Evaluating Contact Sessions and Assignments Grades Impact with Association Rules

Περίληψη

The socialization of students in distance learning and the impact on their performance is a major issue. The concept of Contact Sessions has a trend to be substituted by videoconferences, especially in the coronavirus era. Learning Analytics (LA) is a modern scientific field that enhances the learning environments and also the educational procedures. It leads to a better comprehension of the students’ learning process. The learners’ activity is traced by collecting, analyzing, and reporting their data in order to redesign the course in terms that incur from the LA new methodologies. Nowadays, there is a transition of LA from research to practice, which formulates a new perception of learning for the students by implementing the existed LA methodologies. We utilize the opportunity of this scientific field to reveal hidden patterns for student data by employing appropriate Data Mining algorithms. Specifically, we study the impact of Contact Sessions participation on the correlation among students who either have failed or passed the final exams. For this purpose, we find the association rules with the use of Apriori algorithm in data formulated in market basket format. The data concern the participation in the Contact Sessions and the submitted projects grades. In this fashion, we prove the need for the students’ attendance in the Contact Sessions as a factor that influences their performance in terms of socialization by using Data Mining.