Mental models and understanding technology

Sun May 23 19:49:55 GMT 2004 Mental models and understanding technology

When you are trying to learn a system, whether a second language, an application, or an operating system, you develop mental models of how you think the system works: if you do A, you expect B. If you don't get B, you revise your model and perhaps experiment more to see why you had it wrong. Some people are very good at this process, some are not, but all of us have the skill to some degree or another. When teaching someone else, you try to impart a good working model, but it is often even more important to understand what your student's model is. Seeing that they are not understanding is easy enough, but seeing what possible models could lead them to that misunderstanding can give you a better idea of how to help them to a more accurate understanding.

There are, unfortunately, people who seemingly don't work this way at all. These are the rote memorizers, the people who just want lists of rules. If their memory skills are exceptional, they can function nearly as well as someone who relies on comprehension more than memory. Of course we all rely on memory too, and people who have both good modeling skills and good memory have the easiest learning path. I personally find it difficult to teach the rote memorizers when they make very little use of analogs and models.

On the other hand, people who develop poor models also can be frustrating, particularly when their models lack consistency and are grossly contradictory. To a certain extent, we all encounter contradictions as we learn, and resolving those inconsistencies is what helps us refine and improve our understanding. Yet, some people seem remarkably untroubled by "facts" that obviously cannot stand together. Part of "intelligence" is the ability to link cause and effect chains: to be able to see that if A affects B, and C affects D, then if changing D also causes a change in A, a change in C will affect B. How far an individual can trace such chains will affect their ability to develop good mental models of systems, so the degenerative case of not noticing A and B being in conflict means very poor modeling indeed. If there is no compensation from rule memorization, teaching such people can seem completely impossible.

I was reminded of this the other day while trying to help someone configure a pair of VPN routers. The ISP hadn't helped by issuing one set of addresses and then changing their mind a week later, and it also didn't help that the person I was dealing with was obviously tired and distracted by other issues. The problem he had was that he didn't understand the concept of internal and external addresses, my problem was that I couldn't figure out what his mental model of the Internet was. It was obvious that he misunderstood everything at a very fundamental level, and was being led to very wrong conclusions, but I just couldn't grok where he left the path. For example, after we had basic internet connectivity working (but not the VPN), he wanted to try the "wrong" addresses that the ISP had given him previously. In my world, it is "obvious" that you have the right address in the router because you have basic connectivity, and that's all you need for a VPN: there aren't addresses that are "good" or "bad" for use with a VPN (disregarding the possibility of firewall interference). I just could not (and still cannot) envison a model where that would not be true, so I was unable to help him to a better understanding. We did get the VPN's working, but I don't think he'll be able to do this on his own, and that was part of our goal.

Leaning can be hard, but sometimes teaching is even more difficult.

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