# A Domain-Driven Framework to Analyze Learning Dynamics in MOOCs through Event Abstraction
## 5 Case Study: Successful Student Sessions in Coursera
### Case Study & Framework
_Cluster 2_ groups about 6% of the instances, however the events in it account for 20.12% of the total events in the log. This cluster is distinguished by longer sessions (about 108 minutes) and a larger number of activities per session (an average of 8.267 each). In this instance, four dynamics had high z-scores: Assessing (0.315), Exploring (0.518), Echoing (1.509), and Fetching (1.42), with the latter two having the highest scores for their respective activity. It is worth noting that in this situation, the majority of the sessions grouped belong to the middle of the course, with the bulk of them falling into the second quintile (25.75%), third quintile (21.84%), and fourth quintile (19.77%). Sessions in this cluster tend to occur less frequently in initial sessions (17.01%) and final sessions (15.63%). The high z-score of activities involving content repetition, paired with their location in the middle of the course, may imply that these sessions represent an active effort by the student to overcome some barrier, such as learning a new subject or overcoming the difficulty of an assessment. _Cluster 3_ makes up 0.5% of all cases and 4.85% of all events. These sessions correspond to long-duration sessions that generally revolve around many interactions between the Retaking and Skimming activities, with the appearance of one of the other 5 learning dynamics in certain cases. As in Cluster 2, the sessions in this scenario take place mostly in the middle of the courseThis is due to 36.36% occurring in the second quintile, 27.27% in the third quintile, and 18.18% in the fourth quintile. With only five cases at the beginning (15.15%) and one at the end of the course. Figure 10: Sessions at the end of the course or at the fifth quintile. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Cluster** & **N\({}^{\circ}\) of Sessions** & **Percentage** & \
\begin{tabular}{c} **Average Time** \\ **(Minutes)** \\ \end{tabular} &
\begin{tabular}{c} **Average** \\ **Activities** \\ \end{tabular} \\ \hline Cluster 1 & 5288 & 74.6\% & 19.4 & 1.4 \\ Cluster 2 & 435 & 6.1\% & 108.9 & 8.2 \\ Cluster 3 & 33 & 0.5\% & 163.5 & 26.2 \\ Cluster 4 & 1329 & 18.8\% & 93.8 & 4.42 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Cluster statistics. _Cluster 4_ is the second largest cluster in terms of size, accounting for 18.88% of all sessions and 33.89% of the events in the high-level event log. The z-score of the progressing activity in this cluster is the highest in the sample, at 1.692. This means that this cluster identifies sessions in which the learner is progressing sequentially and thoroughly following the course program. This is supported by the fact that the Assessing activity, that is, performing assessments for the first time, also had the highest Z-score in the sample at this point, with a value of 1.500. When the distribution of sessions is compared to the quintiles of course progression where they are situated, the majority of the sessions in this cluster appear at the start of the course (31.45%). Then, as the course progresses, the number of sessions of this type gradually decreases, with only 9.17% of them coming from the course's final quintile. The fact that only 4.42 activities are seen on average during each of these sessions, which last an average of 93.8 minutes, is also interesting to note. This could indicate an intention to advance through the course, taking into account both assessments and video lectures, in order to successfully complete it.