Mobile learning, COVID-19, 5G technology, Adoption, Machine learning algorithm},
        doi={10.4108/eai.16-9-2021.170958}
    }
    
  • Pooja Gupta
    Vimal Kumar
    Vikash Yadav
    Year: 2021
    Student’s Perception towards Mobile learning using Interned Enabled Mobile devices during COVID-19
    INIS
    EAI
    DOI: 10.4108/eai.16-9-2021.170958
Pooja Gupta1, Vimal Kumar1, Vikash Yadav2,*
  • 1: Meerut Institute of Engineering and Technology, Meerut, India
  • 2: Department of Technical Education, Uttar Pradesh, India
*Contact email: vikas.yadav.cs@gmail.com

Abstract

INTRODUCTION: The novel corona disease disrupted education all around the world. This shifted people to mobile learning in real time wireless classroom from the physical face-to-face classroom.

OBJECTIVE: Mobile learning has been present for years but the use of mobile learning is more in the current scenario due to COVID-19. However, people’s acceptance of mobile learning education at institutions is still low. Thus, this research seeks to understand the student’s perspective by analysing constructs hypothesized in the proposed hybrid model.

METHOD: Data is collected using a survey from an Indian institute of the Meerut region with a total of 1022 students.

RESULT: Data analysis and research findings showed that Random Forest and K-Nearest Neighbour Algorithms outperforms than other classifiers in predicting the dependent variables with better accuracy rate, precision, and recall value in this study.

CONCLUSION: The research findings will help the designers and software development to design learning applications considering the perspective of students with respect to 5G technology.