## 5 Results
In particular, the R-squared (\(R^{2}\)) and the mean squared error (MSE) values were calculated. \(R^{2}\) provides values between 0 and 1, where higher values are better; MSE provides non-negative values where 0 is the smallest value, where a lower value is better. The study also evaluated whether distributi  
Figure 1: Average classification of the CHAEA results for each branch of knowledge. \begin{table}
\begin{tabular}{l|c c c c} \hline
**Course** & **Active** & **Reflector** & **Theorist** & **Pragmatist** \\ \hline ExpBio-Bioche-2223 & \(3.00\pm 1.31\) & \(\mathbf{3.53\pm 0.99}\) & \(3.47\pm 1.19\) & \(2.47\pm 1.25\) \\ ExpBio-Bioche-2324 & \(2.89\pm 1.20\) & \(3.16\pm 1.12\) & \(\mathbf{3.84\pm 0.90}\) & \(2.84\pm 1.17\) \\ PlaNut-Bioche-2223 & \(3.00\pm 1.17\) & \(3.65\pm 1.17\) & \(\mathbf{3.94\pm 1.09}\) & \(2.65\pm 0.93\) \\ PlaNut-Bioche-2324 & \(2.50\pm 2.12\) & \(1.50\pm 0.71\) & \(\mathbf{4.50\pm 0.71}\) & \(2.50\pm 0.71\) \\ StrFun-Cell-2223 & \(2.53\pm 1.13\) & \(\mathbf{3.47\pm 0.92}\) & \(3.40\pm 0.99\) & \(2.80\pm 0.86\) \\ StrFun-Cell-2324 & \(4.00\pm 0.00\) & \(4.00\pm 0.00\) & \(\mathbf{5.00\pm 0.00}\) & \(3.00\pm 0.00\) \\ Health-Deep-2223 & \(3.33\pm 1.39\) & \(3.19\pm 0.93\) & \(\mathbf{3.62\pm 0.86}\) & \(3.05\pm 0.92\) \\ LanDev-Speech-2324 & \(\mathbf{4.33\pm 0.87}\) & \(2.67\pm 1.22\) & \(3.67\pm 0.87\) & \(3.22\pm 0.83\) \\ ChiDis-Speech-2223 & \(3.67\pm 1.07\) & \(3.00\pm 0.60\) & \(\mathbf{4.08\pm 1.00}\) & \(3.00\pm 0.85\) \\ ComLan-Primary-2324 & \(3.87\pm 1.06\) & \(3.39\pm 0.89\) & \(\mathbf{4.26\pm 0.86}\) & \(3.04\pm 0.37\) \\ InfCom-Physio-2324 & \(3.75\pm 1.28\) & \(3.50\pm 1.31\) & \(\mathbf{4.38\pm 0.74}\) & \(3.38\pm 0.74\) \\ InfPhys-Health-2223 & \(3.94\pm 1.26\) & \(2.78\pm 1.11\) & \(\mathbf{4.11\pm 0.96}\) & \(3.67\pm 0.84\) \\ ComTec-Software-2223 & \(3.00\pm 1.26\) & \(2.90\pm 1.25\) & \(\mathbf{3.55\pm 1.32}\) & \(2.85\pm 1.04\) \\ ComTec-Software-2324 & \(3.00\pm 1.32\) & \(3.00\pm 1.32\) & \(\mathbf{3.78\pm 1.20}\) & \(3.67\pm 1.32\) \\ IntSys-Computer-2223 & \(3.10\pm 1.33\) & \(3.45\pm 1.10\) & \(\mathbf{3.85\pm 0.93}\) & \(3.10\pm 1.25\) \\ TheAut-Computer-2223 & \(3.24\pm 1.22\) & \(3.05\pm 1.09\) & \(\mathbf{3.74\pm 0.95}\) & \(3.08\pm 1.08\) \\ TheAut-Computer-2324 & \(3.40\pm 1.04\) & \(3.30\pm 1.15\) & \(\mathbf{3.63\pm 1.03}\) & \(3.03\pm 1.19\) \\ ProPla-Computer-2223 & \(3.09\pm 1.45\) & \(3.45\pm 1.44\) & \(\mathbf{4.18\pm 0.98}\) & \(3.36\pm 0.67\) \\ ProPla-Computer-2324 & \(3.25\pm 1.16\) & \(2.88\pm 1.13\) & \(\mathbf{3.38\pm 1.19}\) & \(2.88\pm 0.99\) \\ \hline DMA-2224 & \(3.29\pm 1.25\) & \(3.21\pm 1.11\) & \(\mathbf{3.82\pm 1.01}\) & \(3.03\pm 1.01\) \\ \hline \end{tabular}
\end{table} 
Table 5: Average CHAEA level for each learning style and course. Best results are highlighted in bold. marks by scores or using levels is more suitable. Only courses with at least ten responses were considered for the correlation analysis to avoid unreliable estimates. Tables 6-9 present the performances of the computed linear regression models for each learning style, along with their distribution by scores or levels. The results are highly varied: there are courses where linear regression does not apply due to an insufficient number of respondents (e.g., PlaNut-Bioche-2324 and StrFun-CellMol-2324), courses where the regressors yield very low performance (for example, TheAut-Computer-2223), courses where certain grade distributions perform better as regressors (for example, ProPla-Computer-2223 shows higher performances when grades are distributed by levels), and courses where the regressor for a certain style achieves higher performances than the remaining styles, regardless of whether the marks are distributed by score or level (for example, the pragmatist style in ComLan-Primary-2324). the reverse situation: non-respondent students achieved higher marks than participants. Overall, the grades are good, with no failing students.