## 5 Data Analysis and Results
### SEM Analysis
#### 5.2.2 Structural Model  
Structural equation modeling (SEM) using Amos 20 was performed to test the study hypotheses. SEM allows simultaneous testing of all hypotheses including direct effects. The results of the direct effects indicate that while source credibility (SC) impacted information usefulness (IU), information language (IL) did not. Consequently, while H1 was accepted, H2 was not supported. Moreover, intrinsic information quality (IIQ), contextual information quality (CIQ), and accessibility information quality (AIQ) impacted information quality (IQ); thus, H3, H4, and H5 were supported. The results found that information quality (IQ) impacted information usefulness (IU), and the latter had an effect on information adoption (IA), and, in turn, on academic achievement (AA); consequently H6, H7, and H8 were supported.  
Moreover, the coefficient of determination (R\({}^{2}\)) for the research endogenous variables IQ, IU, IA, and AA were 0.929, 0.922, 0.945, and 0.928, respectively, which suggests that the research model does account for the variation. Table 7 below presents an abstract of the tested hypotheses.  
To reflect the results shown in Tables 3 and 7 onto the proposed model, Figure 2 was developed to show with a graph and numbers the results of this research. The figure shows the mean and standard deviation for each construct. Moreover, it reflects the value of  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Constructs** & **SC** & **IL** & **IIQ** & **CIQ** & **AIQ** & **IU** & **IQ** & **IA** & **AA** \\ \hline SC & 0.98 & & & & & & & \\ \hline IL & 0.714 & 0.97 & & & & & & \\ \hline IIQ & 0.836 & 0.815 & 0.97 & & & & & \\ \hline CIQ & 0.888 & 0.821 & 0.888 & 0.99 & & & & \\ \hline AIQ & 0.900 & 0.820 & 0.887 & 0.883 & 0.98 & & & \\ \hline IU & 0.871 & 0.899 & 0.877 & 0.878 & 0.876 & 0.95 & & \\ \hline IQ & 0.923 & 0.843 & 0.854 & 0.836 & 0.847 & 0.843 & 0.94 & \\ \hline IA & 0.921 & 0.819 & 0.853 & 0.834 & 0.846 & 0.850 & 0.885 & 0.98 & \\ \hline AA & 0.881 & 0.879 & 0.878 & 0.871 & 0.879 & 0.873 & 0.857 & 0.859 & 0.98 \\ \hline \hline \end{tabular} Note: Diagonal elements are square roots of the average variance extracted for each of the ten constructs. Off diagonal elements are the correlations between constructs.  
\end{table}
Table 6: Correlations of constructs.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Research** & **Coefficient** & **t-Value** & **\(p\)-Value** & **Empirical** \\
**Proposed Paths** & **Value** & & **Evidence** \\ \hline H1: SC \(\rightarrow\) IU & 0.233 & 16.344 & 0.000 & Supported \\ \hline H2: IL \(\rightarrow\) IU & 0.009 & 0.507 & 0.612 & Not supported \\ \hline H3: IIQ \(\rightarrow\) IQ & 0.084 & 7.720 & 0.000 & Supported \\ \hline H4: CIQ \(\rightarrow\) IQ & 1.012 & 95.741 & 0.000 & Supported \\ \hline H5: AIQ \(\rightarrow\) IQ & 0.053 & 4.215 & 0.000 & Supported \\ \hline H6: IQ \(\rightarrow\) IU & 0.861 & 89.513 & 0.000 & Supported \\ \hline H7: IU \(\rightarrow\) IA & 0.952 & 109.907 & 0.000 & Supported \\ \hline H8: IA \(\rightarrow\) AA & 1.041 & 95.116 & 0.000 & Supported \\ \hline \hline \end{tabular}
\end{table}
Table 7: Summary of the results for the research theoretical model.  
coefficient of determination (R\({}^{2}\)) for each intermediate construct and the coefficient value for each relation.