# Predicting Student Grades Based on Their Usage of LMS Moodle Using Petri Nets
## 4 Results and Discussion
### Model of the Final Exam in Petri Nets  
Each student was allowed two attempts for the final exam if he/she failed to pass the exam the first time. Based on student grading, a model in Petri Nets was created that showed how students proceeded with passing the exam.  
The \"Start\" location represented the number of students who took the exam this year. The model (Figure 11) also used transition weights to display the distribution of grades from a single exam. Transitions in which \"Exam\", \"Exam 2\", and \"Exam 3\" places were entered, had weights set according to the number of students who received a grade for the exam, as determined by the exit points of these places. In the model, weights were displayed by transition weights so it was shown that four students after the first exam did not come to the next exam, and five students did not take the third exam after failure, but the students who came to the third exam all succeeded. Observing the model, the question arose whether it would be possible to see any improvements in the grade among exams in terms of visits to study materials.  
In the model of Figure 12, \"Mat 1\" and \"Mat 2\" were added to serve as an e-course visit counter. \"The Book\" and \"Lectures\" were the chosen materials to observe. In the previous graphs, they displayed the most significant correlations and they were the only materials that could be used to study between the exams. The tracking data from the model produced interesting results. For students who failed the first attempt, the correlations between their grade obtained after successfully completing the second  
Figure 11: Model of the final exam in Petri Nets.  
Figure 10: Grades based on attendance.  
or third attempt and their time spent studying in the e-course were insignificant. For students who completed the exam after the second attempt, these correlations were \(-0.24551\) for Book visits and \(-0.13365\) for Lecture visits, both of which represented a small correlation. For students who completed the exam on the third attempt, correlations were positive, \(0.555851\) for \"Book\" visits and \(0.610275\) for \"Lectures\", which would mean that the less they studied, the better grade they got. It could be assumed that these correlations could be explained by the possibility that students cheated on the test or having only a small sample of students for the test (five students).  
For this reason, the students who passed the exam on their first attempt or did not come to the next dates were observed more. For them, the correlation of the final grade and the time spent studying in the course was most striking, as explained below.  
For students who succeeded on the first attempt or gave up after the first attempt, correlation based on Moodle\"Book\" visit was \(-0.43742\). Their arrangement can be seen in Figure 13.  
Figure 12: Model of the final exam with the observation of the study.  
Figure 13: Grades based on visits in “Book”material, at the first attempt.  
For students who succeeded on the first attempt or gave up after the first attempt, the correlation based on Moodle\"Lecture\" visit was \(-0.58561\), which represented a greater correlation. This is shown in Figure 14. This was the most significant correlation of all.  
To sum up, it is not possible to conclude that the only contributing part to improve student grades was the PDF lectures that students could view in Moodle. Neither participation in the exercises nor the practical assignments submitted to the exercises had a significant impact on the final evaluation of students.