Academic Data Derived from Blended Learning

The data were collected from the digital infrastructure of the University. The dataset provided for this research is constructed using data from two different platforms: The MS Team platform and the Open eClass Platform.

Our dataset was extracted from MS Teams and includes 13 attributes related to the course meetings that lecturers participate in. Our next source of data is the (open) eClass Platform which includes statistics about the student’s behavior on the platform. Data are completely anonymized, as no reference to the participant is kept. Only a newly auto-increment ID per student is used. The final dataset of student profile consists of 32 attributes, and it requires preprocessing in order to eliminate the parameters which are going to feed the classification algorithms.