## 3 Results
### Variation Ranges for the \(Madm_{m}\), \(Ci_{m}\), and \(\beta_{m}\) Indicators
The generality of the method allows for choosing them differently provided they satisfy the conditions specified by Equation (96). In turn, Table 5 gives upper bounds (UBs) and lower bounds (LBs) for the variation ranges of the Complexity Pointer (\(CP_{M}\). ), Consistency Index (\(CI_{M}\)), and Efficiency Index (\(\beta_{M}\)) (cf. Equations (95), (100) and (101)). These are calculated by setting \(\theta=0.13\) and \(\rho=1.0\) (cf. Inequality (99)). Table 6 presents values of indicators for Mean Absolute Deviation (\(MAD_{M}\)), Complexity (\(CP_{M}\)), Consistency (\(CI_{M}\)), and Efficiency (\(\beta_{M}\)) associated with the analyzed grading methods (cf. Equations (106), (95), (100), and (101)). Finally, Table 7 reports the standard errors linked to the indicators of Agreement \((MAD_{M})\), Consistency (\(CI_{M}\)), and Efficiency (\(\beta_{M}\)) for the four grading methods analyzed. These values, obtained from simulation processes, offer insight into the statistical precision and reliability of each metric. Smaller standard errors reflect higher stability and reduced variability across simulation runs. According to present exploration, among the methods, ST showed the least variability in the \(MAD_{M}\) indicator, suggesting higher precision in that dimension. The Summative approach achieved low standard errors for \(CI_{M}\) and \(\beta_{M}\). Conversely, the ST-FIS method showed the greatest variability across all indicators, pointing to lower statistical robustness. Nevertheless, despite these differences, the variations in standard error values were minimal and did not significantly affect the overall comparative assessment of the methods. Figure 1 depicts the variation of \(CI_{M}\) (Figure 1a) and \(\beta_{M}\) (Figure 1b) when each one of these indicators are set as a function of the \(MAD_{M}\) index while keeping the complexity pointer \(CP_{M}\) holding different fixed values. \begin{table}
\begin{tabular}{c c c c c} \hline  & \(MAD_{M}\) & \(CP_{M}\) & \(CI_{M}\) & \(\beta_{M}\) \\ \hline Summative & 0.11 & 0.23 & 1.20 & 0.20 \\ Rubric & 0.13 & 0.61 & 1.54 & 0.52 \\ ST & 0.07 & 0.79 & 1.73 & 0.71 \\ ST-FIS & 0.06 & 0.96 & 1.91 & 0.88 \\ \hline \end{tabular}
\end{table} 
Table 6: Indicators for Mean Absolute Deviation (\(MAD_{M}\)), Complexity (\(CP_{M}\)), Consistency (\(CI_{M}\)), and Efficiency (\(\beta_{M}\)) associated with the analyzed grading methods (cf. Equations (106), (95), (100), and (101)). \begin{table}
\begin{tabular}{c c c} \hline \(\mathbf{N_{M}\text{ (min)}}\) & \(\mathbf{E_{M}\text{ (min)}}\) & \(\mathbf{Q_{M}\text{ (min)}}\) \\ \hline
3.00 & 15.00 & 19.00 \\ \hline \(\mathbf{N_{M}\text{ (Max)}}\) & \(\mathbf{E_{M}\text{ (Max)}}\) & \(\mathbf{Q_{M}\text{ (max)}}\) \\ \hline
13 & 112 & 60 \\ \hline \end{tabular}
\end{table} 
Table 2: Minimum and maximum values for \(N_{M}\), \(E_{M}\) and \(Q_{M}\) entries across the addressed methods. \begin{table}
\begin{tabular}{c c c c} \hline \(\mathbf{a}\) & \(\mathbf{b}\) & \(\mathbf{c}\) & \(\mathbf{\theta}\) & \(\mathbf{\rho}\) \\ \hline Summative & 0.23 & 0.13 & 0.31 \\ Rubric & 0.46 & 0.41 & 1.00 \\ ST & 0.61 & 1.00 & 0.80 \\ ST-FIS & 1.00 & 0.98 & 0.88 \\ \hline \end{tabular}
\end{table} 
Table 4: Weighting coefficients \(a,b,c\) reflecting the relative importance of factors \(N_{M}\), \(E_{M}\), and \(Q_{M}\), respectively, in the determination of the complexity pointer \(CP_{M}\). Scaling parameters \(\theta\) and \(\rho\) for normalized–pondered values \(PN(N_{M})\), \(PE(E_{M})\) and \(PQ(Q_{M})\) (cf. Equation (96) and Inequality (99)). \begin{table}
\begin{tabular}{c c c c} \hline \(\mathbf{a}\) & \(\mathbf{b}\) & \(\mathbf{c}\) & \(\mathbf{\theta}\) & \(\mathbf{\rho}\) \\ \hline Summative & 0.23 & 0.13 & 0.31 \\ Rubric & 0.46 & 0.41 & 1.00 \\ ST & 0.61 & 1.00 & 0.80 \\ ST-FIS & 1.00 & 0.98 & 0.88 \\ \hline \end{tabular}
\end{table} 
Table 4: Weighting coefficients \(a,b,c\) reflecting the relative importance of factors \(N_{M}\), \(E_{M}\), and \(Q_{M}\), respectively, in the determination of the complexity pointer \(CP_{M}\).