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

Authors

  • Pooja Gupta Meerut Institute of Engineering and Technology
  • Vimal Kumar Meerut Institute of Engineering and Technology
  • Vikash Yadav Department of Technical Education

DOI:

https://doi.org/10.4108/eai.16-9-2021.170958

Keywords:

Mobile learning, COVID-19, 5G technology, Adoption, Machine learning algorithm

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.

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Published

16-09-2021

How to Cite

Gupta, P. ., Kumar, V. ., & Yadav, V. . (2021). Student’s Perception towards Mobile learning using Interned Enabled Mobile devices during COVID-19. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 8(29), e1. https://doi.org/10.4108/eai.16-9-2021.170958