Using Machine Learning Algorithms to Predict People's Intention to Use Mobile Learning Platforms During the COVID-19 Pandemic: Machine Learning Approach.

Iman Akour,Said Salloum,Barween Al Kurdi,Muhammad Alshurideh,Amel Al Ali

doi:10.2196/24032

Abstract

BackgroundMobile learning has become an essential instruction platform in many schools, colleges, universities, and various other educational institutions across the globe, as a result of the COVID-19 pandemic crisis. The resulting severe, pandemic-related circumstances have disrupted physical and face-to-face contact teaching practices, thereby requiring many students to actively use mobile technologies for learning. Mobile learning technologies offer viable web-based teaching and learning platforms that are accessible to teachers and learners worldwide.ObjectiveThis study investigated the use of mobile learning platforms for instruction purposes in United Arab Emirates higher education institutions.MethodsAn extended technology acceptance model and theory of planned behavior model were proposed to analyze university students’ adoption of mobile learning platforms for accessing course materials, searching the web for information related to their disciplines, sharing knowledge, and submitting assignments during the COVID-19 pandemic. We collected a total of 1880 questionnaires from different universities in the United Arab Emirates. Partial least squares-structural equation modeling and machine learning algorithms were used to assess the research model, which was based on the data gathered from a student survey.ResultsBased on our results, each hypothesized relationship within the research model was supported by our data analysis results. It should also be noted that the J48 classifier (89.37% accuracy) typically performed better than the other classifiers when it came to the prediction of the dependent variable.ConclusionsOur study revealed that teaching and learning could considerably benefit from adopting remote learning systems as educational tools during the COVID-19 pandemic. However, the value of such systems could be lessened because of the emotions that students experience, including a fear of poor grades, stress resulting from family circumstances, and sadness resulting from a loss of friends. Accordingly, these issues can only be resolved by evaluating the emotions of students during the pandemic.

Highlights

BackgroundColleges and universities often actively aim to create web-based teaching environments with the help of relevant learning platforms and resources [1,2,3]
It should be noted that the J48 classifier (89.37% accuracy) typically performed better than the other classifiers when it came to the prediction of the dependent variable
Our study revealed that teaching and learning could considerably benefit from adopting remote learning systems as educational tools during the COVID-19 pandemic

Summary

Introduction

Colleges and universities often actively aim to create web-based teaching environments with the help of relevant learning platforms and resources [1,2,3]. These higher education institutions attempt to achieve effective student results by providing various learning management platforms that enhance strategies and practices for teaching and learning. The COVID-19 pandemic has presented higher education institutions with several challenges, as students worldwide have been experiencing negative emotions and feelings with regard to their studies. Such emotions include fear, anxiety, and apprehension. Mobile learning technologies offer viable web-based teaching and learning platforms that are accessible to teachers and learners worldwide

Methods

Results

Discussion

Conclusion