## 4 Results and Discussion
### Scenario Analysis  
On top of the baseline analysis performed previously, a scenario analysis was performed as a post-analysis to demonstrate how the prioritization of barriers changes when some of the critical barriers become fully addressed due to the extensive implementation of available alternative strategies. In the first scenario (a), the influence of the cost barrier (B2) on all other barriers is assumed to be near zero, while the influence of other barriers is assumed to be as is. In the second scenario (b), the influence of the barrier on lack of training resources (B5) on all other barriers is assumed to be near zero, while the influence of the other barriers is assumed to be as is. Simultaneous implementation of the computational framework for both cases was performed, and the resulting prominence relation maps are presented in Figure 5. The heatmaps of the total relation matrix for both scenarios are also presented in Figure 6.  
Figure 5: Prominence-relation maps for scenario (**a**) and scenario (**b**).  
The critical barriers identified in the baseline analysis remain critical for both post-analysis scenarios. For scenario (a), the cost barrier is no longer classified as critical. This result is expected because its initial influence on other barriers is reconfigured to near zero. The result for scenario (b) presents a more interesting finding. In scenario (b), the lack of training resources remains a critical barrier regardless of its initially near-zero influences on other barriers. These results can be easily explained by zooming into the heatmaps in Figure 5. The relationships involving the cost barrier in scenario (a) are not sufficiently significant to be considered critical. However, the opposite is observed for the barrier on lack of training resources in scenario (b). It should be noted that in the baseline case (see Figure 3), the majority of the critical relationships are influences of other barriers towards the complexity of learning platforms (B11), while the majority of the critical relationships have the barrier on lack of training resources (B5) as the source of influence.  
On the other hand, scenario (b) demonstrates that addressing the barrier on lack of training resources (B) eliminates almost all critical relationships of other barriers towards the complexity of learning platforms (B11). This result is both intuitive and demonstrative of the effects of strategic planning. By focusing attention on the most critical barrier, in the case of the baseline case/results--B5, all other barrier relationships are also addressed. Comparing the heatmaps in Figures 4 and 6, it is also clear that addressing the critical barriers significantly reduces the overall barrier influences in the system. This result is indicative of the general alleviation of the EDUC4 implementation barriers in the system, which is deemed ideal. The reduction in the mean influence of barriers to one another (in matrix \(T\)) for the baseline, scenario (a), and scenario (b) while omitting the row with all zeros (to avoid bias) yields statistically significant results (see Table 4). The statistical results reveal that, although the lack of training resources (B5) has the most significant relationship with other critical barriers in the baseline case, addressing it does not yield a better result. Instead, addressing the cost barrier (B2), which only has one critical relationship in the baseline case, yields a statistically better abatement of mean influence in the total relation matrix. These results demonstrate that the quantity/frequency of critical relationships may  
Figure 6: Heatmaps of the total relation matrix for scenario (a) and scenario (b).  
not be a direct indicator of priority. Instead, the quality of critical relationships may be seen as a better measure for prioritizing EDUC4 implementation barriers.