Stephanie Teasley is a research professor at the School of Information and has been a faculty member at UMSI since 2001. She received her PhD in psychology from the University of Pittsburgh and a BA from Kalamazoo College. She is the director of the USE Lab at the University Library, whose mission is to investigate how instructional technologies and digital media are used to innovate teaching, learning, and collaboration.
She directed the doctoral program at UMSI from 2006-12. She is currently a member of the U-M Coursera Advisory Group and the Learning Analytics Task Force and serves on the Executive Board of the Society for Learning Analytics Research (SoLAR).
Learning analytics (LA) is rapidly becoming a hot area in the larger arena of “big data,” and universities have become particularly interested in the ways we can use LA to improve teaching and learning. Stephanie’s research utilizes LA to categorize and simplify the vast amount of data on student engagement and learning available in CTools, the campus learning management system (LMS).
Given the penetration of LMSs throughout higher education and the breadth of use on most campuses, these systems offer a ready source of near real-time data that can be analyzed to support a multitude of academic decisions for an increasing number of students. However, prior research on data-driven decision making has shown that the access to educational data does not automatically lead to improvements in student learning.
Working together with students in the USE Lab, Stephanie has developed a system to provide rich and actionable views of student data and present this data in an easy-to-understand dashboard. This dashboard, called the Student Explorer, was specifically developed for academic advisors of at-risk students. In the 2011-12 academic year, nearly 400 U-M engineering students’ course-related activities in the campus learning management system were coded and presented in conjunction with formative assessment data recorded by their instructors. The Student Explorer dashboard categorized student performance and engagement, and allowed advisors to identify which students were in critical need of intervention and additional support.
In her future work, Stephanie plans to include admissions and registrar data that may help alert advisors to students who might be more likely to experience greater difficulty in particular courses. In addition, she would like to eventually roll out a dashboard for students that encourages them to be pro-active about seeking advising and utilize the available support mechanisms that are most appropriate for each course.
This project builds recent advances in Learning Analytics to create “early warning systems” that alert faculty and/or students to sub-par student performance. Stephanie’s findings can guide future interventions that combine large data sources, performance dashboards, and purposeful academic support.
Although as a research professor Stephanie rarely teaches in the classroom, she works closely with students at all levels, from undergraduates to post-docs, on her research projects. The USE Lab currently has eight students working on projects related to technology for supporting collaboration and learning. To date she has graduated three PhD students from UMSI and served on numerous thesis committees across the university.