After three days of rain
PITTSBURGH—Carnegie Mellon University researchers will tap data-driven approaches to improving learning as part of a new Google-sponsored effort to unlock the educational potential of massive open online courses, or MOOCs.
The multi-year program, made possible through a Google Focused Research Award, employs a variety of methods to improve MOOCs. The research plan includes development of techniques for automatically analyzing and providing feedback on student work, for creating social ties between learners and for designing MOOCS that are effective for students with a variety of cultural backgrounds.
“We’re excited about Carnegie Mellon’s work on mechanisms to allow online courses to adapt automatically to the learning needs of individual students,” says Alfred Spector, vice president of Research and Special Initiatives at Google. “We believe this research will make online courses much more engaging, and benefit both students and educators around the world.”
The goal is to get online courses to be as successful as the best courses in brick-and-mortar classrooms, said Justine Cassell, associate vice provost of technology strategy and impact and co-director of CMU’s Simon Initiative, a university-wide effort that uses learning science and technology to improve student learning.
“A MOOC today typically means a lecture-style presentation with little if any opportunity for interaction with other people in the course,” Cassell said. Not surprisingly, most students drop out long before the courses are complete, and learning gains are often low even for those who stick it out. “Unless the MOOCs pay attention to how people actually learn, they will not be able to improve effectiveness, and will end up as just a passing fad,” she added.
The CMU program will approach the problem from several directions.
In one thrust, Emma Brunskill, assistant professor of computer science, and Ken Koedinger, professor in theHuman-Computer Interaction Institute (HCII) and director of the Pittsburgh Science of Learning Center, will use machine-learning techniques to personalize the MOOC learning experience. Computer programs will evaluate each student’s work, identifying subject matter that has been mastered and areas where additional study or different types of exercises could be beneficial.
This kind of data-driven learning, pioneered at Carnegie Mellon, has shown to make learning faster and more effective.
In another thrust Carolyn Rosé, associate professor in the Language Technologies Institute, and Robert Kraut, professor of HCII, will look for ways to reduce attrition. Though many students in MOOCs are simply browsing, even committed students have a high drop-out rate. To improve retention, Kraut and Rosé will look for ways of increasing socialization, through mentoring, team assignments and other techniques. They also seek to identify warning signs that students are in danger of dropping out and to develop interventions to re-engage them in courses.
A third thrust will focus on how to make the content of the course more engaging. Jessica Hammer, assistant professor in HCII and the Entertainment Technology Center, and Amy Ogan, assistant professor in HCII, will examine how to enhance the pleasurable aspects of MOOCs, adjust the design of courses available globally to account for cultural differences, and develop a deeper understanding of how and when to incorporate game play into MOOCs.
The Google award will fund the research at $300,000 a year for two years, with an option for a third year.
Google’s Spector is a member of the Global Learning Council (GLC), which includes leaders from academia, the private sector and the foundation community. Chaired by Carnegie Mellon President Subra Suresh, the GLC aims to serve as a standards and best-practices resource for individuals and organizations seeking to deploy technology-enhanced learning approaches to improve learning outcomes. The GLC will have its first annual meeting in Pittsburgh in September.
The Human-Computer Interaction Institute, Language Technologies Institute and Computer Science Department are all part of Carnegie Mellon’s top-ranked School of Computer Science, which is celebrating its 25th year. Follow the school on Twitter @SCSatCMU.