Colorado State U and McGraw-Hill Education Launch Learning Analytics Research Project
A new research initiative from McGraw-Hill Education and Colorado State University is exploring the use of learning analytics to boost retention. The collaboration represents the first academic research project undertaken by the recently created McGraw-Hill Education Learning Science Council, a group of education experts and McGraw-Hill researchers focused on learning analytics, learning algorithms, learning quality and learning efficacy.
The project is investigating "the use of advanced techniques in learning analytics and educational data mining to reduce the Drop-Fail-Withdraw (DFW) rates in science, technology, engineering and mathematics (STEM) gateway courses" at Colorado State — courses that often impact retention and graduation rates, according to a press release. Researchers will focus on "testing and validating predictive models for course completion," combined with "interactive insights for advanced diagnostics and intervention." The goal is to help instructors identify at-risk students and work with them to make sure they succeed.
"Learning analytics is developing quickly as an area of academic research, and we want to use this type of research to solve strategic challenges at the university," said Patrick Burns, CIO for Colorado State University, in a statement. "By working with McGraw-Hill Education's researchers, we hope to discover new techniques for solving the persistent challenge of high attrition rates in STEM gateway courses. We expect that the research will also benefit other courses and allow faculty to access data and insights in novel ways for enhancing teaching effectiveness."
"Through our collaboration with McGraw-Hill Education, we are looking at how we can provide instructors with actionable, data-driven insights that will allow them to help students, at all levels, successfully complete their courses," said Dave Johnson, director of research and analytics for Colorado State University Online, which has been leading the learning analytics research. "We are already starting to see some exciting results and look forward to incorporating our findings in new practical applications."
Preliminary results are expected in the first half of this year.
About the author: Rhea Kelly is executive editor for Campus Technology. She can be reached at firstname.lastname@example.org.