## 3 Results
### Variation Ranges for the \(Madm_{m}\), \(Ci_{m}\), and \(\beta_{m}\) Indicators
(2) A moderate consistency range sustained through \(1<CI_{M}\leq 3/2\) (\(M\) shows acceptable consistency, but it could be improved). (3) A high consistency range tied to the condition \(3/2<CI_{M}\leq 2\) (\(M\) provides a reliable grading output). The \(\beta_{M}\) index rates a method \(M\)'s efficiency by measuring how consistently it performs relative to its complexity. Certainly, a high value of \(\beta_{M}\) indicates that the grading method maintains high consistency despite its complexity, meaning it efficiently balances fairness and structure. Likewise, a low value of \(\beta_{M}\) suggests that the grading method is either too complex for its level of consistency or too inconsistent in relation to its complexity. Relating to the variation of \(\beta_{M}\), we ought to consider several key cases. (1) Whenever \(CP_{M}\) is high, a low \(\beta_{M}\) value means that the grading method is unnecessarily complex relative to its ability to assign stable grades. Conversely, a high \(\beta_{M}\) value could signal that despite high complexity, the grading method is very consistent, which may justify the complexity. (2) If \(CP_{M}\) is very low, a high value of \(\beta_{M}\), may suggest that the grading method is efficient; in other words, it achieves strong consistency with minimal complexity. Furthermore, a low value of \(\beta_{M}\) at low \(CP_{M}\), would indicate that perhaps due to its simplicity, the grading method still lacks consistency, meaning it might need better-defined criteria. Accordingly, if two grading methods have similar \(CI_{M}\) values, the one entailing a higher value of \(\beta_{M}\) is the more efficient one, as it achieves similar consistency with less complexity. Moreover, \(\beta_{M}\) sustains the identification of overly complex methods, as a very low value of this ratio suggests that the complexity added to the grading system does not significantly improve its consistency, meaning the method might be unnecessarily convoluted. We can expand on the \(\beta_{M}\)-based comparison criterion by suggesting a threshold-based ranking approach. This provides a structured approach to further categorizing methods based on their efficiency. We propose arranging the following benchmark thresholds: (1) One for inefficiency associated with a condition \(\beta_{M}\leq 1/6\) (where the method is either highly inconsistent or extremely complex, necessitating a significant adjustment). (2) A low efficiency range \(1/6<\beta_{M}\leq 2/6\) (the method battles with consistency or exhibits unnecessary complexity; enhancement is needed). (3) A moderate efficiency range \(2/6\leq\beta_{M}\leq 3/6\) (the method is reasonably fair, but optimizing complexity or consistency could be necessary). (4) A highly efficient domain \(\beta_{M}>3/6\) (the grading method achieves strong consistency with reasonable complexity). Calculations Related to \(Md_{m}\), \(C_{l}\) and \(\beta_{m}\) Indicators Based on Simulated Grade Data and Pondered-Normalized Complexity Pointer \(Cp_{m}\) Values  
The results of the subsequent analysis are available in Tables 1-7. Table 1 displays the Components (\(N_{M}\)), Elements (\(E_{M}\)), and Operations (\(Q_{M}\)) for the different methods considered in this study (M stands for Summative, Rubric, ST, and ST-FIS). Table 2 presents the Minimum and Maximum values for \(N_{M}\), \(E_{M}\) and \(Q_{M}\) entries across the addressed methods. Table 3 includes the pondered-normalized values for Components (\(PN(N_{M})\)), Elements (\(PE(E_{M})\)), and Operations (\(PQ(Q_{M})\)). These items were obtained by using Equations (89)-(91). Table 4 gives the values of the pondering-normalizing parameters \(\theta\) and \(\rho\) (cf. Inequality (99)). It also sets values for the 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 \(CP_{M}\) (cf. Equation (95). Parameter values \(a,b,c\), in this table were chosen as an illustrative device.