Determining the most critical factors affecting E-learning in some Saudi universities by using statistical methods

Hanaa Abu-Zinadah; Salwa AlKhayyat; Eman  Alhawiti

doi:10.35877/454RI.asci4377

Hanaa Abu-Zinadah University of Jeddah, College of Science, Department of Mathematics and Statistics, Jeddah, Saudi Arabia (SA) https://orcid.org/0000-0002-0343-9604
Salwa L. AlKhayyat University of Jeddah, College of Computer Science and Engineering, Department of Computer Science & Artificial Intelligence, Jeddah, Saudi Arabia (SA)
Eman Alhawiti University of Jeddah, College of Science, Department of Mathematics and Statistics, Jeddah, Saudi Arabia (SA)

Keywords: Electronic Learning (E-learning); Distance education; Blended learning; Logistic regression; Neural networks; Decision tree; traditional education

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Abstract

The global COVID-19 pandemic accelerated the shift to e-learning in higher education, making faculty acceptance a key factor in its success. This study aims to identify factors influencing the orientations of faculty members in some Saudi universities toward e-learning (blended learning) as a viable alternative to traditional instruction. Statistical methods, including Decision Tree, Neural Network, and Logistic Regression analyzes, were used to determine these factors. The analysis revealed that the most influential factors shaping faculty attitudes toward e-learning were the suitability of teaching from home, the adherence to lecture schedules, the availability of lecture recordings, the need for additional time and the view of blended learning as a solution during crises. These findings suggest that technological readiness, time discipline, and positive perceptions of blended learning enhance faculty acceptance of e-learning (blended learning).

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