## 5 Results
### Relationship Between Usage Frequency and Performance  
To examine the relationship between ITS-CAL usage and student performance, we conducted a multiple linear regression analysis with exam performance as the dependent variable and ITS-CAL usage metrics (hint usage, debugging frequency, and question-asking frequency) as independent variables. The regression model was statistically significant (\(F\) (3, 32) = 154.026, \(p\) < 0.05), with an R\({}^{2}\) value of 0.935, indicating that 93.5% of the variance in student performance could be explained by ITS-CAL usage. These results suggest that ITS-CAL usage had a positive association with exam performance. Secondly, the relationship between usage frequency and test scores was analyzed, as shown in Table 6. The results reveal distinct patterns. Students who did not use ITS-CAL had an average pass rate of 56.77%. Among them, high-knowledge students achieved a 100% pass rate, medium-knowledge students had a pass rate of 50.83%, and low-knowledge students failed entirely. This indicates that high-knowledge students could perform well without ITS-CAL, whereas medium- and low-knowledge students had a greater dependency on the system. Moderate usage (e.g., 2 times) correlated with the highest average pass rate of 72.22%, with high-knowledge students maintaining a 100% pass rate and low-knowledge students achieving a pass rate of 16.67%. This suggests that moderate ITS-CAL use effectively supports learning, particularly for medium-knowledge students, by compensating for their limited problem-solving abilities. Excessive usage (e.g., 4 times) led to a significant decline in performance, with an average pass rate of 27.98%. Notably, the pass rate for high-knowledge students dropped to 0%, while medium-knowledge students achieved 47.92% and low-knowledge students dropped to 2.08%. This indicates that over-reliance on the system may impair independent problem-solving abilities. When the total number of uses exceeded 10 times, the average pass rate declined further to 16.67% or lower. For students with 15 or more uses, the pass rate fell to 4.17%, predominantly in the low-knowledge group. This suggests that excessive reliance on ITS-CAL without effective problem-solving strategies may result in poor learning outcomes. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Total Number of Times Used**} & \multirow{2}{*}{**Average Pass**} & \multicolumn{3}{c}{**Knowledge Level Distribution**} \\  & & \multicolumn{3}{c}{**(Number of People/Pass Rate)**} \\ \cline{3-5}  & & **High** & **Medium** & **Low** \\ \hline
0 & 56.77\% & 2/100.00\% & 5/50.83\% & 1/0.00\% \\ \hline
2 & 72.22\% & 2/100.00\% & & 1/16.67\% \\ \hline
3 & 35.42\% & 1/100.00\% & 4/28.13\% & 1/0.00\% \\ \hline
4 & 27.98\%  
From a knowledge level perspective, high-knowledge students consistently maintained high pass rates, regardless of ITS-CAL usage, demonstrating their ability to tackle challenges independently. Medium-knowledge students showed a positive correlation between moderate ITS-CAL usage and improved performance, indicating that the system provided meaningful support. In contrast, low-knowledge students exhibited low pass rates across all usage levels, reflecting a need for additional support beyond ITS-CAL to improve their learning outcomes. To determine whether the differences in performance among students with different knowledge levels were statistically significant, a one-way ANOVA was conducted to assess differences in exam performance among low-, medium-, and high-knowledge students. The results indicated a statistically significant difference among groups (\(F\) (2, 33) = 8.313, \(p\) < 0.05, \(\eta^{2}\) = 0.335), suggesting that the knowledge level had a significant impact on student performance. Post hoc Tukey's HSD tests further revealed that high-knowledge students performed significantly better than medium- and low-knowledge students (\(p\) < 0.05). Medium-knowledge students outperformed low-knowledge students (\(p\) < 0.05).