Analytics Research: Effective Tool Use Patterns and Student Responses to Data-Driven Interventions

Tuesday, February 14 | 4:15PM–5:00PM | Houston Ballroom VII
Session Type: Breakout Session
Delivery Format: Interactive Presentation
Learning analytics research has largely been constrained to a small number of courses, and it's unclear whether this research will scale. This session will discuss the results of research on LMS use and student achievement across 927 institutions, 70,000 courses, and 3.3 million learners. Aggregate "total duration" was found to be a weak indicator; gradebook access, content use, and time in assessments reveal more powerful predictors and interesting patterns revealing student motivations and outcomes. Further, we will present research into student perspectives on the usability of data-driven intervention designs, comparing high- and low-achieving students.

Outcomes: Understand strong and weak predictors of student achievement within the LMS across a large number of courses *Apply similar predictors to courses within their institution and refine a learning analytics project *Interpret the results of several research studies within the context of their own institution


  • Stephanie Teasley

    Research Professor, School of Information and Director of the Learning Education & Design Lab, University of Michigan-Ann Arbor
  • John Whitmer

    Senior Fellow, Federation of American Scientists