UMSI Research Professor Stephanie Teasley was awarded a $1.25 million grant from the Michigan Institute for Data Science (MIDAS) to fund a learning analytics project, which seeks to build a holistic model of student achievement. As principal investigator of the project, Teasley will use data drawn from U-M’s learning technologies and information available in the student data warehouse to build a model of student achievement that will provide tailored instruction for the specific needs of all students.
One of the aims of Teasley's project is to integrate the learning analytics work being done by U-M research in several different fields—from visualizing educational data to studying active learning technologies to analysis of in-class behavior—into a single, data-driven model that promises to yield new insights into the learning process.
"This research has the potential to yield new understandings of how people learn," Teasley said. "Our goal is to demonstrate how data-driven inquiry can improve teaching and learning in higher education."
Associate Professor Kevyn Collins-Thompson and Research Assistant Professor Chris Brooks will also contribute to Teasley’s project along with researchers from the College of Engineering, School of Education and the departments of Physics and Astronomy.
This funding was awarded as part of a U-M Data Science Initiative announced in fall 2015. Four research projects – two each in transportation and learning analytics – received $1.25 million dollars in the first round of the MIDAS Challenge Initiatives program, which was determined through competitive submission process.