Results of CH4 SPSS Data: Finding Results

Differences between faculty member toward eLearning based on attending university and type of teaching classes.

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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)

Subscales (questions from 17-34) University Mean SD
Perceived self-efficacy ( Q 17-19) AJU 4.0580 .80424
NBU 4.0556 .80540
Perceived enjoyment (Q 20-22) AJU 4.2246 .71191
NBU 4.2222 .71344
Perceived usefulness ( Q23-25) AJU 4.3797 .64954
NBU 4.4167 .65623
Behavioral intention to use e-learning
Q26-28
AJU 4.3029 .65901
NBU 4.4444 .65918
Perceived system satisfaction (Q29-31) AJU 3.9391 .80402
NBU 3.9444 .80540
Multimedia instructions (Q32-34) AJU 4.0174 .92865
NBU 4.0278 .92007
Box’s Test of Equality of Covariance Matricesa
Box’s M 31.172
F 1.461
df1 21
df2 542467.709
Sig. .079
Tests the null hypothesis that the observed covariance matrices of the dependent variables are equal across groups.
a. Design: Intercept + universt

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.

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Table 4.18. MANOVA Test of Faculty Members’ Perceptions Based on Current University

Effect Value F H.
df
Error
df
Sig.
Intercept Pillai’s Trace .989 6026.779b 6.000 403.000 .000
Wilks’ Lambda .011 6026.779b 6.000 403.000 .000
Hotelling’s Trace 89.729 6026.779b 6.000 403.000 .000
Roy’s Largest Root 89.729 6026.779b 6.000 403.000 .000
Current University Pillai’s Trace .032 2.198b 6.000 403.000 .042
Wilks’ Lambda .968 2.198b 6.000 403.000 .042
Hotelling’s Trace .033 2.198b 6.000 403.000 .042
Roy’s Largest Root .033 2.198b 6.000 403.000 .042

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

Source Dependent Variable SS df MS F Sig. Partial Eta Squared,p2
Current University Perceived self -efficacy .001 1 .001 .001 .976 .000
Perceived enjoyment .001 1 .001 .001 .973 .000
Perceived usefulness .138 1 .138 .324 .570 .001
Behavioral intention to use e-learning 2.023 1 2.023 4.657 .032 .011
Perceived system satisfaction .003 1 .003 .004 .947 .000
Multimedia instructions .011 1 .011 .013 .910 .000
Levene’s Test of Equality of Error Variancesa
F df1 df2 Sig.
selfefficacy .000 1 408 .989
enjoyment .002 1 408 .963
usefulness .082 1 408 .775
elearning .663 1 408 .416
satisfaction .001 1 408 .971
instructions .002 1 408 .964
Tests the null hypothesis that the error variance of the dependent variable is equal across groups.
a. Design: Intercept + universt

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.

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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)

Subscales (questions from 17-34) Currently Teaching Mean SD
Perceived self-efficacy ( Q 17-19) EL 4.2222 .68599
BLC 4.0822 .83464
BL 3.6667 .00000
Perceived enjoyment (Q 20-22) EL 4.1852 .78567
BLC 4.2161 .73835
BL 4.3333 .00000
Perceived usefulness ( Q23-25) EL 4.5556 .57166
BLC 4.3943 .68221
BL 4.3226 .05987
Behavioral intention to use e-learning
Q26-28
EL 4.6111 .50163
BLC 4.3878 .68344
BL 3.9570 .11359
Perceived system satisfaction (Q29-31) EL 4.0741 .56656
BLC 3.9012 .83837
BL 4.3333 .00000
Multimedia instructions (Q32-34) EL 4.0926 .96206
BLC 4.0203 .96204
BL 4.0000 .00000
Box’s Test of Equality of Covariance Matricesa
Box’s M 19.206
F .794
df1 21
df2 3079.495
Sig. .730
Tests the null hypothesis that the observed covariance matrices of the dependent variables are equal across groups.
a. Design: Intercept + type

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

Effect Value F H.
df
Error
df
Sig.
Intercept Pillai’s Trace .957 1491.153b 6.000 402.000 .000
Wilks’ Lambda .043 1491.153b 6.000 402.000 .000
Hotelling’s Trace 22.256 1491.153b 6.000 402.000 .000
Roy’s Largest Root 22.256 1491.153b 6.000 402.000 .000
Classes Currently Teaching Pillai’s Trace .346 14.060 12.000 806.000 .000
Wilks’ Lambda .656 15.709b 12.000 804.000 .000
Hotelling’s Trace .520 17.385 12.000 802.000 .000
Roy’s Largest Root .513 34.464c 6.000 403.000 .000

Note. H= hypothesis df

Levene’s Test of Equality of Error Variancesa
F df1 df2 Sig.
selfefficacy 70.321 2 407 .000
enjoyment 74.143 2 407 .000
usefulness 30.882 2 407 .000
elearning 50.472 2 407 .000
satisfaction 17.945 2 407 .000
instructions 17.271 2 407 .000
Tests the null hypothesis that the error variance of the dependent variable is equal across groups.
a. Design: Intercept + type

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

Source Dependent Variable SS df MS F Sig. Partial Eta Squared,p2
Class(es) Currently Teaching Perceived self-efficacy 5.443 2 2.722 4.281 .014 .021
Perceived enjoyment .420 2 .210 .414 .661 .002
Perceived usefulness .626 2 .313 .736 .480 .004
Behavioral intention to use e-learning 6.439 2 3.219 7.582 .001 .036
Perceived system satisfaction 5.662 2 2.831 4.458 .012 .021
Multimedia instructions .106 2 .053 .062 .940 .000

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

Multiple Comparisons
Tukey HSD
Dependent Variable (I) type (J) type Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval
Lower Bound Upper Bound
selfefficacy E-learning Classroom – based Learning .1400 .19258 .747 -.3130 .5930
Blended learning .5556 .23629 .050 -.0003 1.1114
Classroom – based Learning E-learning -.1400 .19258 .747 -.5930 .3130
Blended learning .4155* .14924 .015 .0645 .7666
Blended learning E-learning -.5556 .23629 .050 -1.1114 .0003
Classroom – based Learning -.4155* .14924 .015 -.7666 -.0645
enjoyment E-learning Classroom – based Learning -.0309 .17213 .982 -.4358 .3740
Blended learning -.1481 .21121 .763 -.6450 .3487
Classroom – based Learning E-learning .0309 .17213 .982 -.3740 .4358
Blended learning -.1173 .13339 .654 -.4311 .1965
Blended learning E-learning .1481 .21121 .763 -.3487 .6450
Classroom – based Learning .1173 .13339 .654 -.1965 .4311
usefulness E-learning Classroom – based Learning .1613 .15755 .562 -.2093 .5319
Blended learning .2330 .19332 .451 -.2218 .6877
Classroom – based Learning E-learning -.1613 .15755 .562 -.5319 .2093
Blended learning .0717 .12210 .827 -.2155 .3589
Blended learning E-learning -.2330 .19332 .451 -.6877 .2218
Classroom – based Learning -.0717 .12210 .827 -.3589 .2155
elearning E-learning Classroom – based Learning .2233 .15737 .332 -.1469 .5935
Blended learning .6541* .19310 .002 .1999 1.1083
Classroom – based Learning E-learning -.2233 .15737 .332 -.5935 .1469
Blended learning .4308* .12196 .001 .1439 .7177
Blended learning E-learning -.6541* .19310 .002 -1.1083 -.1999
Classroom – based Learning -.4308* .12196 .001 -.7177 -.1439
satisfaction E-learning Classroom – based Learning .1729 .19247 .642 -.2799 .6256
Blended learning -.2593 .23616 .516 -.8148 .2963
Classroom – based Learning E-learning -.1729 .19247 .642 -.6256 .2799
Blended learning -.4321* .14915 .011 -.7830 -.0813
Blended learning E-learning .2593 .23616 .516 -.2963 .8148
Classroom – based Learning .4321* .14915 .011 .0813 .7830
instructions E-learning Classroom – based Learning .0723 .22361 .944 -.4537 .5983
Blended learning .0926 .27438 .939 -.5528 .7380
Classroom – based Learning E-learning -.0723 .22361 .944 -.5983 .4537
Blended learning .0203 .17329 .992 -.3873 .4279
Blended learning E-learning -.0926 .27438 .939 -.7380 .5528
Classroom – based Learning -.0203 .17329 .992 -.4279 .3873
Based on observed means.
The error term is Mean Square (Error) =.857.
*. The mean difference is significant at the.05 level.

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

Descriptives
N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum
Lower Bound Upper Bound
selfefficacy E-learning 18 4.2222 .68599 .16169 3.8811 4.5634 3.33
Classroom – based Learning 361 4.0822 .83464 .04393 3.9958 4.1686 2.67
Blended learning 31 3.6667 .00000 .00000 3.6667 3.6667 3.67
Total 410 4.0569 .80376 .03969 3.9789 4.1349 2.67
enjoyment E-learning 18 4.1852 .78567 .18519 3.7945 4.5759 3.00
Classroom – based Learning 361 4.2161 .73835 .03886 4.1396 4.2925 3.00
Blended learning 31 4.3333 .00000 .00000 4.3333 4.3333 4.33
Total 410 4.2236 .71171 .03515 4.1545 4.2927 3.00
usefulness E-learning 18 4.5556 .57166 .13474 4.2713 4.8398 3.33
Classroom – based Learning 361 4.3943 .68221 .03591 4.3237 4.4649 3.00
Blended learning 31 4.3226 .05987 .01075 4.3006 4.3445 4.00
Total 410 4.3959 .65194 .03220 4.3326 4.4592 3.00
elearning E-learning 18 4.6111 .50163 .11824 4.3617 4.8606 3.67
Classroom – based Learning 361 4.3878 .68344 .03597 4.3171 4.4586 3.00
Blended learning 31 3.9570 .11359 .02040 3.9153 3.9987 3.67
Total 410 4.3650 .66202 .03270 4.3008 4.4293 3.00
satisfaction E-learning 18 4.0741 .56656 .13354 3.7923 4.3558 3.00
Classroom – based Learning 361 3.9012 .83837 .04412 3.8144 3.9880 2.00

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.

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