Source: NYTimes, Mar 2012
At Stanford University, an intriguing big-data experiment in online education is under way. Last year, three computer science courses, including videos and assignments, were put online. Hundreds of thousands of students have registered and participated in the courses.
The courses generate huge amounts of data on how students learn, what teaching strategies work best and what models do not, said Daphne Koller, a professor at the Stanford Artificial Intelligence Laboratory.
In most education research, teaching methods are tested in small groups, comparing results in different classrooms, Ms. Koller explained. With small sample groups, research conclusions tend to be uncertain, she said, and results are often not available until tests at the end of school semesters.
But in an online class of 20,000 students, whose every mouse click is tracked in real time, the research can be more definitive and more immediate, Ms. Koller said.
“If 5,000 people had the same wrong answer, it’s obvious a concept is not getting through, and you have a clear path that shows where students went wrong,” she said.
That kind of data tracking in education, she said, provides “an opportunity no one has exploited yet.”