Institutions of higher education possess large amounts of learning-related data in their student registers and learning management systems (LMS). This data can be mined to gain insights into study paths, study styles and possible bottlenecks on the study paths. In this study, we focused on creating a predictive model for study completion time…

The purpose of this mixed-methods study was to explore factors affecting faculty members' motivation to use learning analytics (LA) to improve their teaching. In the quantitative phase, 107 faculty members completed an online survey about their motivation to use LA. The results showed that cost, utility, attainment value, and competence all…

Predicting students' learning outcomes is one of the main topics of interest in the area of Educational Data Mining and Learning Analytics. To this end, a plethora of machine learning methods has been successfully applied for solving a variety of predictive problems. However, it is of utmost importance for both educators and data scientists to…