## 4 Experiments and Results
### Correlation Between Student Clusters and Performance
While the feature importance analysis does not indicate a high predictive value for forum participation, Figure 13 reveals that clusters with fewer students and higher weighted averages tend to exhibit greater engagement in forum discussions, suggesting that students in these high-performing clusters actively seek help, clarifying doubts, discussing concepts, and leveraging peer interactions to enhance their understanding. Notably, many of their messages demonstrate continuity within discussions, indicating that they initiate and sustain engagement by responding to peers, following up on advisors' answers, and contributing to ongoing conversations. This behavior aligns with SRL strategies, particularly the help-seeking dimension, which [PERSON] [33] identifies as a key component of effective self-regulation. Rather than passively struggling with difficulties, these students actively approach their learning by reaching out to peers or instructors, demonstrating metacognitive awareness of their  
Figure 13: Students’ forum participation cluster at different \(\text{CWA}_{U}\) thresholds. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**CWA\({}_{U}\)**} & \multirow{2}{*}{**Feature**} & \multicolumn{3}{c}{\(\mu\pm\sigma\)} \\ \cline{3-5}  & & **Cluster 1** & **Cluster 2** & **Cluster 3** \\ \hline \multirow{2}{*}{20\%} & Weighted Average & 3.72 \(\pm\) 1.18 & 4.00 \(\pm\) 0.83 & 4.05 \(\pm\) 0.82 \\  & Linearity Score & 0.58 \(\pm\) 0.28 & 0.43 \(\pm\) 0.28 & 0.39 \(\pm\) 0.36 \\ \hline \multirow{2}{*}{40\%} & Weighted Average & 3.78 \(\pm\) 0.97 & 4.03 \(\pm\) 0.98 & 4.10 \(\pm\) 0.54 \\  & Linearity Score & 0.65 \(\pm\) 0.33 & 0.58 \(\pm\) 0.27 & 0.30 \(\pm\) 0.25 \\ \hline \multirow{2}{*}{60\%} & Weighted Average & 3.83 \(\pm\) 0.96 & 3.95 \(\pm\) 0.60 & 4.11 \(\pm\) 0.91 \\  & Linearity Score & 0.66 \(\pm\) 0.31 & 0.37 \(\pm\) 0.30 & 0.59 \(\pm\) 0.27 \\ \hline \multirow{2}{*}{80\%} & Weighted Average & 3.84 \(\pm\) 0.97 & 3.97 \(\pm\) 0.58 & 4.19 \(\pm\) 0.86 \\  & Linearity Score & 0.67 \(\pm\) 0.30 & 0.37 \(\pm\) 0.30 & 0.59 \(\pm\) 0.28 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Weighted Average and Linearity Score comparison (\(\mu\pm\sigma\)) values per cluster, for the four different \(\text{CWA}_{U}\) thresholds (20%, 40%, 60% and 80%). knowledge gaps and a willingness to use available resources to overcome challenges. In online learning environments, research has shown that students who engage in interactive, feedback-driven learning, such as forum discussions, tend to develop deeper conceptual understanding and achieve better academic outcomes [34]. Furthermore, help-seeking in online learning environments is an indicator of self-directed learning, where students navigate their educational journey by combining independent study with strategic social interactions. The findings suggest that while forum participation alone may not directly predict performance for all students, it plays a crucial role for those who exhibit a high degree of self-regulated learning behaviors. Therefore, encouraging structured peer discussions and fostering a collaborative learning culture could benefit students who actively engage in self-regulation strategies.