The Post-MOOC World

We’ve become so accustomed to the cycle of hype that we apply it to every new innovation without thinking. We expect all new technologies to be swept upward on a wave of emotion, only to fall to earth when the hype wears o . By reducing innovation to a stereotype, we overlook the new ideas that each innovation can bring. A recent swing in the cycle of hype began in 2011, when massive open online courses (MOOCs) emerged as the great disruptive technology of higher education. That fall, Stanford University’s now-famous MOOC on arti cial intelligence attracted 160,000 students. Within a year, many univer sities ann ounced plans for MOOCs and more than a few university trustees criticized their presidents for not embracing the technology quickly enough. By fall 2014, most schools had restricted their plans for MOOCs or even abandoned the model entirely. Detractors quickly noted these courses’ low completion rates and high cost of production. Successful providers such as Udacity, edX, and Coursera tended to focus on large courses that were standard parts of the university curricula. University administrators began to claim that MOOCs might gain publicity for a school even if they wouldn’t transform higher education. Swept up in the cycle of hype, we’ve missed an opportunity to think deeply about how we learn, how we transmit ideas from one generation to the next, and how we discipline our thoughts to meet the challenges of our times. Much of the discussion of MOOCs treated computing technology as a tool of mass distribution—a way of storing great thoughts and circulating them to ever wider audiences. This wasn’t a particularly innovative idea, as it differed little from a 1950s conversation about computers in higher education. In 1955, businessman Roger Babson, the founder of Babson College, proposed capturing great thinkers’ ideas and distributing them to classes with the aid of a computer. “The result should be more e ective than the present ‘human touch’ idea,” he wrote. He concluded by stating that “we have been misled to believe we must have a visible human teacher.” Babson’s vision failed to transform higher education during his time. In much the same way, we’re moving into the post-MOOC world not because we’ve learned anything new about education, but because of the economics of this mode of learning. A few researchers are using computing technology to observe how students interact with instructional material in the hopes of getting a clearer understanding of the educational pro cess. A recent MIT study tracked the keystrokes of students watching instructional videos. For the most part, the study yielded little new information: great intellectual breakthroughs rarely follow the cycle of hype. However, there were at least two major patterns in the keystrokes. About 60 percent were associated with changes in the videos and could be explained by a conventional story. These keystrokes identi ed activities such as students jumping back to review an idea they had missed, and jumping forward past material they understood. Although 40 percent of the keystrokes didn’t match obvious changes in the video and thus didn’t lead to any obvious conclusions, they suggest the process of a mind at work—a mind that’s starting to break away from the narrative arc of the video and building a narrative of its own. Such an action might ultimately give us a deeper under standing of the learning process than the data that matches the pattern set by the instructional material.