Differences between faculty member toward eLearning based on attending university and type of teaching classes.
Continued chapter 4 finding
Five separate one-way multivariate analyses of variances (MANOVAs) were conducted to test for significant differences between each of the demographic variables (i.e. gender, age, educational level, nationality, teaching experience) and the six perceptions of e-learning variables (self–efficacy, enjoyment, usefulness, behavioral intention, system satisfaction, use of multimedia). All five MANOVAs were statistically significant with alpha at .05.
The following sections report the results of the MANOVAs, and corresponding univariate ANOVA results, for each of the demographic variables. ANOVAs results following up by Post hoc comparisons using the Tukey HSD test indicated that the mean score for demographic variables to find out which groups differ from each other (Warner, R. M., 2008).
Findings the Differences between participants Based on Current University
Faculty member from two universities in the KSA was attended in this study. Mean scores and standard deviations for educational level are displayed in Table 4.18. Higher mean scores indicated a stronger agreement with the survey statements. Table 4.18 shows that in case of most of the subscales, the respondents have shown higher degree of agreement towards the survey results.
Table 4.18. Means and Standard Deviations for Survey Subscales by Current University (n= 410)
The box test of homogeneity for MANOVA shown by the Box Test of Equality of Covariance Matrix shows that the “Sig.” Value is less than.001. In this case, it is not as p=.079 indicating that it adheres to the homogeneity assumption of multivariate ANOVA indicating that there is variance in the data. If the p value was less than.01 it would have negated the homogeneity assumption and Robust test of equality of mean had to be done. But as the homogeneity assumption is met in the test of homogeneity of variance, it shows that the underlying assumption of MANOVA is met.
One – way MANOVA revealed a significant multivariate effect for educational level, Wilks’ Lambda =.968 F(6,2.19)=403, p <.042. Table 4.18 contains the MANOVA summary data. These results show that the participants’ perceptions of e-learning were influenced or not by their current university. The MANOVA results therefore prove that there is a strong influence of the current university on e-learning.
Table 4.18. MANOVA Test of Faculty Members’ Perceptions Based on Current University
Note. H = hypothesis df
ANOVAS Univariate tests for educational level on the six perceptions of e-learning variables are reported to Table 4.19. To account for the possibility of inflated statistical error, an alpha of.001 was used for the univariate analysis using the Bonferroni inequality (Stevens, 1992). Table 4.19 shows that the participants’ perceptions of e-learning were influenced by their current university.
Table 4.19. Univariate Test of Faculty Members’ Perceptions (subscales) Current University
Leven’s test in the above table shows that for all the cases there is homogeneity of variance as p>.05 in all six cases. This meets the underlying assumption of Levene’s homogeneity assumption as the F-statics of the independent variables are not significant.
The ANOVA results indicate the current university status of the respondents showed that the behavioral intention to use e-learning changed with Current University, F(4.657)= 2.023, p<0.032. ANOVA results show that behavioral intention to use e-learning had a significant effect on the current university status of the respondents with the Partial Eta Squared value at.011.
Perceived usefulness. ANOVA showed that the perceived usefulness was not significantly influenced by current university with F (.324) =.138, p >.57.
Behavioral intention. ANOVA showed that the behavioral intention to use e-learning was significantly influenced by the current university of the respondent F (4.675) = 2.023, p <.032. The above analysis of the six subscales using one-way MANOVA shows that current university has a strong effect on the respondents’ perception of e-learining in case of perceived usefulness and behavioral intention scales.
The ANOVA results for perceived usefulness scale shows that the there is no significant influence by current university with F (.324) =.138, p >.57. In case of behavioral intention, ANOVA results show that the intention to use e-learning was significantly influenced by the current university of the respondent F (4.675) = 2.023, p <.032. All the other subscales showed that they were not significantly affected by current university.
Findings the Differences between Participants Based on Class(es) Currently Teaching
The demographic variable of Class(es) Currently Teaching was categorized on three levels : a) E-learning (EL), (b) Classroom – based Learning(BLC), (c) Blended learning(BL). Faculty member from two universities in the KSA was attended in this study. Mean scores and standard deviations for classes currently teaching are displayed in Table 4.20. Higher mean scores indicated a stronger agreement with the survey statements.
Table 4.20. Means and Standard Deviations for Survey Subscales by Classes Currently Teaching (n= 410)
The Boxes test for equality of covariance shows that p>.73 indicating that the null hypothesis of homogeneity of variance the underlying assumption of MANOVA holds for the test indicating differences in variance of the data. Table 4.21 contains the MANOVA summary data. One – way MANOVA revealed a significant multivariate effect for educational level, Wilks’ Lambda=.43 F(15.709)=.65, p <.000. The MANOVA results indicate that the classes currently teaching were greatly affected by the depended variables. The results demonstrate that the MANOVA result is strongly supports the argument that current classes teaching has a strong effect on faculty member’s perception about e-learning.
Table 4.21. MANOVA Test of Faculty Members’ Perceptions Based Class(es) Currently Teaching
Note. H = hypothesis df
Levene’s Test for equality of error of variance also shows that the null hypothesis of the MANOVA that the error of variance of the dependent variables are present is shown in the above table as p<.000. As this does not meet the homogeneity of variance assumption, we have to look at the Robust test of equality of mean rather than variance.
Univariate tests for educational level on the six perceptions of e-learning variables are reported to Table 4.23. To account for the possibility of inflated statistical error, an alpha of.001 was used for the univariate analysis using the Bonferroni inequality (Stevens, 1992). Table 4.12 shows that the participants’ perceptions of e-learning were influenced by their current university.
Table 4.22 shows that the classes currently teaching had a great positive influence on perceived efficacy, behavioral intention to use e-learning and perceived system satisfaction. Univariate results show that current teaching had significant effect on perceived efficacy F(4.281)=.021, p<.014, for behavioral intention to use e-learning F(7.582)=.036, p<.001, and for system satisfaction F(4.458)=.021, p<.012.
Table 4.22. Univariate Test of Faculty Members’ Perceptions (sub-scales) Class(es) Currently Teaching
The ANOVA results indicate that classes currently teaching changed positive reactions pertaining to efficacy, F(4.281)=.021, p<.014, behavioral intentions, F(7.582)=.036, p<.001, and system satisfaction F(4.458)=.021, p<.012.
Perceived self-efficacy. ANOVA showed that the perceived usefulness was of Currently Teaching the respondent F(4.281) = 5.443, p<.014, p2=.021. Table 4.24 shows that Post hoc comparisons using the Tukey HSD test indicated that the mean score for self efficacy was significantly different from classroom based blended e-learning with a mean difference (MD)=4.185, p<.015.
Perceived enjoyment. ANOVA showed that the perceived usefulness was not significantly influenced by the classes teaching F (.414) =.420, p >.661. Post-hoc Tukey test showed that there was no significant difference between enjoyment and any of the other dependent variables.
Perceived usefulness. ANOVA showed that the perceived usefulness too did not have any significant influence on the classes currently teaching.
Behavioral intention. ANOVA showed that the behavioral intention to use e-learning was significantly influenced by the current classes teaching of the respondent F (7.582) = 6.439, p<.001. Post hoc comparisons using the Tukey HSD test indicated that the mean score for behavioral intentions showed a significant difference with class-room based blended learning.
Perceived system satisfaction. ANOVA showed that the behavioral intention to use e-learning was significantly influenced by the current classes teaching of the respondent F (4.458) = 5.662, p<.021. Post hoc comparisons using the Tukey HSD test indicated that the mean score for system satisfaction and blended and classroom learning.
Multimedia instruction. ANOVA showed that the multimedia instruction was not significantly influenced by the educational level of the respondent post-hoc Tukey test too did not show any significant difference in mean value.
Table 4.23. Tukey Test of Faculty Members’ Perceptions (sub-scales) Class(es) Currently Teaching
Table 4.24 presents the descriptive statistics for faculty member’s perception on classes currently taught. A high degree of mean value indicates a high level of agreement of the respondents tot eh survey questions. Table 4.23 shows that there is a high degree of difference in mean for group 1 with mean difference coming to more than 0.4.
Table 4.24. Descriptive statistics of Faculty Members’ Perceptions (sub-scales) Class(es) Currently Teaching
In conclusion, current classes teaching have a strong effect on efficacy, behavioral intention, system satisfaction of the faculty members. As shown through the ANOVA results that classes currently teaching changed positive reactions pertaining to efficacy, F(4.281) = 5.443, p<.014, behavioral intentions, F(7.582) = 6.439, p<.001, and system satisfaction F(4.458)= 5.662, p<.012.
Therefore, the one-way MANOVA test and ANOVA and the post-hoc analyses demonstrates that classes currently teaching has significant influence on perceived efficacy, behavioral intention towards e-learning, and system satisfaction of the faculty members.