How Engaged are Our Students? Using Analytics to Identify Students At-risk
PROCEEDING
Tony Williams, Jason Morton, Peter Kilgour, Maria Northcote, Avondale College of Higher Education, Australia
EdMedia + Innovate Learning, in Amsterdam, Netherlands Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
Abstract
Learning Management System (LMS) analytics have become an area of increasing interest and development. The potential to better understand our students’ levels of engagement provided by the systems have, to date, has been underutilized information resources. The study reported here looks at the relationship of student and staff engagement in the LMS and considers the levels of predictability in student behavior leading to failure. Also considered is the impact of the lecturer on the student engagement of poor and high performing students.
Citation
Williams, T., Morton, J., Kilgour, P. & Northcote, M. (2018). How Engaged are Our Students? Using Analytics to Identify Students At-risk. In T. Bastiaens, J. Van Braak, M. Brown, L. Cantoni, M. Castro, R. Christensen, G. Davidson-Shivers, K. DePryck, M. Ebner, M. Fominykh, C. Fulford, S. Hatzipanagos, G. Knezek, K. Kreijns, G. Marks, E. Sointu, E. Korsgaard Sorensen, J. Viteli, J. Voogt, P. Weber, E. Weippl & O. Zawacki-Richter (Eds.), Proceedings of EdMedia: World Conference on Educational Media and Technology (pp. 122-128). Amsterdam, Netherlands: Association for the Advancement of Computing in Education (AACE). Retrieved August 13, 2024 from https://www.learntechlib.org/primary/p/184189/.
© 2018 Association for the Advancement of Computing in Education (AACE)
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