## 4 Dataset Description  
The dataset used in the research was provided by the Hellenic Open University and comprised records of 1073 students who attended the 'Introduction to Informatics' module of the 'Computer Science' course during the academic year 2013-2014. These records were collected from three different sources, the course database, the teachers, and the course LMS, thus producing three distinct sets of attributes (Figure 2):  
* The demographic set \(\text{S}_{1}=\{\text{Gender, NewStudent}\}\) (Table 1). The distribution of male and female students was 76.5% and 23.5%, respectively. In addition, 87.5% of the students had enrolled in the course for the first time, while the rest failed to pass the previous year's final exams. * The academic performance set \(\text{S}_{2}=\{\text{Ocs}_{i},\text{Wri}_{i}\}_{i=1}^{2}\) (Table 2). The attribute named \(\text{Ocs}_{i}\) refers to students' absence or presence in the i-th optional contact session, while the attribute named \(\text{Wri}_{i}\) represents students' grades (ten-point grading scale) in the i-th written assignment, i \(\in\{1,2\}\). Four written assignments should be submitted during the academic year, while a total sum \(\sum_{i=1}^{4}\text{Wri}_{i}\geq 20\) was required for a student to undertake the final exam. * The LMS activity set \(\text{S}_{3}=\{\text{L}_{i},\text{V}_{1i},\text{V}_{2i},\text{V}_{3i},\text{ V}_{4i},\text{V}_{5i},\text{P}_{1i},\text{P}_{2i},\text{P}_{3i},\text{P}_{4i}\}_{i=1}^{2}\) (Table 3). These attributes monitor student activity on the online LMS course (i.e., logins, views, and posts). \begin{table}
\begin{tabular}{c c c} \hline \hline
**Attribute Name** & **Description** & **Values** \\ \hline Gender & Student gender & male, female \\ New Student & A student enrolled in the course for the first time & yes, no \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Demographic attributes. Each instance of the dataset represents a single student (Figure 2) and is described by a vector of attributes, such as \(x=(s_{1},s_{2},s_{3})\), where \(s_{1},s_{2},s_{3}\) correspond to the vector attributes of \(\mathsf{S}_{1}\), \(\mathsf{S}_{2}\), \(\mathsf{S}_{3}\) sets, respectively. Since the early prognosis of students at risk of failure is of utmost importance for higher education institutions, the academic year was divided into four time-periods according to each written assignment submission deadline (Figure 3). To this end, the notation \(\mathsf{V}_{\text{1i}}\) denotes the total number of student views in the pseudo-code forum in the i-th period, \(\mathsf{i}\in\{1,2\}\), and so forth. For example, attribute \(\mathsf{P}_{\text{21}}\) refers to the total number of student posts in the compiler forum in the first time-period (i.e., from the beginning of the academic year until the first written assignment submission deadline). Finally, the output attribute \(y\in[0,10]\) represents the grade of students in the final examinations of the course. Note that we examine two distinct scenarios, corresponding to the first one and the first two time-periods, respectively. \begin{table}
\begin{tabular}{c c c} \hline
**Attribute Name** & **Description** & **Values** \\ \hline \(\mathsf{O}\text{cs}_{\text{i}}\) & Student presence in the i-th optional contact session & absence, presence \\ \(\mathsf{W}\text{ri}_{\text{i}}\) & Student grade in the i-th written assignment & [0, 10] \\ \hline \end{tabular}
\end{table} 
Table 2: Academic performance attributes, \(\mathsf{i}\in\{1,\ 2\}\).