# An Early Warning System to Detect At-Risk Students in Online Higher Education
## 6 Case Studies: Computer Fundamentals and Databases
### Performance of the Warning Level Classification
For CF, the p-value \(<\) 0.04 and, thus, we can reject the null hypothesis, the median of the final mark increases from 7.8 to 7.9, and the dropout decreases from 51% to 31% on the students who signed the consent. The results regarding retention and scoring are slightly better, but we cannot claim that they are only inferred from the utilization of the EWS, since difficulty on the activities may be different, and the percentages were computed based on students who signed. Those students are generally more engaged, and they tend to participate in pilots (i.e., self-selection bias). Related to DB, the p-value \(<\) 0.02 and we can also reject the null hypothesis, the median of the final mark increases from 7 to 7.6, and the dropout decreases from 26 to 17%. A similar claim to CF \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multicolumn{11}{c}{} & \multicolumn{11}{c}{**COMPUTE FUNDAMENTALS**} \\ \hline \multirow{3}{*}{**WL**} & \multicolumn{3}{c}{**AA1**} & \multicolumn{3}{c}{**AA2**} & \multicolumn{3}{c}{**AA3**} & \multicolumn{3}{c}{**AA4**} \\ \cline{2-11}  & **No.** & **Fail** & **Pass** & **No.** & **Fail** & **Pass** & **No.** & **Fail** & **Pass** & **No.** & **Fail** & **Pass** \\  & **(**c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** \\ \hline G & – & – & – & 200 & 25.5 & 74.5 & 194 & 19.6 & 80.4 & 188 & 15.4 & 84.6 \\ Y1 & 221 & 33.0 & 67.0 & – & – & – & – & – & – & – & – & – & – \\ Y2 & 52 & 78.8 & 21.1 & 33 & 63.6 & 36.4 & 9 & 66.7 & 33.3 & 9 & 66.7 & 33.3 \\ Y3 & – & – & – & – & – & – & – & – & – & – & – & – \\ R & 32 & 87.5 & 12.5 & 31 & 93.5 & 6.4 & 13 & 92.3 & 7.69 & 14 & 92.9 & 7.1 \\ B & 8 & 100 & – & 43 & 100 & – & 49 & 93.6 & 6.12 & 18 & 100 & – & \\ B2 & 0 & – & – & 6 & 100 & – & 48 & 100 & – & 84 & 100 & – & \\ \hline \multicolumn{11}{c}{} & \multicolumn{11}{c}{DATABASES} \\ \hline \multirow{3}{*}{**WL**} & \multicolumn{3}{c}{**AA1**} & \multicolumn{3}{c}{**AA2**} & \multicolumn{3}{c}{**AA3**} & \multicolumn{3}{c}{**AA4**} & \multicolumn{3}{c}{**AA5**} \\ \cline{2-11}  & **No.** & **Fail** & **Pass** & **No.** & **Fail** & **Pass** & **No.** & **Fail** & **Pass** & **No.** & **Fail** & **Pass** \\  & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** \\ \hline G & 55 & 21.8 & 78.2 & 49 & 10.2 & 89.8 & 47 & 6.3 & 93.6 & 46 & 6.5 & 93.5 & 54 & 13.0 & 87.04 \\ Y1 & – & – & – & – & – & – & – & – & – & – & – & – & – \\ Y2 & – & – & – & 2 & 100 & – & 2 & 50.0 & 50.0 & 4 & 50.0 & 50.0 & – & – & – \\ Y3 & 9 & 66.6 & 33.3 & – & – & – & – & – & – & – & – & – & – \\ R & – & – & – & 15 & 73.3 & 26.7 & 5 & 80.0 & 20.0 & 1 & 100 & – & 1 & – & 100 \\ B & 7 & 71.4 & 28.6 & 3 & 100 & – & 13 & 84.6 & 153 & 5 & 60.0 & 40.0 & – & – & – \\ B2 & – & – & – & 2 & 100 & – & 4 & 100 & – & 15 & 93.3 & 6.7 & 16 & 100 & – \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Performance of the warning level where _WL_ are the different warning levels defined in Figure 7, _No._ is the number of students identified in that risk, _Fail_ is the percentage of students identified in that risk that failed the course and _Pass_ is the percentage of students in that risk that passed the course. can be done. However, the difference is significantly better. This course does not have the variability in terms of marks that a first-year course has. The students have already done several courses in an online learning setting. Therefore, they know better how to self-regulate to pass the course compared to new students of a first-year course that do not have this prior experience.