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 main aim of this paper is to present results of an experimental test focused on the validity and effectiveness of composed methodology aimed at increasing the student's attention in Virtual Learning Environment. Areas of presented methodology which were subject of our research is students behavior during learning. The behavioral part of…

This empirical study uses a random forest algorithm to examine the factors that influence learners' persistence in online learning at a prominent Korean institution. The data were collected from students who began their studies in Spring 2021, and encompassed a range of variables including individual attributes, academic engagement, academic…

This study examined the efficiency of teaching Russian as a foreign language (L2) in two groups of students -- the first benefited from the e-learning platform's capabilities (experimental), and the second underwent a traditional in-class course. Students learning Russian as L2 at People's Friendship University of Russia (Moscow, Russia) were…

This study explores the potential of using screen time data in learning management systems (LMS) to estimate student learning time (SLT) and validate the credit value of courses. Gathering comprehensive data on actual student learning time is difficult, so this study uses LMS Moodle logs from a computer programming course with 490 students over 16…