## 5 Discussion
The difference in results of performance and understanding subscales highlights an important nuance in how trust is developed and perceived among users. While Taguette was most trusted for task performance, users expressed greater confidence in calibrating their trust towards ChatGPT. In this case, trust may have been influenced by factors such as familiarity, prior experience, and user expectations. Enhancing users' familiarity with a tool through effective onboarding or training could potentially change obtained results and improve their understanding and calibration of trust, thereby increasing overall user satisfaction and performance. Future research could explore strategies to bridge the gap between performance trust and understanding trust, ultimately leading to a more cohesive UX across QDA tools. The results from the Single Ease Question (SEQ) provide valuable insights into users' perceptions of task difficulty across the evaluated tools. The average SEQ score (\(\overline{\chi}_{all}=2.01\)) in this study was lower than the average scores obtained over 4000 tasks by [85], where a mean score of around 5.5 was observed. This comparison indicates that the tasks in this study were seen as quite complex by the participants. The mean values, compared to the average scores of previous studies, are presented in Figure 12. The overall mean SEQ score of ChatGPT was 1.71, followed closely by Gemini with 1.86. Taguette reached higher mean values, indicating greater perceived task difficulty with an overall mean SEQ score of 2.46. With these values, ChatGPT is placed in the highest tenth percentiles by the task's difficulty, while Gemini and Taguette were placed within the top 25% of the most difficult tasks. The consistent trend of higher SEQ scores for Taguette (also visible in separate observations per task) suggests that users perceived this tool as more complex and challenging to navigate, highlighting potential usability issues that could hinder effective task completion. In contrast, AI-based chatbots were associated with a lower task difficulty (while completing a very similar task), as evidenced by their significantly lower SEQ scores across both tasks. The Kruskal-Wallis H test confirmed a significant difference in SEQ scores for Task 1 among the three tools (\(\chi^{2}(2)=52.293,p<0.001\)), with a large effect size (\(\eta^{2}=0.1972\)). The pairwise comparisons revealed that the differences in perceived difficulty between Taguette and the other tools were statistically significant, further highlighting the challenges users faced when interacting with Taguette. Interestingly, the lack of significant differences in SEQ scores for Task 2 (\(\chi^{2}(2)=2.039,p=0.361\)) suggests that users may have adapted to the tasks or that the second task was inherently less complex across all tools. This points to the potential for learning effects or task characteristics to influence perceived difficulty, underscoring the need for further investigation into how task design and user familiarity can impact users' perceptions of the tool. The mental workload evaluation, conducted with NASA-TLX in this study yielded results comparable to prior studies utilizing this tool. [PERSON] [86] reported an analysis of over 1000 uses of NASA-TLX scores from over 200 publications. The mean values reported in our study were in the range of 26-32 for the AI tools (ChatGPT, Gemini) and in the range of 49-57 for the non-AI tool (Taguette). This positions the results of AI tools in the 20% of the lowest scores observed in the literature (by [86]), while the non-AI tool is positioned in the 50%-70% percentile.