This study aims to discover groups of students enrolled in the emergency remote teaching online course based on the various course-related data collected throughout the first year of COVID-19 pandemic. Research was conducted among 222 students enrolled in the course “Business Informatics” at the Faculty of Organization and Informatics of the University of Zagreb in the academic year 2020/2021. Overlays were used to model students’ success on the various quizzes and exams within the course. The k-means clustering was employed to classify students into groups, based on combination of students’ overlay values, frequency of accessing course lessons and the final grades. Three distinct clusters (i.e., students’ groups) were discovered and explained in the given context. The identified groups of students can be used for future adaptations of the online course design in order to improve the retention and their final grades.

This study aims to evaluate the ways that the actual usage of a platform for digital competence acquisition, evaluation and certification contributes to satisfaction and perceived success of students in primary and secondary schools. A cross-sectional survey was implemented online to collect 1725 students’ answers in six European countries. The analysis of collected data was carried out by employing Pearson correlation, Partial least squares structural equation modelling (PLS-SEM) and Importance-performance map analysis (IPMA). Findings indicated that the usage of such a platform has greater effects on the impacts than on students’ satisfaction. Detailed analysis of correlations revealed that students’ decision on whether they will use the platform in the future greatly depends on how it contributes to the success of their learning processes. Results also suggest that teachers are seen as an inevitable part of such a process and are mandatory to achieve the full potential of the platform.