# Analyzing the Impact of a Structured LLM Workshop in Different Education Levels
## 3 Results
### Surveys and Interviews
#### 3.2.3 Group Comparison Analysis
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multicolumn{10}{c}{**Q24. Were There Many Instances Where ChatGPT’s Responses Did Not Align with the Tone or Style You Wanted for Your Short Story**} \\ \hline  & \multicolumn{3}{c}{**1—Many**} & \multicolumn{3}{c}{**2—Rather a Lot**} & \multicolumn{3}{c}{**3—Some**} & \multicolumn{3}{c}{**4—Rather None**} & \multicolumn{3}{c}{**5—None**} & \multicolumn{1}{c}{**Blank**} \\ \hline
**Group** & \(n\) & **Friq** & **Friq \%** & **Friq \%** & **Friq \%** & **Friq \%** & **Friq \%** & **Friq \%** & **Friq \%** & **Friq \%** & **\%** \\ \hline
11 ELS & 60 & 3 & 5.00\% & 5 & 8.33\% & 31 & 51.67\% & 15 & 25.00\% & 6 & 10.00\% & 0.00\% \\ \hline
12 ELS & 34 & 0 & 0.00\% & 4 & 11.76\% & 9 & 26.47\% & 13 & 38.24\% & 7 & 20.59\% & 2.94\% \\ \hline
12 Math & 21 & 2 & 9.52\% & 5 & 23.81\% & 9 & 42.86\% & 4 & 19.05\% & 1 & 4.76\% & 0.00\% \\ \hline
3 SE & 15 & 0 & 0.00\% & 3 & 20.00\% & 4 & 26.67\% & 5 & 33.33\% & 2 & 13.33\% & 6.67\% \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Q24 result analysis result percentage distribution. Question Q29 (seen in Table 8 and Figure 8) evaluates the increase in interest in information systems and technologies in general. The answer distribution displays the overall small increase in interest of the various groups. Some participants were thoroughly impressed and motivated, while others were not. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multicolumn{10}{c}{**Q28. After Working Together with LLMs to Generate Content and Code, How Likely Are You to Use Them in the Future in Your Education? (No 1-Yes 5)**} \\ \hline  & \multicolumn{3}{c}{**1—Not**} & \multicolumn{3}{c}{**2—Rather Not**} & \multicolumn{3}{c}{**3—Maybe**} & \multicolumn{3}{c}{**4–Closer to Yes**} & \multicolumn{3}{c}{**5–Yes**} & \multicolumn{1}{c}{**Blank**} \\ \hline
**Group** & \(n\) & **Friq** & **Friq \%** & **Friq \%** & **Friq \%** & **Friq \%** & **Friq \%** & **Friq \%** & **Friq \%** & **Friq \%** & **\%** \\ \hline
11 ELS & 60 & 1 & 1.67\% & 7 & 11.67\% & 33 & 55.00\% & 14 & 23.33\% & 4 & 6.67\% & 0.00\% \\ \hline
12 ELS & 34 & 2 & 5.88\% & 4 & 11.76\% & 11 & 32.35\% & 12 & 35.29\% & 4 & 11.76\% & 2.94\% \\ \hline
12 Math & 21 & 2 & 9.52\% & 1 & 4.76\% & 5 & 23.81\% & 6 & 28.57\% & 7 & 33.33\% & 0.00\% \\ \hline
3 SE & 15 & 0 & 0.00\% & 0 & 0.00\% & 3 & 20.00\% & 3 & 20.00\% & 8 & 53.33\% & 6.67\% \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Q28 result analysis result percentage distribution. Figure 6: Q26 result analysis result distribution. Figure 7: Q28 result analysis result distribution. A temporary conclusion can be made based on the answer distribution for the chosen questions, the age groups, and previous qualification and/or specialization matters for the statistical answer distribution and participant attitude. The background of the participants influences their expectations and behavior towards the LLM tools they were provided and had to work with. Students with additional specialization in art were the most motivated to complete the task compared to their peers. They formed the prompts carefully using an iterative approach until they were happy with the results. They were behaving in the most positive way out of all the participating groups. Students with additional specialization in mathematics were concise and less descriptive with their prompts, needing more iterations to reach a satisfactory result. They needed more individual discussions in order to overcome the frustrations created by their brevity. Students with additional specialization in entrepreneurship also had to modify their prompts, but were unhappy in the beginning, as most of them had already decided beforehand on their prompts and were not as malleable in their wording as their peers. The software engineering students recognized the value of the workshop and were happy with the overall experience, understanding how to use LLMs as tools. They behaved in the most calm and professional manner, compared to the younger participants.