Non-parametric Statistical Methods to Predict the Benefits of Switching to E-learning, by Application on Saudi Universities
DOI:
https://doi.org/10.48161/qaj.v4n3a733Abstract
The current research aims to use non-parametric tests to predict the benefits of switching to e-learning. Non-parametric tests (Chi-square goodness of fit, Chi-square independence and Kruskal Wallis) were used. For the empirical analysis, a questionnaire was used as a tool to collect data and distribute it in 8 Saudi public universities. The research questions included: What are the readiness students of switching to e-learning? What are the most significance indicators of the positive and negative impact of switching to e-learning? The findings indicated that (67.1%) of the students have a high the readiness. It had been seen that the most significance of indicators related to the benefits of switching to e-learning are: (e-learning solves the problem of increasing the number of students, e-learning focuses more on knowledge, it reduces time, it is flexible, e-learning has succeeded in developing programs, e-learning offers topics are well organized, it increases the sharing of experiences between students, assessment methods are fair; and it gives me enough time to think). The most significance indicators related to the challenges, are (e-learning prompted students not to underestimate the education, the professor can identify the negative student, the university provides a virtual library, I have get sufficient training , indirect communication does not affect the understanding , virtual laboratories have been activated, there is no difficulty in submitting exams , the internet is strong in my area, virtual classes are more effective, e-learning helps in exchanging assignments, and the university provides technical support). The findings showed that the course content was the decisive factor of switching to e-learning. The findings can benefit for educators and policy makers for the effective implementation of e-learning in Saudi universities, through attention is paid to all indicators that have a negative impact. And adopting the positive indicators to encourage students to continue e-learning in the future.
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