## 4 Results
### Analysis of Evaluation Metrics
#### 4.2.3 Objective Performance: Efficiency and Effectiveness
The hybrid-based mode showed superior performance in complex tasks, indicating strong adaptability and reliability, but was less effective for complex tasks, where the text-based mode retained a clear advantage. Conversely, the menu-based mode showed lower effectiveness across all of the difficulty levels. These findings suggest that while the chatbot performed effectively in handling intermediate tasks and complex tasks, its lower effectiveness on more straightforward tasks, mainly through the hybrid- and menu-based modes, may indicate that users struggled to locate or access straightforward information; thus, more precise navigation or more intuitive query handling for basic inquiries might be needed. Table 8 indicates that the menu-based interaction mode achieved the best (lowest) efficiency scores for simple tasks, with a mean time of 1.24 \(\pm\) 0.32 s (median: 1.1, range: 1.0-1.8). This suggests that users can quickly complete simple tasks by using the menu interface. The text-based mode followed closely, with a mean time of 1.41 \(\pm\) 0.12 s, while the hybrid-based mode was slower, at 2.04 \(\pm\) 0.50 s, indicating that it may not be as optimized for simple interactions. For complex tasks, the menu-based mode also outperformed the others, with a mean time of 3.10 \(\pm\) 0.58 s (median: 2.9, range: 2.5-4.0), slightly faster than the text-based mode (3.48 \(\pm\) 0.34). The hybrid-based mode was less efficient for complex tasks, with a mean time of 4.19 \(\pm\) 0.25 s, indicating longer task completion times than the other modes. In the complex task category, the menu-based mode again showed the best efficiency, with a mean time of 2.62 \(\pm\) 1.10 s (median: 2.75, range: 1.2-3.8). The text-based mode had the highest average time (4.56 \(\pm\) 1.27 s), suggesting that it took longer for users to complete complex tasks than with the menu- and hybrid-based interfaces. The hybrid-based mode performed moderately well, with a mean time of 3.66 \(\pm\) 1.44 s.  
Overall, the menu-based mode demonstrated superior efficiency across all task complexities, because data could be retrieved quickly based on the defined query. The text-based mode showed competitive performance for more straightforward tasks, but it lagged for more complex ones, reflecting potential areas for improvement. The hybrid-based mode had slower response times across all task types, indicating the need for optimization to enhance speed. According to our results regarding effectiveness and efficiency, the menu-driven mode proved to be the most efficient across tasks of varying complexities, as it excelled in task completion; however, its effectiveness was lacking in more intricate tasks; therefore, improved query management is required. The text-based mode exhibited effectiveness with complex tasks, showcasing its resilience, but fell short in efficiency, indicating the potential for refinement. The hybrid-based mode excelled in level tasks, displaying adaptability,although it faced challenges with speed and effectiveness in simple and complex situations, suggesting areas for enhancement. Figure 5 illustrates the comparative analysis of effectiveness and efficiency across the three interaction modes (text-based, menu-based, and hybrid-based) at varying levels of question complexity (simple, intermediate, and complex). The efficiency scores were scaled from 0 to 100 using Equation (8). \[\text{Efficiency}\ =\ 100-\left(\frac{\text{Actual Time}-\text{Min Time}}{\text{ Max Time}-\text{Min Time}}\right) \tag{8}\]  
The hybrid-based mode was balanced, excelling in complex tasks (effectiveness = 80.7), although its efficiency was the lowest for simple tasks (75.7). Despite this, it recorded a significantly lower error count (F (2,58) = 9.45, \(p\) < 0.001, \(n^{\text{2P}}\) = 0.31) and shorter response times (F (2,58) = 10.82, \(p\) < 0.001, \(n^{\text{2P}}\) = 0.35), indicating reliability across different complexities.