KnE Social Sciences | The Economies of Balkan and Eastern Europe Countries in the Changed World (EBEEC) | pages: 133-141

DOI: 10.18502/kss.v1i2.652

The Effectiveness Of The E-Learning Application: Impact Assessment Of The Quality

Peter Lengyel

István Füzesi

János Pancsira

Gergely Ráthonyi


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 are about the measurement of this success within the institutions. There is a study of DeLone and McLean (2003) which examines the success of the introduction of e-Learning system with the help of ELSS model (e-Learning System Success).

We made two questionnaires to evaluate the application of e-Learning at University of Debrecen, Faculty of Economics and Business. One of them was for the students and the other one asked the lecturers. The aim was to develop such questionnaires which are suitable for both the evaluation of the e-Learning’s quality and its economic benefits.

The basis of the e-Learning’s quality questions was Wang’s article (2007), in which he measured the success of the e-Learning systems, therefore the questions of the students’ and the lecturers’ questionnaires were the same.

The aim of this survey was to compare the opinions of the students and the teachers regarding the application of e-Learning. The role of the questionnaire for quality development is to give guidance for the University of Debrecen in the e-Learning application.

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. Factor analysis is used to compress data and explore data structure. In most cases, factor analysis is used foremost in order to filter out multicollinearity.


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ISSN: 2518-668X