From LMS Data to Course Achievement

Pauline Muljana, a PhD Candidate in Instructional Design and Technology at Old Dominion University, will present a synthesis of her three papers related to applying course-level learning analytics to help instructors promote learning behaviors and strategies associated with successful learning.

Paper 1 – “Learning analytics: Translating data into ‘just-in-time’ interventions,” available at https://digitalcommons.humboldt.edu/sotl_ip/vol1/iss1/6/

Paper 2 – “Female students in quantitative courses: An exploration of their motivational sources, learning strategies, learning behaviors, and course achievement,” available at https://rdcu.be/cpkTL

Paper 3 – “Conducting a formative evaluation on a course-level learning analytics approach through the lens of self-regulated learning and higher-order thinking” (still under review).

The use of learning analytics is emerging in higher education, and the potential benefits are recognized. However, the practice of translating data into actionable interventions is not a simple task. In this presentation, Pauline will introduce practical guidelines for using readily-available LMS data to inform decisions regarding “just-in-time” interventions that help students perform better. Then, examples regarding the LMS data correlatable with student performance will be presented. Lastly, Pauline will discuss an evaluation of course-level learning analytics that uses the aforementioned guidelines and LMS data, wherein the findings inform the next reiteration of course design.