THE E-LEARNING SYSTEM SUCCESS: ASSESSMENT OF THE SERVICE QUALITY USING BINOMINAL LOGISTIC REGRESSION
Keywords:e-learning, higher education, binomial logistic regression
The success and the efficiency of e-Learning should be measured by a reliable method in order to use it effectively. Although, there are several studies about the success of e-Learning systems, only a few of them deal with the measurement of this success within the institutions. We made two questionnaires to evaluate the e-Learning application. The aim was to develop such questionnaires which are suitable to evaluate e-Learning’s quality. The basis of the e-Learning’s quality questions was Wang’s article (2007), in which he measured the success of e-Learning systems, therefore the questions of the students’ and the lecturers’ questionnaires were the same. The aim of the questionnaires were to compare the opinions of the students and the teachers and also to evaluate the Faculty of Economics and Business (FEB) of the University of Debrecen and the Corvinus University of Budapest (CUB) regarding the application of e-Learning. The role of the questionnaire for quality development is to give guidance for the FEB in implementing and using e-Learning. E-Learning in the CUB is applied under certain organized institutional circumstances. The e-Learning application of CUB works with an organization defined extended several faculties of the University, which can be a good example for FEB. We have used the Mann-Whitney test to evaluate the questionnaires of the students who use the e-Learning system. This method is used to compare the means of two groups in case of ordinal scales or not normally distributed variables. We have also used factor analysis and binominal logistic regression. We have examined whether the background variables manipulating the variables are possible to be developed on the basis of the answers. We used factor analysis to demonstrate this since it contracts the coherent factors into one common factor. Finally we used logistic regression to determine the importance of a given factor for the users of both faculty.
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