Identifying and ranking the components of evaluating the success of e-learning systems of universities with the approach of fuzzy network analysis (case study of Sistan and Baluchistan University)

Master's thesis in the field of information technology management

Electronic business trend

Abstract:

In the present era, one of the most important human inventions that have brought tremendous changes in the life of mankind is the emergence of the computer and the Internet, which has created a virtual world and an incentive for universities to invest in electronic education. But what makes the importance of the discussion clearer is trying to achieve success in using the electronic learning system and measuring the success rate of these systems. An unsuccessful attempt to implement e-learning will result in a loss of capital. This research has been done with the aim of identifying and ranking the success measurement components of electronic learning systems of universities with the approach of fuzzy network analysis. For this purpose, first, based on previous research, the components and indicators for measuring the success of e-learning systems were proposed, then, in order to measure the validity and appropriateness of the components and indicators proposed, questionnaire number one, with the aim of identifying the components for measuring the success of e-learning systems in person and electronically, was given to the decision group, which were professors and virtual students of Sistan and Baluchistan University. The data collected from questionnaire number one was processed using spss software, and one-sample t-test was used in the data analysis. The number of 7 components and 28 indicators was finalized. Then, based on the components and indicators finalized in the previous stage, questionnaire number two was designed with the aim of prioritizing the components of evaluating the success of e-learning systems in universities and was given to 7 experts in the field of e-learning. The data collected from questionnaire number two was processed using the fuzzy network analysis technique. The main components in order of priority are: 1- Information quality [1] 2- Service quality [2] 3- System and infrastructure quality [3] - 4 Support factors [4] - 5 Professor characteristics [5] - 6 Student characteristics [6] 7 - Environmental factors [7].

Key words: fuzzy network analysis - learning system E-learning assessment components - Universities - Identification and ranking

Chapter 1

Generalities of research

-1- Introduction

In this chapter, the generalities and concepts of research are discussed, the content of this chapter includes: statement of the problem and importance of research, research objectives, research questions and hypotheses, research methods, data collection tools, research field and research concepts and vocabulary.

1-2- Statement of the problem and the importance of research:

Human inventions have often created tremendous changes in the life of humanity, but not all of these inventions have the same value and impact. In today's era, one of the most important ones that has really created a significant change in human life has been the emergence of the computer, which began in the 1950s. But the changes caused by computers reached their peak when the communication networks between them grew and the Internet created a virtual world by eliminating physical distances and existing communication barriers. Following the application of new technologies, education information systems have undergone many changes and transformations (Ozpolat & Kare, 2009). Therefore, the previous concept of electronic learning is undergoing fundamental changes and is not limited to face-to-face classes (Rosenberg 2013; Wang, 2007). Electronic learning refers to the use of electronic devices for learning, including the delivery of content through electronic media such as the Internet, audio, video, satellite broadcasting, interactive televisions, and CDs (Kaplan & Anderson, 2000). The rapid expansion of the Internet with a tendency towards independence from the place of education to the individual has become a motivation for universities. is to invest in the electronic sector (Accles, 1997). In Iran, it is not possible to access higher education in the form of face-to-face classes for many applicants, but the weakness in responding to traditional methods can be compensated for by using electronic learning systems (Yagoubi et al. 2017).  However, the development and management of continuous improvement of e-learning systems of educational and industrial institutions have been quite challenging, and in that evaluation has become an essential requirement (Accles, 1991). The rapid increase in the number of institutions providing e-learning on the one hand and the quantitative growth of its existing fields on the other hand raises the question of how successful these centers have been in implementing and implementing e-learning courses and to what extent.The rapid increase in the number of institutions providing e-learning on the one hand and the quantitative growth of its existing fields on the other hand raises the question of how successful these centers have been in implementing and running e-learning courses and how far they have been able to fulfill the most important goal of their educational system, which is to improve the quality of learning and academic progress of students (Samadi 2019). (Delone, 2003) and an unsuccessful attempt to implement e-learning will cause a loss of capital (Govindasamy, 2002). Therefore, since 1992, several researches have investigated the success of information systems and measured it experimentally (Wang et al, 2007). Many researchers from different fields such as computer, information systems, psychology, technology, education have tried to evaluate electronic learning systems. Some of them focus on the human factor (student and teacher satisfaction), some on educational technology, and some on educational materials (Liaw, Huang, & Chen 2007). In order to identify and examine the success factors of electronic learning systems, we can name the models that have been proposed in the field of information systems. Delon and McLean information systems success model is a model that can help to understand this matter (Petter & McLean, 2002). This model was first developed and reviewed by Delon in 1992. The modified model of Delon and McLean includes 6 dimensions, which are: intention to use the system - user satisfaction - benefits from information systems (Delon & McLean, 2003; Wang, 2007). Since e-learning systems are a special type of information systems (Wang et All, 2007; Lee, 2008). The modified model of Delon and McLean can also be used to measure the success of e-learning systems. In this regard, Wang and his colleagues used the mentioned components (without considering the relationships between them) for the first time in electronic learning systems in organizations (Wang et All, 2007). Then Lin used the mentioned model by removing the benefit component from the system and considering all relationships between components for e-learning systems (Lin, 2007). It should be noted that in each case of using the Delon and McLean model, the success rate of e-learning systems has been examined only from the learner's point of view, and considering that the teacher also plays a very important role in e-learning for the correct application of the model, in addition to considering all the components and relationships between them, the teacher's point of view should also be examined. In another research conducted by Ozkan and Kosler using the modified model of Delon and McLean, a hexagonal model for e-learning [1] (HELAN) was presented and tested in one of the Turkish universities. The dimensions of this model are content (information) - teacher's attitude - service quality - system quality - supporting factors of the learner's attitude and perspective (Ozkan & Koseler, 2009). In this research, the relationships between the components are not considered. It should be noted that one of the most important weaknesses of the previous models is that the relative importance of the components for measuring the success of e-learning systems cannot be measured quantitatively. In other words, it is somewhat difficult to identify which component affects the evaluation more. The network analysis process [2] solves this problem and calculates and ranks the weight of each component quantitatively. Considering the criticism that has been made on the classical network analysis, the combination of the network analysis process and fuzzy logic is proposed as a way to solve the shortcomings.  

Therefore, in this thesis, based on previous research and study and re-examination and getting the opinion of experts, the components of measuring the success of e-learning systems in universities are identified, then the fuzzy network analysis process is used to determine the priority and weight of each component and index. It is hoped that the findings of this research will lead to a better management of e-learning systems and the development of effective e-learning. 1-3-Research objectives: The lack of a comprehensive and local framework to measure the success of the e-learning system in the country's higher education system, as well as the factors that cause the success or failure of e-learning environments, has necessitated such research. In this research, an attempt has been made to provide a comprehensive and native framework for measuring the success rate of e-learning systems with the approach of fuzzy network analysis in universities by using previous models and researches, especially using Ozkan and Kosler's hexagonal model.