# AI-Supported EUD for Data Visualization: An Exploratory Case Study
## 4 Phase 2: Answering RQ2
### Results
#### 4.3.1 Findings for the Basic User  
The following main themes emerged for the basic user profile. **Prompting requires training. ** During interaction with the system, the basic user often asked us for confirmation before proceeding with the task at hand; this happened in particular when task 1 started, as there were some hesitations in formulating the natural language requests to the prototype. Crafting prompts may be difficult for users who rarely use LLMs, leading to complex queries that should be refined at each new iteration. Despite these initial difficulties, the user found that interacting was beneficial, mainly when a new \begin{table}
\begin{tabular}{l l} \hline \hline
**No.** & **Question** \\ \hline
1 & Was it easy for you to express your needs to the system? \\
2 & Was the system response clear and understandable? \\
3 & Was the system response satisfactory and accurate, or would you have preferred another response? \\
4 & Did the system seem to remember previous interactions or your preferences? \\
5 & Do you think this system could improve your work in creating data viz? \\
6 & Would you trust using this system to perform your work? \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Final questionnaire. data viz was exploited for the first time, i.e., a heatmap. In fact, the user observed: _\"Unlike searching on the Internet, here I was working with data I'm already familiar with, so asking for an example based on that made learning much faster. As soon as I saw the table, I understood how it worked and thought that this was nice and useful, I could actually use it in the future\"_. **Problem-solving based on trial and error. ** Task execution was characterized by a trial-and-error style. For example, when the system generated a line chart instead of the intended bar chart for analyzing suppliers and their service level, the user successfully identified the issue and solved it. Likewise, some attempts to incorporate multiple categories in a bar chart were unsuccessful, requiring continuous adjustments and many prompts. In synthesis, the prompting activity often required iterative refinement to yield the desired result. Nonetheless, the user seemed to acknowledge and appreciate the tool capability of providing data viz and data manipulation, recognizing some advantages over human error for some tasks (_\"Yes, it definitely makes fewer mistakes than I do when I manually copy formulas over and over. Once the data and databases are loaded into the system, there's significantly less room for human error\"_). **Expectations about how LLMs work. ** Managing dates within the system proved to be another dull activity, and the expected handling was not always clear (_\"I cannot really read the dates...Oh, right. You can hover over the line to see specific values. But I asked for data from December, and it only shows February. Is it just me not reading it correctly?\"_). The user also showed a strong wish for accuracy by frequently checking interpretations and emphasizing proper wording, having little confidence and trust in the LLM. **Difficulties in feature discovery. ** Some functionalities, like sorting data, did not initially come to mind but were successfully used after our suggestions. In the same vein, there was a lack of familiarity with many types of available data viz, but once reminded of available options, the user actively explored new data visualizations (such as the heatmap mentioned above) and extended this understanding to other tasks. The basic user often expressed challenges in interpreting data visualizations, sometimes unaware of interactive features like the mousover functionality. Another remark was on the importance of precisely entering dataset column names (_\"Oh, I think it's because I didn't write it correctly...I was supposed to use a capital letter. I made a mistake\"_). A key request was the possibility to place different data visualizations side by side for easier comparison. **Ease of natural language interaction.