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Identification and Ranking the measuring component of e-learning systems success in universities with fuzzy network analysis approach (Case Study: Sistan and Baluchestan University)

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Management, e-business branch

Identification and Ranking the measuring component of e-learning systems success in universities with fuzzy network analysis approach

(Case Study: Sistan and Baluchestan University)

ABSTRACT

Nowadays, one of the invention that created dramatic changes in human life is computers and the Internet that create the virtual world. And is an incentive for universities to invest in e-learning. But what makes clear the importance of issue, is trying to achievement the success in use of e-learning systems and assessment the success of these systems. Unsuccessful efforts to implement e-learning system will result in loss of investment. This study, with purpose of identifying and ranking the measuring factors of e-learning systems success in universities, were done with fuzzy network analysis approach. So at first, based on previous research, components of e-learning systems success have been proposed. The No.1 questionnaires were given to decision group (Teachers and Virtual students of Sistan and Baluchestan University) to identify the components of e-learning system success. Questionnaires were used to the number one person in the group. Collected Data from No.1 questionnaires were analyzed using SPSS software. The single-sample T-test was used for data analysis. 7 components and 28 indexes were finalized. Then No.2 Questionnaire, with the purpose of prioritizing the measuring components of e-learning systems success in universities and based on finalized Components and index in previous step, were designed and given to 20 experts in e-learning field. Collected data from No.2 Questionnaire were analyzed using fuzzy network analysis techniques. The main components are: 1) data quality, 2) service quality, 3) system and infrastructure quality, 4) Supporting factors, 5) teacher characteristics, 6) student characteristics and 7) environmental factors respectively.

Key words: fuzzy Network Analysis – E-Learning System – Universities – Identification – Ranking- components and indexes of e-learning system success

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Table of contents

Title………………………………………………………………………………………………………………………………..Page

CHAPTER 1. 1

1- 1-Introduction. 2

2-1 – Problem issue and research importance. 2

3-1- purpose of the research. 4

4-1- Research hypotheses. 4

5-1- Research Methods: 5

6-1- Research scope: 6

7-1– Research terminology. 6

CHAPTER 2. 8

1-2-Introduction. 9

2-2 – Distance education. 9

3-2 – Evolution of distance education. 9

4-2 – E-learning concept 11

5-2 Definitions of e-learning. 11

6-2 – The benefits of e-learning. 12

7-2 – E-learning challenges in Iran. 16

8-2 – E-learning models. 18

1-8-2- Synchronous – Live (Online) classes: 18

2-8-2- Asynchronous – Self Paced (Off Line) classes. 18

3-8-2- Computer Base Training (CBT) 18

4-8-2- Internet Base Training (IBT) 19

5-8-2- Web Base Training (WBT) 19

9-2 – E-learning systems. 19

1-9-2- Learning Management System.. 19

2-9-2- Learning Content Management System (LCMS) 20

10-2 – A review of previous researches: 20

1-10-2- E-learning critical success factors of e-learning system: 20

2-10-2- Models of Information System’s Success. 23

3-10-2- E-Learning Success Models. 25

11-2- Summarization of e-learning system success components. 30

CHAPTER 3. 34

1-3- Introduction. 35

2-3 – Analytical model of research (study): 35

3-3 – Research method: 41

4-3 – Data collection tools: 42

5-3 – statistical population and sampling method. 43

6-3- Validity of questionnaire: 43

7-3 – The reliability of questionnaire: 43

8-3 – Analysis methods: 44

9-3-Multi-criteria decision-making methods. 44

1-9-3- AHP method. 45

2-9-3- ANP method: 45

3-9-3- ANP process steps. 46

First step: paired comparisons and estimates of relative importance: 46

4-9-3 Fuzzy logic: 49

5-9-3 Fuzzy sets: 49

6-9-3 Triangular fuzzy numbers: 49

7-9-3- Fuzzy network analysis process: 50

CHAPTER 4. 52

1-4Introduction. 53

2-4-Descriptive statistics. 53

1-2-4- Gender: 53

2-2-4- Level of Education: 54

3-2-4 – The level of experience in the field of e-learning. 54

4.2.4 – Frequency distribution of respondents in terms of being teacher or student 55

5-2-4 – The age Frequency distribution of respondents: 56

3-4 – Analytical Statistics: 56

1-3-4 – Analysis the data of identification the e-learning systems success factors questionnaire  56

1-1-3-4- Research hypothesis Analysis: 61

2-3-4 – Analysis of questionnaire data and prioritize the affecting factors on success of e-learning systems  66

CHAPTER 5. 93

1-5-Introduaction: 94

2-5- Results and discussion. 94

3-5 – Research Limitations: 98

4-5 – original suggestions: 99

References. 101

Tables List  

Title………………………………………………………………………………………………………………………………..Page

Table 1-2- Critical success factors of information systems and e-learning systems. 31

Table 1-3 Components indexes for measuring the success of e-learning systems. 39

Table 2-3 verbal variables scale with triangular fuzzy numbers. 46

Table 1-4- the Results of KMO and kroit Bartlett’s test 57

Table 2-4. 58

Table 3-4- Reliability of questionnaire of e-learning system success 60

Table 4-4- Pearson correlation coefficient between the factors, entire test 61

Table 5-6- investigation the Mean and standard deviation of questionnaire questions. 61

Table 6-4- Comparative study of expert’s opinion. 63

Table 7-4- the paired comparisons mean toward the components (matrix W21) 69

Table 8-4: Matrix W22 of e-learning system components. 70

Table 9-4: Matrix Wi of e-learning system components. 71

Table 10-4- The Fuzzy weight for each component of e-learning systems success. 72

Table 11-4- the paired comparisons mean of system quality and infrastructure indexes (matrix W21), (Source: 1391 Research calculations) 74

Table 12-4: W22 matrix for system quality and infrastructure indicators. 74

Table 13-4: Wi matrix for Quality Systems and infrastructure indexes. 75

Table 14-4- Fuzzy weight for each index of system quality and infrastructure. 75

Table 15-4- the paired comparisons mean of service quality indexes (matrix W21) 77

Table 16-4: W22 matrix for service quality indexes. 77

Table 17-4: Wi matrix for service Quality indexes. 78

Table 18-4- Fuzzy weight for each index of service quality. 78

Table 19-4- the paired comparisons mean of information quality indexes. 80

Table 20-4: W22 matrix for information quality indexes. 81

Table 21-4-  Wi matrix for information quality indexes. 82

Table 22-4- Fuzzy weight for each index of information quality. 83

Table 23-4- the paired comparisons mean of student characteristic indexes (matrix W21), 85

Table 24-4: W22 matrix for student characteristic indexes. 85

Table 25-4- Wi matrix for student characteristic indexes. 86

Table 26-4- Fuzzy weight for each index of information quality. 86

Table 27-4- the paired comparisons mean of teacher characteristic indexes (matrix W21), 88

Table 28-4: W22 matrix for t teacher characteristics indexes. 88

Table 29-4-Wi matrix for teacher characteristic indexes. 89

Table 30-4- Fuzzy weight for each index of teacher characteristic. 89

Table 31-4- the paired comparisons mean of supporting factors indexes. 91

Table 32-4: W22 matrix for t teacher supporting factors. 91

Table 33-4-Wi matrix for supporting factors indexes: 92

Table 34-4- Fuzzy weight for each index of supporting factors. 92

Table 1-5: Weight of each component and indexes of e-learning system success. 96

Diagrams List

Title………………………………………………………………………………………………………………………………..Page

Diagram 1-4- Gender distribution of respondents. 53

Diagram 2-4- Frequency distribution of respondent’s education level. 54

Diagram 3-4- Frequency distribution of respondent’s experience Level 55

Diagram 4-4- Frequency distribution of respondents in terms of being teacher or student 55

Diagram 5-4- age group of respondents. 56

Diagram 4-6- screen plot 59

 Figures List

Title………………………………………………………………………………………………………………………………..Page

Figure 1-2 – critical success factors of e-learning on academic environment 22

Figure 2-2 – Aspects of e-learner’s satisfaction (Sun, et Al.2008) 23

Figure 2-3 – Delon and McLean Information System Success Model 23

Figure 4-2 – Delon and MacLean’s Information System Success modified Model 24

Figure 5-2 model of e-learning Success (Holsapple & Lee-Post, 2006) 25

Figure 6-2 – e-learning evaluation model (Johnson, Hornik, And Salas, 2008) 26

Figure 7-2 – online communities success Model (Lin & Lee, 2006) 27

Figure 8-2 – Model of online e-learning system success evaluation (Lin, 2007) 27

Figure 9-2-the technology acceptance model (TAM) in online learning systems. 28

Figure 10-2- hexagonal e-learning assessment model (HELAM) 2009) 28

Figure 11-2 – E-learning system acceptance model (Wang & Wang, 2009). 29

Figure 12-2- E-learning system evaluation model (Kanani, 1389) 30

Figure 1-3 Components and indexes for measuring the success of e-learning systems. 36

Figure 2-3- hierarchy Process and network process. 48

Figure 3-3- triangular fuzzy numbers. 50

Figure 1-4- Interaction of E-learning system components with each other 68

Figure 2-4- interaction the indexes of System quality and infrastructure component 73

Figure 3-4- interaction the indexes of service quality component with each other 76

Figure 4-4- interaction the indexes of information quality component with each other 79

Figure 5-4- interaction between the indexes of student characteristic component 84

Figure 6-4- interaction between the indexes of teacher’s characteristics component 87

Figure 7-4- interaction between the indexes of supporting factors. 90

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