Identifying Critical LMS Features for Predicting At-risk Students. (arXiv:2204.13700v1 [cs.LG])

Learning management systems (LMSs) have become essential in higher education
and play an important role in helping educational institutions to promote
student success. Traditionally, LMSs have been used by postsecondary
institutions in administration, reporting, and delivery of educational content.
In this paper, we present an additional use of LMS by using its data logs to
perform data-analytics and identify academically at-risk students. The
data-driven insights would allow educational institutions and educators to
develop and implement pedagogical interventions targeting academically at-risk …

arxiv features risk students