New Trends in Engineering

Data mining in the education sector is predominantly used to predict, group, model, and monitor
various learning activities using techniques such as classification, clustering, association rules,
statistics, and visualization (Aldowah, Al-Samarraie, & Fauzy, 2019). EDM is a process for
addressing important educational questions using DM techniques applied to specific datasets
originating from educational environments (Romero & Ventura, 2013). In Romero and
Ventura’s review (2013) on EDM, they figured out a cycle (Figure 1) about how DM in
educational environments is applied. The items in EDM lifecycle have educational systems as
source of data; ie traditional classrooms, e-Learning environments, data mining tools and
methods; ie Python, Weka, RapidMiner, etc. and classification, clustering and directions of
meaningful information gained are students, educators and responsible administrators.