Developing a Next-Generation Model for Massive Digital Learning

Abstract

A decade ago, massively open online courses (MOOCs) were heralded as the solution to universal, global access to higher education. While they failed to reach this vision, primarily because of teaching-by-telling and learning-by-listening (a PDF of the residential classroom), MOOCs provided the foundational models and infrastructure for emergency remote learning in the pandemic. Reports of remote learning’s death post-pandemic are greatly exaggerated, since the world is now irreversibly hybrid—and will stay that way because many people and organizations value the new opportunities this presents. From now on, when students leave the shelter of classrooms to interact with the world beyond schooling, they must have skills for adept performance both face-to-face and across distance. Colleges, universities, and regions that force all teaching and learning to be face-to-face are dooming their graduates to reduced agency in every other aspect of life. As discussed in recent reports from Harvard, MIT, and Stanford, innovative approaches to digital learning were developed during the pandemic that are now improving campus-based learning. Insights from these approaches offer the opportunity for student engagement at scale, taking advantage of strengths of online instruction such as collapsing time, bridging space, personalizing via rich datastreams, using AI-based instructional assistants and learning partners, delivering content and experience across universities, and sustaining online learning communities after formal instruction ends. Combined, these advances can enable next-generation massive digital hybrid learning, a means to achieve the aspirational vision of universal global access to higher education. A coalition of higher education institutions could begin to realize this vision, an essential step in enabling all learners to survive and thrive in our increasingly turbulent, disruptive global economy and civilization.