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How Engaged are Our Students? Using Analytics to Identify Students At-risk PROCEEDING

, , , , 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 October 20, 2018 from .

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References

  1. Agudo-Peregrina, Á. F., Iglesias-Pradas, S., Conde-González, M. Á., & Hernández-García, Á. (2014). Can we predict success from log data in VLEs? Classification of interactions for learning analytics and their relation with performance in VLE-supported F2F and online learning. Computers in Human Behavior, 31, 542-550.
  2. Cerezo, R., Sánchez-Santillán, M., Paule-Ruiz, M.P., & Núñez, J.C. (2016). Students' LMS interaction patterns and their relationship with achievement: A case study in higher education. Computers& Education, 96, 42-54.
  3. Kim, D., Park, Y., Yoon, M., & Jo, I.-H. (2016). Toward evidence-based learning analytics: Using proxy variables to improve asynchronous online discussion environments. The Internet and Higher Education, 30, 30-43.
  4. Krause, K.-L. (2005). The changing face of the first year: Challenges for policy and practice in research-led universities. Paper presented at the First Year Experience Workshop.
  5. Pitkethly, A., & Prosser, M. (2001). The first year experience project: A model for university-wide change. Higher Education Research& Development, 20(2), 185-198.
  6. Strang, K.D. (2016). Do the critical success factors from learning analytics predict student outcomes? Journal of Educational Technology Systems, 44(3), 273-299.
  7. Tinto, V., & Goodsell-Love, A. (1993). Building community. Liberal Education, 79(4), 16-22. Williams, A., Kilgour, P., Stewart, B., & Northcote, M. (in-press). An initiative to support first year students and students at risk: The Virtual Mentor Programme. The Journal of Adventist Education.
  8. Williams, A., & Sher, W. (2007). Using Blackboard to monitor and support first year engineering students. Paper presented at the 18th annual Australasian Association for Engineering Education Conference, Melbourne, Australia. Retrieved from http://www.cs.mu.oz.au/aaee2007/papers/paper_34. Pd f, Melbourne.
  9. You, J.W. (2015). Examining the effect of academic procrastination on achievement using LMS data in e-learning. Journal of Educational Technology& Society, 18(3), 64.
  10. Zacharis, N.Z. (2015). A multivariate approach to predicting student outcomes in web-enabled blended learning courses. The Internet and Higher Education, 27, 44-53.
  11. Zhao, C.-M., & Kuh, G.D. (2004). Adding value: Learning communities and student engagement. Research in higher education, 45(2), 115-138.

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