Experts in artificial intelligence are leaving academia to bring online learning to the world. But their most radical ideas are still on hold.
“We saw the opportunity and the technology and had the ability to leverage it,” says Koller. But putting classes online is only part of what the AI researchers intend with MOOCs. By following the progress of millions of students online, it may be possible to develop new insights into how people learn and tailor classes on an individual level. “What we have here is an unprecedented level of detail and scale of data,” she says.
Like its technology, Coursera’s business model is a work in progress. One idea considered has been a job board to connect employers to students who have taken specific Coursera classes. Another is to charge students who want to earn an official credit. In November, Antioch University in Los Angeles said it would begin letting its students take two Coursera classes for credit, splitting the modest revenues with the company.
Classes on the site are still of uneven technical quality. A course on Greek and Roman mythology is little more than a talking professor green-screened against bullet points and pictures of temples. But Koller believes this is just the beginning. By collecting an unprecedented amount of data about how students are learning, and analyzing it automatically in real time, educators could realize their dreams of personalized education at a large scale. “The goal is to design personalization, and to identify where someone is struggling and what might be helpful to them,” she says.
Some of Koller’s own academic research, published this February, illustrates how this might work. She and several collaborators applied machine-learning techniques to study an introductory programming class. The researchers created mathematical descriptions of the students themselves, looking for models that would explain their advances and setbacks. One discovery: success in the course was predicted by a student’s approach to solving the first assignments, not by right or wrong answers.