The “cure” for Baumol’s cost disease and what it might mean for education and MOOCs

Many discussions of education reform make reference to Baumol’s Cost Disease, an economic theory which seeks to explain why costs rise in industries, like health care and education, which are resistant to efficiency gains. Essentially it argues that costs will rise rapidly in sectors that are labor intensive because wages must rise to attract workers in a competitive labor market, but the labor intensive nature of the enterprise keeps productivity from keeping up with gains in other sectors that are more amenable to automation.

Baumol did his original research on the performing arts. pointing out in the 1960’s that it takes the same number of people the same number of person-hours to perform a string quartet as it did a century ago.  While that’s true, the actual cost to hear music is much lower than it was.  Why?…recordings.

While most people accept that listening to a recording is not the equal of the live concert experience, most people listen to more recorded music than live music.  The combination of lower cost (buy MP3’s of a string quartet once for $4 and listen as many times as you want) and convenience (even in the largest of cities there isn’t a live performance of the piece you want to hear whenever you want to hear it.)  mean that recorded music is, for most people, good enough. (See also Walter Benjamin’s “The Work of Art in the Age of Mechanical Reproduction“)

Here is a parallel to education. Most would accept the premise that a small class with lots of interactions is better than a class of hundreds in which most assignments are graded by computer.  The latter model, in particular, does not lend itself to higher level thinking skills without very careful design.  The proponents of what Lisa Lane would call Network based MOOCs Would likely counter that network effects and opportunities for learner autonomy create an environment that is in some ways preferable to a traditionally structured class, even if that class is small and interactive. However, the network based MOOC is not driven by measurable outcomes, and it’s unclear how this might fit in to a credential. When early network based MOOCs were offered for credit, there was a cohort within the class.  for that cohort, which was small, more traditional assessment methods were used (journals, projects, etc.)

Any kind of redesign of education which would significantly increase the productivity of teachers will likely involve significant automation of content delivery and, more importantly, assessment.  The key question is, will learners accept a course where most assignment feedback is machine generated as good enough?  I think this will most likely depend on whether a credential earned via low cost, massive, machine graded courses is perceived to have economic and employability benefits comparable to the traditional labor intensive approach.

Interestingly, Baumol apparently argues in a new book (I haven’t read it) that the “disease” is not , in fact, a big problem, because decreases in the cost of other things will offset the inevitable cost increases in education, health care, and other labor intensive sectors. I’m skeptical. I guess we will all see in a decade or so.

 

 

The Limits of Sensemaking

As I pondered this week’s task on design elements, I was drawn back to a post Jenny Mackness made last week on the science of teaching, or perhaps that should have been the science of teaching science.

Rather than my trying to summarize her summary of a conference presentation, I’ll give the x sentence tl;dr

  • Presenting/demonstrating is ineffective, especially when dealing with complex concepts.
  • Class time should instead be used for sense-making, where students are presented with situations and collaboratively create and discuss hypotheses about what will happen next.
  • Confusion is actually a good thing.

Eric Mazur, the Harvard physicist in question, describes the whole process as “teaching by questioning rather than by telling.” As I mentioned previously. I very much like the idea of a questioning centered classroom. However, Mazur’s work, which is centered around teaching science, raises another question. In a science lab (and here I’m talking about the lab component of an intro course as opposed to a research lab) what happens should be predictable. Whan you set up a scenario and ask a question, there is a right answer.

When you teach human systems (languages, arts, economics, etc.) you can create suce certainty by using very carefully chosen examples that “follow all the rules”. How well does that prepare students for the much less tidy real world?

On the other hand…..

Lisa linked to an Atlantic article, that served as the start point for a debate about teaching writing, contrasting the writer’s workshop approach with one that makes grammar and mechanics more explicit. My most interesting takeaway from this was a reminder of the importance of background knowledge. The students at New Dorp had internalized fewer rules of high-level language structure than had their peers, and teachers found more success when those rules were taught explicitly.

This is an issue that many of us who teach at community colleges face every day. Students don’t come to us with the background knowledge we hope they will have. If we are teaching a subject like art history or physics, which they may have never studied formally before, the gap between what they know and hat we wish they knew may be even larger. If these students are left to do much of their own sensemaking, they can become confused to a fault, not knowing what to do and suffering intellectual paralysis as they wait for someone to tell them. Sometimes they wait without asking or telling us they are lost.

Do we then go back to an instructional model full of explicit knowledge presentation? After all, it’s what many of our students are quite used to. How does that interface with the need for them to develop their own sense making skills, a goal which is probably more important that the material we strive to cover in our survey classes? Also, how does that sensemaking take place when the patterns you are trying to uncover are arbitrary by definition?

Course Design the Google Way

Today, Google announced the availability of Course Builder, an open source platform for delivering online courses. Among the wiki pages is an outline of Google’s course design process. As you read it, what pedagogical assumptions do you think it embodies? On a quick first glance, many of those assumptions seem to me to be implicit rather than explicit. How does this outline compare to the process of exploring our own pedagogical preferences we’re doing this week.