Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsTechnological advancement has led to the increasing use of all types of electronic devices,
which causes large volumes of data to be constantly generated and stored in repositories.
This growth in data through Information Technology (IT) systems makes it necessary to
continue its exploration and analysis to support institutions in the decision-making process.
Due to the importance of education in society, this field has been the target of several studies
over the years.
Taking that into account, and knowing that association rules and regression analysis are
among the most popular data mining algorithms for finding the hidden patterns in data,
the purpose of this paper is to find exciting trends across courses considering the students’
grades, as well as study if, and to what extent, the student’s learning performance is related
to their interaction in moodle. The data used were collected through the netp@ and moodle
systems, consisting of all student learning data and activities/logs history. This data belongs
to students of all masters who attended the academic years between 2012-2013 and 2020-
2021.
We chose Sample, Explore, Modify, Model, and Assess (SEMMA) methodology for the
applicability of its steps to accomplish the study’s goals.
Through the Partial Least Squares Regression (PLSR) algorithm, it was shown that Gestão
do Conhecimento, Metodologias de Investigação and Métodos Descritivos de Data Mining are
the most importants courses that affect the grades of Dissertation/Work Project/Intership
Report in the Business Intelligence specialization. In addition, according to the predictive
model, Metodologias de Investigação was the most important variable for predicting the performance
of the Dissertation/Work Project/Internship Report of Information Systems and
Technologies Management specialization.
Finally, the association rules algorithms used were the Apriori, FP-Growth and Eclat.
From their results, it was found that courses with continuous assessment methods achieve
better academic performance compared to others. Furthermore, higher levels of online
interaction are associated with better achievement
