Shifts in Educator Roles, Professional Practices, and Organizational Models Driven by eLearning Disruptive Forces

Michael Sandel is an international superstar.  His 2013 tour filled 14,000 person stadiums in places like Seoul Korea.  He was broadcast on national television and became so popular that he was asked to take a place of honor at a national sporting event.  In China his Internet video has been watched over one million times.  If you have not heard of Michael Sandel you might be surprised to hear that he is not the lead singer in a rock band, or a Hollywood movie star.  Michael Sandel is a Harvard philosopher and lecturer.  Sandel’s “show” is a series of lectures on justice and political philosophy, not exactly a topic regarded in the popular mainstream.

Andrew Ng is both a “rock star” and an “edupreneur.”  In October 2011 he offered his Machine Learning course at Stanford for free to anyone in the world.  Over 100,000 people enrolled in that first iteration. His work subsequently led to the founding of business start-up Coursera in 2012.  He is quoted as commenting that to reach that many students within the traditional model he would have to teach for 250 years.

An ecosystem empowered by global telecommunications and Internet technologies is creating the opportunities for some teachers to have a positive impact on significantly more lives and reach unprecedented levels of fame and fortune. Disruptive forces driven by eLearning technologies, “big data”, new human capital strategies of educational institutions, market demands, economic conditions, learning science discoveries, and innovations in professional practice are driving toward new education delivery models.  Some of these models give good lecturers a “bigger stage” without significantly changing the big lecture hall experience for learners. Other models leverage the specialties of a team of education professionals to personalize and optimize student learning.  Market demand for these new delivery models has already begun to impact traditional institutions.

New models of delivery require changes in professional practices. Emerging online learning models, for example, shift the focus from hour-long lectures and textbooks to more interactive shorter cycle learning experiences in which individual learner understanding is checked continuously.  While much of the hype around massively open online courses has been about the number of students watching video lectures, a more important metric is the higher quality that can be achieved with economies of scale and the massive amounts of data that can be mined to optimize student learning.  This data is powerful as a feedback loop for optimization of individual learning experiences and as a means to optimize learning experiences across populations.  This “big data” also supports new research methodologies driving down the cost and time that it takes to do gold standard studies and with greater applicability.

“You can turn the study of human learning from a hypothesis-driven mode to the data driven mode.  You can ask questions like what are some of the misconceptions that are more common and how can we help students fix them.”

(Koller, Daphne; http://www.ted.com/talks/daphne_koller_what_we_re_learning_from_online_education.html, June 2012, downloaded 21 April 2013)

Part of what is giving this "big data" the greatest impact is the adoption of common data vocabularies, such as those defined in the Common Education Data Standards (CEDS), an initiative led by the U.S. Department of education.  CEDS doesn't collect data, it provides common definitions used across organizations and sectors so that data about student learning experiences from one institution may be compared to data from another institution.

Professor Neil Heffernan teaches artificial intelligence at WPI.  Unlike Andrew Ng, however, Heffernan doesn’t lecture to hundreds of thousands of students through a massively open online course.  He is achieving a different kind of fame as an inventor of next generation learning technologies. Heffernan developed intelligent tutoring technology that is bridging research and practice.  He is taking on Benjamin Bloom’s “2-sigma problem.” Bloom found that one-on-one tutoring is two standard deviations more effective than a group lecture, and the problem is that one-on-one tutoring is cost prohibitive at scale…or at least it has been cost prohibitive.  Heffernan’s free-to-the-public ASSISTments platform offers “scaffolding” similar that provided by a tutor for students learning mathematics.  The system can be configured to identify common mistakes/misconceptions and give descriptive feedback to the student just at the right time, but it is not designed to replace teachers, rather it supports a teacher-directed blended learning model.  As a research platform ASSISTments can identify common misconceptions and perform short-cycle studies on the effectiveness of possible interventions in alleviating those misconceptions.

So far we’ve identified three emerging roles in which college professors have gained greater impact, not to mention fame and fortune.  I’ll call them the “rock star”, the “edupreneur”, and the “innovator”.  There are many other roles critical to the success of the emerging eLearning models.  Other roles include the learning experience designer, the producer, the cinematographer, the game-based-learning developer, to name a few.   Online and blended learning models could bring about a renaissance for the education profession with new opportunities and opportunities for greater rewards. 

Disclosure: My current work includes facilitating the Common Education Data Standards (CEDS) an initiative of the U.S. Department of Education, and I’m on an advisory board for WPI’s ASSISTments project.