# Insights from Learning Analytics for Hands-On Cloud Computing Labs in AWS
## 4 Insights from Data Analytics
### Statistical Overview  
First, we focus on the aggregated statistics of the students. With this aim, Table 1 shows the number of students (_COUNT_) that undertook the voluntary assessment test for each one of the seven modules of the course, together with the average mark on a 0-10 scale (_AVG_) and the standard deviation (_STD_). The same information is obtained for the final timed test (_CTOCA_). The last line (_DROP_) indicates the percentage of students that did not take the corresponding test with respect to the total population of students. The results indicate that 75.17% of the students took the final test, obtaining an average grade of 8.70 with a standard deviation of 1.05. The dropout rate of students with respect to the voluntary tests starts at 9.6%, which stands for the percentage of students that did not take the test after module 1, and increases throughout the different modules, up to a total 46.1% of students that did not take the test in module 7. Notice, though, that the dropout rate of students that did not perform the final test goes down to 24.8%, since students do not typically want to miss the opportunity to achieve the final course completion certificate. The rationale underlying this behavior may be two-fold. On the one hand, the students may be facing difficulties with keeping up with the amount of material of the course. Even if the course is self-paced, where students are provided with all of the material and the cloud environment required to perform all the activities at their own speed, a tentative schedule is suggested, though not enforced. The length of the course, which is planned for a four-month period (120 days), may impact the dropout rate of the students. Previous studies on attrition in online learning, such as the one carried out by [PERSON] and [PERSON] and [PERSON] (2018), indicated that shorter term length was a key variable affecting student attrition, since many students argue that time requirements represent a barrier to enroll in an online course. Table 2 shows statistics of the percentage progress of students with respect to each lab activity in the cloud, visually depicted in Figure 3. Notice that we provide average values that both include students that did not perform a specific lab activity (i.e., the percentage of progress is 0) and exclude them in order to focus, in this latter case, on students that carried out the lab activities. Indeed, as the course develops, the average percentage of progress for each lab activity decreases. The difference between the blue and red bars increases more towards the end of the course. This means that fewer people carry out these lab activities towards the end of the course, but those who do achieve a good percentage of progress and almost fulfill all the activities within each lab activity in the cloud. Note also the decrease in the number of students for certain lab activities (e.g., _DROP_ value for _PL_RDS_), showing the preference of students for the other lab activities. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**STAT** & **CTAM1** & **CTAM2** & **CTAM3** & **CTAM4** & **CTAM5** & **CTAM6** & **CTAM7** & **CTOCA** \\ \hline COUNT & 386 & 346 & 336 & 323 & 314 & 276 & 230 & 321 \\ AVG & 9.24 & 8.59 & 8.72 & 8.93 & 8.49 & 8.56 & 8.79 & 8.70 \\ STD & 0.97 & 1.32 & 1.36 & 1.25 & 1.51 & 1.49 & 1.58 & 1.05 \\ DROP (\%) & 9.6 & 19.0 & 21.3 & 24.4 & 26.5 & 35.4 & 46.1 & 24.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Statistical overview of the students’ results for the theoretical activities across three academic years (\(N=427\)). Notice that this information could not have been gathered and analyzed without using Cloud Trail-Tracker, thus highlighting the benefits of collecting educational analytics for cloud instruction using cloud techniques as well. The results indicate a similar behavior when compared to those obtained when carrying out the theoretical activities. However, the drop rate is substantially increased for the latest lab activities.