It’s probably too early to say whether Massive Open Online Courses (MOOCs) are a “tsunami” or a “seismic shift,” but, continuing with the natural disaster theme, the last few months have seen a massive “avalanche” of press commentary about them, especially within the last few days.

Also getting lots of press attention (though not as much right now) is Adaptive/Personalized Learning. Both innovations seem to fascinate us, but probably for different reasons, since they are so fundamentally different at their cores. Personalized Learning, like more traditional concepts of education, places the individual at the center. With MOOCs, groups and social interaction take center stage and learning becomes a collective enterprise.

This post elaborates on this distinction, but also points to a recent blurring of the lines between the two – a development that could be troubling.

But, first things first: What is Personalized/Adaptive Learning, what are MOOCs, and why are they different?

As I wrote elsewhere, personalized learning uses technology to adapt the presentation of content to students’ strength and weaknesses, as indicated by their prior responses to the material. The basic premise is that, when software is able to gauge a student’s level and adjust subsequent material to his/her pace and style of learning, the result is a more effective and higher quality learning experience.

By contrast, MOOCs are free college-level courses that are available to anyone with an Internet connection, where both participants and content are scattered across the Internet. Although some structure is provided, MOOCs are better understood as “a way to connect and collaborate” or “an event around which people who care about a topic can get together, work and talk about it in a structured way” – see here and here.

Personalized education views learning as an individual pursuit; learning results when the student interacts with the right content, at the right time, through the right medium. Technology helps this process by providing software that tries to “understand” what students know and how they learn – and, based on that, recommends what is hopefully the most appropriate material, presented in the most appropriate sequence, using the most appropriate methods.

The designers of MOOCs – and the open education movement more generally – tend to view learning as a cooperative endeavor. Knowledge does not reside in specific people or locations; instead, knowledge is “networked” and it is generated largely in interaction, as instructors and learners engage with one another. Content is not fixed and, although guidance materials are provided, an important objective of MOOCs is that students generate new content as they learn about a subject – i.e., “learning by doing.”

Personalized learning is seductive because it promises to customize structures and make things easier. By contrast, MOOCs are attractive because of their dynamism, sometimes verging on the chaotic. Both models have virtues, serve different types of learners, and may be combined in different ways at different stages of the learning process.

Because much of the “technology in education” debate focuses on higher education, I will say that, in my view, personalized learning has its limitations for college-level students. A few years down the road, when students graduate and go into the workplace, little if anything will adapt to their “individual needs and styles.” Indeed, in the workplace, it is their ability to adapt that will be viewed as valuable. How can a system that is designed to accommodate every individual idiosyncrasy help to prepare young people to thrive in a world that is so wide open?

More fundamentally, learning occurs, at least in part, when unexpected things push us out of our comfort zone. Somewhere I read that the purpose of education is to give people the opportunity to learn something they ordinarily wouldn’t. There is a missing ingredient in most models of personalized learning: basically, the natural entropy that characterizes human experience. After all, let’s not forget that adaptive learning is based on the same technology that is used to generate automatic movie and music recommendations – and most of us would agree that that these have their limitations.

With MOOCs, active learner participation is not just important; it’s central. The actual course is built around learners’ interactions and their co-construction of information. But it’s quite possible that MOOCs will only work for a small group of highly motivated people or people who share a specific interest and a drive to learn about it. For example, Stanford University recently offered two MOOCs: Machine Learning, for which 104,000 students registered but only 13,000 completed, and Introduction to Databases, for which 92,000 registered, and 7,000 completed.

Perhaps it is also possible for everybody to learn something abstract from this model: knowledge or “truth” is sometimes that which survives negotiation and consensus. In other words, the process of learning is a social or collective task, where everybody involved needs to do some of the adapting.

So what about the blurring that I mentioned at the beginning?

In 2008, George Siemens and Stephen Downes designed and taught a free online course called “Connectivism and Connective Knowledge.” The course was open to anyone and more than 2,000 people worldwide signed up. The phrase “Massive Open Online Course” was coined to describe this model, which, albeit much later, the Chronicle of Higher Education described as “a landmark in the small but growing push toward open teaching.”

A few days ago the New York Times published a story stating that “Internet courses are monologues” while “true learning is a dialogue” and that that is the “Trouble With Online Education.” I think this is not right. MOOCs – admittedly only a type or a stage of online learning – were never conceived as “monologues.” The real trouble is that the focus is increasingly shifting away from making learning as accessible as possible to making student assessment and credentialing as lucrative as possible. This, despite the fact one of the Ten Commandments of MOOCs is that assessment does not drive learning; learners’ own goals do. But maybe not anymore.

Early in June, Udacity (a company that imparts MOOCs) announced a partnership with Pearson VUE, a worldwide provider of testing services with 4,000 centers in more than 170 countries. This partnership makes it possible for Udacity students to take a final exam in a Pearson testing center, obtain an official credential, and be included in a job placement program. In other words, these traditional functions of college course-taking are being made more adaptable and personalized to accommodate the needs of students whose geographical location or work and family obligations make college attendance difficult. This may be of great value, but is such a course still a MOOC?

In an interesting essay titled “A Brief Guide to Understanding MOOCs” Ken Masters describes four stages in the evolution of online education – with MOOCs being the fourth stage. Toward the end, the author cautions instructors to be prepared to be scared:

Teaching through a MOOC is very different from the methods used in our education. Many of us are only now coming to grips with online education as described in Stage 2 or 3 above. In Stage 4, the course has been integrated with something that carries all the power (positive and negative) of social networking. You will be scared. Your students will be scared. The amount of self-regulation required by you and your students will, at first, be daunting, but is sure to be more easily accommodated as you proceed. Education has never been for the faint-hearted.

It seems to me that these cautionary (but exciting) words were more true a year ago than they are today. The increased focus on testing and credentialing feels like a step backwards. In sum, two technology-related movements that could have served different educational purposes, and could have enriched each other and improved learning, are getting lumped together much too soon.

The lowest common denominator? Measurement and testing. Not exactly new or revolutionary.

Edwards Deming said that “the most important things cannot be measured.” I wonder about the direction of this association: Can attempts to measure important things render them unimportant?