Exploring the link between e-learning and performance through a learning analytics lens
Kenneth David Strang, State University of New York, United States
Journal of Interactive Learning Research Volume 27, Number 2, ISSN 1093-023X Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
Researchers have demonstrated the capability of learning data analytics for student retention but it remains unclear if e-learning course activity is related to, or can predict, academic learning. Moodle engagement analytics has not yet been investigated with respect to student performance or in online business discipline courses. Unfortunately none of the hypothesized learning analytics factors were positively related to, nor could they predict, student academic performance. However, several interesting deductions from the learning analytics data gave rise to ideas for further research. Sense making of puzzling statistics suggested a mediating pattern of students’ poor self-regulation skills because more focus was put on the assignment requirements but less on interacting with the lesson materials needed to complete the assignment and thereby resulting in lower grades. Suggestions were made to use real-time learning analytics for capacity monitoring and human resource planning, to flag attrition, as well as to facilitate student self-regulation in online courses.
Strang, K.D. (2016). Exploring the link between e-learning and performance through a learning analytics lens. Journal of Interactive Learning Research, 27(2), 125-152. Waynesville, NC: Association for the Advancement of Computing in Education (AACE).
© 2016 Association for the Advancement of Computing in Education (AACE)