Human Beings Could Be the Largest Untapped Resource in Online Learning

Jim ShimabukuroBy Jim Shimabukuro

Posted 7/28/15 at 10:17am; updated 11:46am

In the discussion on “MOOCs and Traditional Online Courses Are on a Collision Path,” Ray Rose (onlinelearningevangelist) and Harry Keller are having a fascinating exchange on the problem of captioning in MOOC videos. A cost-effective solution is autocaptioning, but the outlook at this time for developing an effective tool isn’t very good.

Their discussion fascinates in more ways than one. For example, it raises the issue of problem-solving in the online environment. What is the best approach?

For problems in technology, we naturally gravitate toward technological solutions, for example, a program that automatically translates speech to text and displays it as captions.

The cost for developing such a program, however, may be prohibitive, and the wide variation in human speech even within a single dialect makes the task extremely difficult.

But high tech problems don’t necessarily exclude low-tech solutions that are leveraged by technology. Put another way, the latest technology could generate innovative approaches that rely on old-fashioned human power, creating cost-effective solutions that blend the old with the new.

For example, Duke’s Sally Kornbluth,1 discussing the problem of formative evaluations in MOOCs, says, “If you’re wondering how you can possibly read 400,000 essays, you can have 400,000 students read one another’s essays.” Her point is that “there’s a lot of unexplored power that can be harnessed.” We just need to open our eyes to a much wider range of possibilities — and the possibilities could easily include human resources such as classmates empowered by networking technology.

The rap against peer feedback models, however, is that they’re unreliable, but ongoing research is proving that they can be and are being improved.

We have to keep in mind, though, that peer feedback is really just one of many other forms of evaluation provided by people other than teachers. For example, Sebastian Thrun,2 for his Udacity nanodegree on Android programming, takes the idea of peer evaluators and leverages it to include experts who aren’t part of the formal instructional staff. He has created a “network of 300 global code reviewers” who provide feedback to students.

The genius of this business model is that it’s self-sustaining while providing a profit for Udacity. Students pay $200 a month, reviewers’ pay is covered by this amount, students rate the quality of the feedback they receive, and reviewer income is determined by the evaluations they receive from students.

According to Thrun, “The best-earning global code reviewer makes more than 17,000 bucks a month. I compare this to the typical part-time teacher in the U.S. who teaches at a college — they make about $2,000 a month.”

This model could be applied to other problems (see Harry Keller’s comment) such as captioning. For example, MOOC developers could put out an international call for transcribers who are willing to provide captioning services. Since captions are aimed primarily at learners with disabilities, candidates could be volunteers or paid through philanthropic and public funds. A rating system could be attached to the videos, providing both student feedback on the quality of the captions and a means to control for quality.

The pool for captioners, when geographic location is factored out, is potentially huge. It could include high school and college students earning service credits, retirees, homebound adults, military personnel, and select prisoners.

We tend to think of technology as cold and impersonal, but it really doesn’t have to be. Technology could easily be a means to expand and deepen human interaction, providing a way for people to collaborate, one-on-one, with others.

1George Anders, “The Believer: Duke’s Sally Kornbluth,” MIT Technology Review, 27 July 2015.
2Nanette Byrnes, “Uber for Education,” MIT Technology Review, 27 July 2015.