Sources of Knowledge: Stickiness and the Chasm Between Theory and Practice.

Like all sources, it helps to know the origin and the purity.

My head is still full of my current crop of research papers and, while I can’t go into details, I can discuss something that I’m noticing more and more as I read into the area of Computer Science Education. Firstly, how much I have left to learn and, secondly, how difficult it is sometimes to track down ideas and establish novelty, provenance and worth. I read Mark Guzdial’s blog a lot because Mark has spent a lot of time being very clever in this area (Sorry, Mark, it’s true) but he is also an excellent connecter of the reader to good sources of information, as well as reminding us when something pops up that is effectively a rehash of an old idea. This level of knowledge and ability to discuss ideas is handy when we keep seeing some of the same old ideas pop up, from one source or another, over time. I’ve spoken before about how the development of the mass-accessible library didn’t end the importance of the University or school, and Mark makes a similar note in a recent post on MOOCs when he points us to an article on mail delivery lessons from a hundred years before and how this didn’t lead to the dissolution of the education system. Face-to-face continues to be important, as do bricks and mortar, so while the MOOC is a fascinating new tool and methodology with great promise, the predicted demise of the school and college may (once again) turn out to be premature.

If you’ve read Malcolm Gladwell’s “The Tipping Point”, you’ll be familiar with the notion that ideas need to have certain characteristics, and certain human agents, before they become truly persuasive and widely adopted. If you’ve read Dawkin’s “Selfish Gene” (published over a decade before) then you’ll understand that Gladwell’s book would be stronger if it recognised a debt to Dawkins’ coining of the term meme, for self-replicating beliefs and behaviours. Gladwell’s book, as a source, is a fairly unscientific restatement of some existing ideas with a useful narrative structure, despite depending on some now questionable case studies. In many ways, it is an example of itself because Gladwell turned existing published information into a form where, with his own additions, he has identified a useful way to discuss certain systems of behaviour. Better still, people do (still) read it.

(A quick use of Google Trends shows me that people search for “The Tipping Point” roughly twice as much as “The Selfish Gene” but for “Richard Dawkins” twice as much as “Malcolm Gladwell”. Given Dawkins’ very high profile in belligerent atheism, this is not overly surprising.)

Gladwell identified the following three rules of epidemics (in terms of the spread of ideas):

  1. The Law of the Few: There are a small group of people who make a big difference to the proliferation of an idea. The mavens accumulate knowledge and know a lot about the area. The connectors are the gregarious and sociable people who know a lot of other people and, in Gladwell’s words, “have a gift for bringing the word together”. The final type of people are salespeople or (more palatably) persuaders, the people who convince us that something is a good idea. Gladwell’s thesis is that it is not just about the message, but that the messenger matters.
  2. The Stickiness Factor: Ideas have to be memorable in order to spread effectively so there is something about the specific content of the message that will determine its impact. Content matters.
  3. The Power of Context: We are all heavily influenced by and sensitive to our environment. Context matters.

Dawkins’ meme is a very sticky idea and, while there’s a lot of discussion about the Selfish Gene, we now have the field of memetics and the fact that the word ‘meme’ is used (almost correctly) thousands, if not millions, of times a day. Every time that you’ve seen a prawn running on a treadmill while Yakity Sax plays, you can think of Richard Dawkins and thank him for giving you a word to describe this.

My early impressions of some of the problem with the representation of earlier ideas in CS Ed, as if they are new, makes me wonder if there is a fundamental problem with the stickiness of some of these ideas. I would argue that the most successful educational researchers, and I’ve had the privilege to see some of them, are in fact strong combinations of Gladwell’s few. Academics must be, by definition, mavens, information specialists in our domains. We must be able to reach out to our communities and spread our knowledge – is this enough for us to be called connectors? We have to survive peer review, formal discussions and criticism and we have to be able to argue our ideas, on the reasonable understanding that it is our ideas and not ourselves that is potentially at fault. Does this also make us persuaders? If we can find all of these “few” in our community, and we already a community of the few, where does it leave us in terms of explaining why we, in at least some areas, keep rehashing the same old ideas. Do we fail to appreciate the context of those colleagues we seek to reach or are our ideas just not sticky enough? (Context is crucial here, in my opinion, because it is very easy to to explain a new idea in a way that effectively says “You’ve been doing it wrong all these years. Now fix it or you’re a bad person.” This is going to create a hostile environment. Once again, context matters but this time it is in terms of establishing context.)

I wonder if this is compounded in Computer Science by the ability to separate theory from practice, and to draw in new practice from both an educational research focus and an industrial focus? To explain why teamwork actually works, we move into social constructivism and to Vygotsky, via Ben-Ari in many cases, Bandura, cognitive apprenticeship – that’s an educational research focus. To say that teamwork works, because we’ve got some good results from industry and we’re supported by figures such as Brooks, Boehm and Humphrey and their case studies in large-scale development – that’s an industrial focus. The practice of teamwork is sticky, that ship has sailed in software development, but does the stickiness of the practice transfer to the stickiness of the underlying why? The answer, I believe, is ‘no’ and I’m beginning to wonder if a very sticky “what” is actually acting against the stickiness of the “why”. Why ask “why?” when you know that it works? This seems to be a running together of the importance of stickiness and the environment of the CS Ed researcher as a theoretical educationalist, working in a field that has a strong industrial focus, with practitioner feedback and accreditation demands pushing a large stream of “what do to”.

It has been a thoughtful week and, once again, I admit my novice status here. Is this the real problem? If so, how can we fix it?

 



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