Massive open online courses, or MOOCs, are hailed as a new innovation so disruptive for academia today that they will do to higher education what the Internet has done to newspapers or what Napster did to music. There's only one problem with this bold hypothesis: It's simply not true.
Don't get me wrong, online learning will fundamentally transform higher education, bridging distances and creating access in ways that have not been possible before. But, in this arena, MOOCs are not a transformative innovation that will forever remake academia. That honor belongs to a more disruptive and far-reaching innovation – "big data." A catchall phrase that refers to the vast numbers of data sets that are collected daily, big data promises to revolutionize online learning and, in doing so, higher education.
Big data in the online learning space will give institutions the predictive tools they need to improve learning outcomes for individual students. By designing a curriculum that collects data at every step of the student learning process, universities can address student needs with customized modules, assignments, feedback and learning trees in the curriculum that will promote better and richer learning.
As the leader of the big data revolution, Google gathers information through clicks on the Internet and uses this information to personalize advertising to individual users. Academia will use the same model in the learning process to customize courses right down to the level of the individual. Some companies, such as the nonprofit testing firm ETS, are already harnessing data to develop predetermined learning trees to track certain responses to questions that imply mastery of specific aspects of material, thus allowing educators to organize assignments based on those answers.
Imagine how such knowledge can be used to give instructors the necessary intelligence to directly address a student's learning style or deficits. In this way, big data can amplify factors that contribute to student success – personalized courses, the instructor-student connection and a wired sense of community – despite being in the detached online learning environment.
I offer up this different view of the technology revolution ahead because too many people in higher education and outside of it, including some of the New York Times' columnists, consider MOOCs to be a revolutionary rather than evolutionary step in academia. Most certainly, MOOCs are a great tool for sharing large qualities of information via the Web, but they are little more than virtual textbooks when it comes to learning. They broadcast information, but they don't teach.
Smart universities are looking for ways to adapt using big data and community-building technologies. They know that students will seek opportunities that allow them to virtually cross borders and boundaries in learning. Beyond online learning, administrators understand that big data can be used in admissions, budgeting and student services to ensure transparency, better distribution of resources and identification of at-risk students.
While the delivery of MOOCs is a very inexpensive solution in the online learning ecosystem, the big data revolution will be expensive and hard. The collection, aggregation and application of learning analytics is a time-consuming process that requires academia to invest in and rethink the entire learning practice. Much will be asked of professors and instructors as well as technology and curriculum experts. This progression will require self-reflection and a ruthless commitment to elevate pedagogy over profits. But then only the naïve and uninformed considered teaching to be a simple and inexpensive proposition.
MOOCs have become the flavor of the moment in higher education reform circles because academia is desperately seeking solutions – and fast. In the United States, universities and colleges face tremendous pressures in terms of their business models, the mobility of students, the growing disillusionment with four-year degrees and the cost of higher education.