## 4 Results
### Mental Workload Evaluation
\begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Sample 1-Sample 2** & **Test Statistic** & **Std. Error** & **Std. Test Statistic** & **Sig.** \\ \hline \multicolumn{5}{c}{Task 1} \\ \hline ChatGPT-Gemini & \(-6.208\) & \(11.348\) & \(-0.547\) & \(0.584\) \\ ChatGPT-Taguette & \(-92.165\) & \(11.477\) & \(-8.030\) & **<0.001** \\ Gemini-Taguette & \(-85.957\) & \(11.314\) & \(-7.598\) & **<0.001** \\ \hline \multicolumn{5}{c}{Task 2} \\ \hline Gemini-ChatGPT & \(14.283\) & \(11.252\) & \(1.269\) & \(0.204\) \\ Gemini–Taguette & \(-65.004\) & \(11.348\) & \(-5.728\) & **<0.001** \\ ChatGPT-Taguette & \(-50.721\) & \(11.147\) & \(-4.550\) & **<0.001** \\ \hline \hline \end{tabular} _Note: Bold values indicate statistical significance at the 0.05 level._  
\end{table} 
Table 8: Pairwise comparison of NASA-RTLX scores for tools with [PERSON]’s Test procedure. Figure 9: NASA-RTLX values for Taguette, ChatGPT, and Gemini, per tasks. them in managing perceived time pressure better (the experiment had no time restraints for tasks). The subscale performance revealed that users were more satisfied with their performance when using Taguette in the first task, though this satisfaction slightly decreased in the second task, while the satisfaction with their performance when using AI tools improved. However, Taguette reached the highest mean values for perceived performance in both tasks (\(\overline{x}_{Taguette1}=10.63,\overline{x}_{Taguette2}=9.71\)). The effort required to complete the task was quite higher for Taguette tool, especially in the first task (\(\overline{x}_{Taguette1}=10.24,\overline{x}_{Taguette2}=7.65\)), compared to the use AI tools (\(\overline{x}_{Chat1}=3.20,\overline{x}_{Cemini1}=4.58\)). This could indicate that the use of AI tools could aid efficiency. Observing the frustration subscale, Taguette, users experience higher frustration levels across both tasks. With the use of AI tools for the tasks, particularly ChatGPT, users showed much lower frustration levels (e.g., for the first task \(\overline{x}_{Taguette1}=8.33,\overline{x}_{ChatGPT}=2.99,\overline{x}_{Cemini }=4.20\)). Mean NASA-TLX values for each tool are visualized in Figure 10, with Figure 10a representing the results for Task 1 and Figure 10b representing the results for Task 2. Kruskall-Wallis H tests were used to analyze the difference between the tools for each subscale and task. The results are also reported in Table 9. The test indicated a significant difference between tools in all six subscales. Observing the first task, for mental demand, \(\chi^{2}(2)=77.133,\)\(p<0.001\), Taguette reached the highest mean rank with 186.43, followed by Gemini with 104.26 and ChatGPT with 98.64. For physical demand, \(\chi^{2}(2)=39.177,\)\(p<0.001\), Taguette also reached the highest mean rank with 167.84, followed by Gemini with 113.92 and ChatGPT with 107.21. For temporal demand, \(\chi^{2}(2)=6.714,p=0.035,\) [PERSON] also reached the highest mean rank with 146.62, followed by ChatGPT with 121.36 and Gemini with 120.83. The results were similar for the performance subscale, \(\chi^{2}(2)=24.229,p<0.001\), where [PERSON] reached the highest mean rank with 161.35, followed by ChatGPT with 119.63 and Gemini with 108.40. A significant difference was also observed for effort, \(\chi^{2}(2)=91.011,p<0.001\), as [PERSON] reached the highest mean rank with 190.41, followed by Gemini with 110.93 and ChatGPT with 87.54. Lastly, for frustration, \(\chi^{2}(2)=50.357,p<0.001\), [PERSON] reached the highest mean rank with 173.35, followed by Gemini with 118.93 and ChatGPT with 96.35. Similar results were observed for the second task, with slight changes in mean rank order for ChatGPT and Gemini. For mental demand, \(\chi^{2}(2)=17.340,p<0.001\), [PERSON] reached the highest mean rank with 152.32, followed by [PERSON] with 118.98 and [PERSON] with 107.80. For physical demand, \(\chi^{2}(2)=22.518,p<0.001\), [PERSON] also reached the highest mean rank with 155.31, followed by [PERSON] with 114.90 and [PERSON] with 109.09.