Vol. 1(2) SEP 2011 - SAVAP International

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Academic Research International ISSN: 2223-9553 Volume 1, Issue 2, September 2011 Table 4.48 above shows the final cluster centers, it gives the mean averages of each application in each cluster, which enables a descriptive name to be given to each cluster based on their dominant averages. Binary Logistic Regression In this section, the binary logistic regression analysis was conducted to explore factors that were associated with adoption groups namely, low adopters; moderate adopters and high adopters as the three-group dependent variable and 13 predictor variables refer. Backward eliminations, a method of stepwise regression were used as it would retain only the predictor variables that were statistically significant in the model (Menard, 2002). The preliminary results of the chi-squared tests and pseudo R square values that measure the effectiveness of the regression model (testing the overall fit of the model) showed that the chi-squared differences was significant at 0.00 level (Table 8 below). In other words, the improvement in the results after the predictor variables were included provides evidence that the predictors were indeed associated with adoption. Table 8 Model Fitting Information -2 Log Likelihood Chi-Square Df Sig. Intercept Only 638.142 Final 511.194 126.948 26 .000 In addition, Table 9 below shows that Nagelkerke R square value of 0.371 for the overall model. The results indicate the model could explain approximately 38% of the variance in the dependents variables. Nagelkerke R square is chosen because it is a modification over the Cox and Snell R square and has a range of 0 – 1. Table 9 Pseudo R-Square Cox and Snell .315 Nagelkerke .371 Table 10 Binary Logistic Regression Model Low-adopters vs. High-adopters Moderate-adopters vs. High-adopters Moderate-adopters vs. Low-adopters Coff (β) Wald p-value Coff (β) Wald p-value Coff (β) Wald p-value Relative -.612 .045 -.112 .705 .501 .001 Flexibility -.224 .398 .099 .700 .323 .036 Compatibility -1.002 .001 -.346 .247 .656 .000 Complexity -.467 .170 .032 .921 .500 .018 Trialability -.607 .077 -.306 .322 .300 .183 Observability -.286 .426 .088 .783 .374 .133 Management .965 .013 .025 .944 -.940 .000 Structure -.616 .031 -.355 .173 .261 .143 Culture -1.131 .002 -1.061 .002 .070 .771 Social contact -.464 .130 -.136 .639 .328 .043 Professional .116 .618 .514 .021 .398 .010 advancement Social -.311 .350 -.670 .036 -.359 .069 stimulation External -.274 .324 .076 .775 .350 .040 expectations Cognitive interest .456 .245 .051 .887 -.405 .096 Copyright © 2011 SAVAP International www.savap.org.pk www.journals.savap.org.pk 366
Academic Research International ISSN: 2223-9553 Volume 1, Issue 2, September 2011 The Wald statistic is used to evaluate the statistical significance of each predictor variable in explaining the dependent variable, and Wald statistic indicates whether the β-coefficient for a predictor is significantly different from zero. If so, then the predictor variable is assumed to make a significant contribution to the prediction of the outcome of the dependent variable. The summary of the results from the binary logistics regressions were shown in table 10. Eleven predictor variables, namely relative advantage, flexibility, compatibility, complexity, top management support, culture, structure, social contact, professional advancement, social stimulation and external expectations were found to be significantly associated with e-learning adoption with various groups of adoption. DISCUSSION In this section discusses the result that emerged from the data analysis. Attempts will be made to explore how the result related to the findings from previous studies. The approaches adopted in this section are that the discussion will reiterate the highlights if the results are as expected, and if the results are unexpected, the discussion will be an attempt to reconcile. The results obtained from interpreting the adoption level and matrix will be discussed and followed by discussion on factors associated with e-learning adoption. Characterizing E-learning Adoption This study has developed a framework to characterised and measure e-learning adoption on a twodimensional matrix representing level of adoption and extent of usage. The level of adoption was represented by teen types of e-learning application. The extent of usage was measured using four category scale represented by not using, use sometime, use most of the time and use all the time with e-learning applications. Previous studies have approach to examine the e-learning adoption by two perspectives which are “adopted or net adopted”. Also, these studies were focused just in one perspective in order to examine the e-learning adoption (e.g. Duan et al. 2010; Hung et al. 2009). While, this study has aimed to examine adoption by focusing on both the range of e-learning applications adopted and the extent of usage of each one in order to provide a comprehensive picture of the adoption of e-learning among adult workers in Jordan. In order to capture information on the extent of usage for each e-learning application, a K-mean clustering has been conducted for this study. Depend on a study sample of 335 responding adult workers; the K-mean has successfully identified diverse e-learning applications’ adoption groups among adult workers in Jordan. These groups were considered as low adopters, moderate adopters and high adopters. The important of K-mean lies in its flexibility, without being restricted by the measurement scale when identifying adoption patterns. Also, this method enables various adoption patterns to be identified the two-dimensional. The first group is the low adopters presented about 37.3% of the study sample. In this group, the choice of application being adopted by these adult workers is limited. Adult workers have mainly adopted e-learning adoption such as e-mail, registration, online library, grades and video. The findings of this study suggest that, these applications methods are more widely used by adult workers than others applications. Also, as discussed in the literature review (chapter two) many students including adult workers have a lack of experience with using the new technology especially in Jordan due to e- learning adoption is still innovation method of learning to numerous students (Abbad and Nahlik, 2009). The next group is the moderate adopters presented about 51.6%, of the study sample. The adult workers have mainly adopted e-learning adoption such as e-mail, registration, online library, grades, video, online chat, audio and online course. This group of adopters is similar to the adoption stage (Hung et al. 2009). Moderate adopters have taken the first step to adopt more advanced internet Copyright © 2011 SAVAP International www.savap.org.pk www.journals.savap.org.pk 367
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