## 4 Results
### IPA User Survey Results  
The purpose of using Importance-Performance Analysis (IPA) in this study was to assess user satisfaction with the LoRA model-generated paper-cutting patterns and to verify whether the model contributes to the dissemination and promotion of Chinese intangible cultural heritage paper-cutting. The survey was conducted in November, with 321 questionnaires distributed and 297 valid responses collected, achieving a response rate of 92.52%. For the 57 participants who could not attend in person, they were asked to avoid late nights and be in a focused state before completing the experiment and survey remotely, as provided by the researchers. After using the provided remote method to generate paper-cutting patterns, participants filled out an online questionnaire to provide feedback on their experience. If a participant's device or environment was not compatible with the software installation, the researchers offered support through remote control software, such as TeamViewer, allowing participants to use the researchers' remote devices to ensure the survey was completed smoothly. The reliability and validity of the importance and satisfaction indicators in the questionnaire were tested using SPSS 25.0. The KMO sample value for satisfaction was 0.869, and [PERSON]'s sphericity test value was 0.000; the KMO sample value for importance was 0.914, with the same [PERSON]'s sphericity test value of 0.000. Both KMO values were greater than 0.8, indicating good validity of the questionnaire. Additionally, in the reliability analysis, the consistency of the 14 items was tested, with [PERSON]'s alpha coefficient for satisfaction at 0.796 and for importance at 0.964. Both alpha values exceeded 0.7, indicating good reliability of the questionnaire. During the survey, participants were informed of the research objectives and the usage of the model, with explanations provided regarding the LoRA model, paper-cutting culture, and related concepts. The demographic information of the 52 respondents is summarized below, as shown in Table 10. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Variable** & **Category** & **Frequency** & **Percentage** \\ \hline \multirow{2}{*}{Gender} & Male & 120 & 40.4\% \\  & Female & 177 & 59.5\% \\ \hline \multirow{4}{*}{Age} & 18–24 years & 90 & 30.3\% \\  & 25–34 years & 86 & 28.9\% \\  & 35–44 years & 80 & 26.9\% \\  & 45–64 years & 41 & 13.8\% \\ \hline \multirow{4}{*}{Occupation} & Undergraduate student & 90 & 30.3\% \\  & Master’s student & 53 & 17.8\% \\ \cline{1-1}  & Ph.D. student & 47 & 15.8\% \\ \cline{1-1}  & University lecturer & 35 & 11.7\% \\ \cline{1-1}  & Intangible cultural heritage & 72 & 24.2\% \\ \hline \multirow{4}{*}{Major} & Design & 98 & 32.9\% \\ \cline{1-1}  & Fine arts & 81 & 27.2\% \\ \cline{1-1}  & Cultural communication & 45 & 15.1\% \\ \cline{1-1}  & Intangible cultural heritage & 73 & 24.5\% \\ \cline{1-1}  & preservation & & \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Demographic information. The data were analyzed using SPSS 27.0, and the average values of user satisfaction and importance for each factor were calculated to construct the IPA (Importance-Performance Analysis) graph. As shown in Figure 5, the average satisfaction score was 3.68, and the average importance score was 4.10. The analysis divided the elements into four quadrants: \"Strengths\", \"Maintain\", \"Opportunities\", and \"Improvements\". Based on the satisfaction-importance analysis, as shown in Figure 5, the distribution of elements in the four quadrants is as follows:  
1. First Quadrant (Strengths)  
Factors in the \"Strengths\" quadrant are those with high user satisfaction and high importance, indicating that these features have been widely recognized by users and should be maintained and further optimized. Specifically, these include the following: 7. The LoRA model saves time and effort (PE3), 10. The LoRA model improves design efficiency (PU3), and 11. The LoRA model enhances the dissemination of paper-cutting culture (PU4). 2.