## 4 Results
### Analysis of Enhancing Question Diversity
#### 4.3.5 Quality Analysis of Higher-Order Thinking Questions  
We specifically focused on the three higher-order thinking levels: analysis, evaluation, and creation. Table 13 presents the mean scores and standard deviations for these three levels across the different generation methods.  
We conducted univariate ANOVAs for the analysis, evaluation, and creation levels separately, with results shown in Table 14. The findings are as follows: (1) At the analysis level, there is no significant difference between the three generation methods (F(2, 87) = 2.14, \(p\) = 0.123, partial \(\eta^{2}\) = 0.04). This indicates that Multi-Examiner performs similarly to GPT-4 and human-generated methods when generating questions at the analysis level. (2) At the evaluation level, the generation method has a significant impact on question quality (F(2, 87) = 4.27, \(p\) = 0.017, partial \(\eta^{2}\) = 0.07). The effect size is medium, suggesting that there are substantial differences in the quality of questions generated by different methods at this level. (3) At the creation level, the impact of the generation method is most significant (F(2, 87) = 6.89, \(p\) = 0.002, partial \(\eta^{2}\) = 0.10). This is a medium-to-large effect size, indicating  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Generation Method** & **Analysis (M \(\pm\) SD)** & **Evaluation (M \(\pm\) SD)** & **Creation (M \(\pm\) SD)** \\ \hline Multi-Examiner & 2.97 \(\pm\) 0.99 & 3.08 \(\pm\) 0.94 & 2.80 \(\pm\) 0.96 \\ GPT-4 & 2.13 \(\pm\) 1.01 & 2.12 \(\pm\) 1.08 & 2.27 \(\pm\) 1.11 \\ Human & 3.34 \(\pm\) 0.91 & 3.43 \(\pm\) 0.96 & 3.67 \(\pm\) 1.03 \\ \hline \hline \end{tabular}
\end{table}
Table 13: Quality scores for analysis, evaluation, and creation levels.  
Figure 8: Interaction effect graph of generation methods and cognitive levels.  
that at the highest cognitive level, the generation method has the greatest influence on question quality.  
To further explore the differences between groups, we conducted [PERSON]'s HSD post-hoc tests for the evaluation and creation levels, with the results shown in Table 15. From these analyses, we can draw the following conclusions: (1) Multi-Examiner performs exceptionally well in generating higher-order thinking questions, particularly at the evaluation and creation levels. Its performance is significantly better than GPT-4 and close to the level of human-generated questions. (2) At the analysis level, there are no significant differences between the three methods, which may indicate that automated methods have reached a level comparable to human performance at this stage. (3) As the cognitive levels increase (from analysis to evaluation and then to creation), the differences between generation methods grow, reflecting the challenge of generating questions that require higher-order thinking skills. (4) GPT-4 shows clear limitations in generating higher-order thinking questions, particularly at the creation level, highlighting the importance of incorporating additional structured information, such as KGs. (5) The performance of Multi-Examiner at the evaluation and creation levels shows no significant difference from that of human-generated questions, indicating that the system has strong potential in generating high-quality, higher-order thinking questions.