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…

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…

Data from three sections of 200-level college statistics courses (student N = 85) were examined to evaluate the relationship between scaffolded assignments, time spent in the course, page views, and student performance. Strong positive correlations were noted between scaffolded assignments. Key formative and summative assignments also showed…