We use Eurobarometer data to examine barriers to international student mobility. Multivariate analysis is employed to study how individual characteristics are related to the obstacles preventing higher education students from participating in activities in another EU country. The results suggest that several demographic factors including area of…

In this paper, we present an extended evaluation of a course recommender system designed to support students who struggle in the first semesters of their studies and are at risk of dropping out. The system, which was developed in earlier work using a student-centered design, is based on the explainable k-nearest neighbor algorithm and recommends a…

This study presents a data mining approach to predict academic success of the first-year students. A dataset of 10 academic years for first-year bachelor's degrees from a Portuguese Higher Institution (N = 9652) has been analysed. Features' selection resulted in a characterising set of 68 features, encompassing socio-demographic, social origin,…

Student dropout is a significant concern for university administrators, students and other stakeholders. Dropout is recognised as highly complex due to its multi-causality, which is expressed in the existing relationship in its explanatory variables associated with students, their socio-economic and academic conditions, and the characteristics of…

This article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…

This study attempts to predict secondary school students' performance in English and Mathematics subjects using data mining (DM) techniques. It aims to provide insights into predictors of students' performance in English and Mathematics, characteristics of students with different levels of performance, the most effective DM technique for students'…

Educational improvement projects are increasingly focused upon the significant role of data in determining student performance, teachers' learning, and schools' ability to initiate local reforms. Thus, schools are moving toward a new approach to learning, progressing from the routine to the non-routine through inquiry-based working. In addition,…

This three-article dissertation considers the pedagogical practices for developing statistically literate students and teaching data-driven decision-making with the goal of preparing students for civic engagement and improving student achievement. The first article discusses a critical review of the literature on data-driven decision-making…