(Originally published on pbk.com September 2017)
For over a decade authors as diverse at Frans Johansson (The Medici Effect – https://www.fransjohansson.com/books-by-frans-johansson/), Daniel Pink (A Whole New Mind – http://www.danpink.com/books/whole-new-mind/), and Steven Johnson (Where Good Ideas Come From – https://stevenberlinjohnson.com/where-good-ideas-come-from-763bb8957069) have argued that innovation comes from a diverse approach to solving problems. This either means developing a broad educational approach within a given individual or bringing together diverse people in a collaborative setting. As Johansson says in Medici, “Leonardo da Vinci, the defining Renaissance man and perhaps the greatest intersectionalist of all times, believed that in order to fully understand something one needed to view it from at least three different perspectives.”
The industrial age was one of specialization and our schools reflect this. Instead of Da Vinci’s dictum that you have to apply a broad spectrum of views to any particular subject, the educational world for the last century has been one of increasing specialization. The further you go up the educational ladder, the more specialized this gets. But even at the lower grades there is usually separation between “art” and “math,” for instance. These distinctions are the product of the industrialized educational system that purports to prepare our students for specific careers that require specialized and in-depth knowledge of a particular subject. Alan Kay shows just how siloed thinking undermines the learning process in this TEDtalk from 2007.
The problem is compounded by magical thinking. Arthur C. Clarke once stated, “Any sufficiently advanced technology is indistinguishable from magic.” This is exactly what has happened to our relationship with technology. Most users have no idea how it works or why it works the way that it does. The same is true for most technologies in schools (and is becoming worse as technological systems become more complex). It is common for schools to approach technology as something expensive that needs to be protected from the students. It is also separated from instruction in the sense that it is used to facilitate certain kinds of experiences but is rarely the focus of instruction itself. As a result, both students and teachers tend to view technological systems as black boxes rather than as learning opportunities.
The struggle to align the educational world with technological realities is a direct product of the specialization that has characterized our educational experiences for a century or more. Is coding a technical subject taught in a Career and Technical Education environment? Is it an exercise in mathematics and logic best taught by engineers? Most controversially, should coding be taught as a foreign language class? The answer is all three and yet our curriculum insists on trying to insert it into traditional boxes that don’t really create effective coders. Good coders have to understand logic and the basic technical limitations of the various languages but also need to be able to speak to the machines in a natural way. These kinds of people are incredibly sought after in the technology world but our systems do a very poor job of producing them. And coding is only the first level of the problem. To get to an iPhone-level device you have to integrate coding with hardware engineering and design (and ultimately entrepreneurship). You need a multidisciplinary approach to practically any problem these days.
How do we work toward a system that creates these kinds of thinkers? One way to do this is to create environments where it is okay to experiment. In the 1950s early computer scientists at MIT and elsewhere often came from the model railroading community. Model railroads are complex electrical switching systems so the transition was a natural one. Bundles of wires often had to be cut, or hacked, and reconfigured in order to make a system work. This was true in computing as well. This is where we get the term “hacker.”
Over the last 20 years this term has returned to its definitional roots through technology spaces that allow users to build, break, and repurpose technologies. Advanced tools such as 3D printers and laser cutters have been added to the mix to allow the rapid fabrication of prototypes. Microcomputers such as Raspberry Pi’s and Arduinos provide rapid access to electronic brains. Hackerspaces, and their more commonly referred to cousin MakerSpaces, have started making their way from community spaces into education. It is not always a natural fit.
MakerSpaces go against the grain of the industrialized educational model. Like coding, they raise questions about where they belong. Viewed purely as a set of tools they can augment traditional programs in Career and Technical Education or the Fine Arts. In higher education they are most commonly placed in the context of engineering or other STEM-based programs. While these programs can greatly benefit from the access to these technologies, it is only through broad access that the true potential of developing the next generation of Da Vinci’s can be realized.
If he were a young student today Steve Jobs might never have had access to this technology because he wasn’t an engineer. Fortunately, he had access to Steve Wozniak, who was an engineer. Together they developed what was to become Apple Computer, an early example of blending computing with design. MakerSpaces offer the opportunity of developing diverse kinds of communities within our schools. However, they can only reach their true potential if they are built with those goals in mind and are accessible and visible to the entire student body, not just those who are technically inclined. As a resource area like a library they can provide a vital bridge for students from a specialized, industrial-focused curriculum and the realities of a post-industrial age. If they are tucked away supporting specialized programs and/or are invisible they are as useful as a library of unread books.