# Key Quality Factors in Digital Competence Assessment: A Validation Study from Teachers' Perspective
## 3 Results
### Key Quality Factors of the Competence Assessment Model
#### 3.2.2 Factor Analysis Results  
The factor analysis revealed the existence of four factors (see Table 6) which explain 65.77% of the total variance. The factors that emerged from the analysis are (KQF1) efficiency in time, student tracking, support and assessment (73.3% of the model); (KQF2) fairness and cognitive complexity (13.3%); (KQF3) meaningfulness and authenticity (7.6%) and (KQF4) reproducibility and transparency (6%). From the teachers' perspective, the most important quality factor is (KQF1) a combination of efficiency in time, student tracking and support, and assessment (Table 7). This first KQF is also very consistent, as in many CFA it appears with the same composition. It consists of a combination of items that are included in the costs and efficiency (CE), educational consequences (E), reproducibility of decisions (R), transparency (T) and fairness (F) QC. Specifically, it emerges that teachers consider a series of elements as part of a unique quality factor. These elements enable the tracking of the students' progress more accurately than other methods, the student engagement and the detection of underperforming cases. Similarly, it increases teachers' capacity for assessment, including additional assessments, while providing better feedback and greater accuracy. Additionally, the CAM allows teachers to provide clear evaluation criteria to students and enhance teaching effectiveness. All in all, these elements focus on efficient procedures and their positive educational impact. The other three KQC are consistent enough to be taken into account. KQF2 (13.28% of the final model) is mainly a combination of two items: fairness and cognitive complexity. It focuses on the way assessment instruments support consistent scoring among all the students, ensure unbiased results and implement activities coherent with what is being assessed. It also includes the capacity of the CAM to track students' reasoning, to enable them to advance according to their level and to increase awareness through the feedback received. In sum, this factor addresses the assessment consistency and reliability but also the scaffold of learning. KQF3 (7.54% of the final model), named'meaningfulness and authenticity', concerns the engagement of students in situations that are relevant and familiar through the CAS and the integration of the components of the DC. As such, this factor is linked to the concept of meaningful learning. \begin{table}
\begin{tabular}{l l l l l l} \hline \hline  & & \multicolumn{3}{c}{**Extraction Sums of Squared Loadings**} & \multicolumn{1}{c}{**Final Model \%**} \\ \cline{3-6}  & & **Total** & **\% of Variance** & **Cumulative \%** & \\ \hline KQF1 & Efficiency in time, student tracking and support, & 12.046 & 48.183 & 48.183 & 73.257 \\  & and assessment & 2.184 & 8.737 & 56.920 & 13.284 \\ KQF2 & Fairness, and cognitive complexity & 1.241 & 4.964 & 61.884 & 7.547 \\ KQF4 & Reproducibility and transparency & 0.972 & 3.889 & 65.773 & 5.912 \\ \hline TOTAL & & 16.443 & 65.773 & & 100.000 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: KQF identified and related variance. \begin{table}
\begin{tabular}{l l} \hline \hline  & **Result** \\ \hline Determinant & 0.0000 \\ KMO & 0.951 \\ Chi2 & 6382.569 \\ [PERSON]’s test & Df & 300 \\ Sig. & 0.000 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: KMO and [PERSON]’s test of sphericity. Finally, KQF4, named'reproducibility and transparency' (5.91% of the total model), although explaining a lesser variance than the other factors, has to be considered independent and reflecting a specific identity. It highlights how the model provides clear information about the students' progress and the assessment results, and reliable outcomes based on multiple assessment occasions and instruments. For a better understanding of the KQF, it is also useful to observe the distribution of the original QC into factors (see Figure 2). Some of them are completely included in one factor while others are divided into two or three.