Excerpts from an interview with Alan Cooper and Chris Noessel by Theory and Practice
Theory and Practice began the interview with two large questions.
Igor Gladkoborodov: In your blog you write a lot about the specifics of the post-industrial era. The new economy heavily influences all aspects of human life, and now we are entering an era of post-everything. I am most interested in the aspect of education, what can you say about the post-education era?
Anton Gladkoborodov: In the industrialized world, education was reduced mainly to the technology of working with a tool or a machine. Similarly, mental activity was usually reduced to a set of algorithms. Today, we need to raise another kind of worker, one that is more flexible and dynamic. However, modern education does not meet the requirements of modern times; it is still based on the principle of factories. What, in your opinion, needs to be done to education?
It’s a good, long conversation, and if you’re down with the Russian you can read the original at the Theory and Practice website. (Special thanks to our friends at Innova for providing the source translation for us.) Below we’ve excerpted some of the most interesting stuff, and arranged it so we don’t sound as jetlagged and meandering as we actually were.
Rote memorization vs. Skills
Chris: …I think we should perceive education not simply as the transmission of a set of information useful for tests, but rather as a set of skills that will come in handy for the rest of our lives. I don’t think that this assertion will come as a surprise to anyone who has studied eductional theory. The notion that education is cramming as much information as possible into a child’s head is antiquated. We have more information than we know what to do with. Now we need skills to get the right information and to know what to do with it. I think the emphasis should be placed on fostering those skills, so that the child can successfully participate, work, and create in the adult world.
Alan: Information is needed to reveal a pattern, but after you see the pattern, information is not important anymore. In this way, information is kind of like scaffolds, helping you to build something new. I love axioms and empirical methods, but I think that in order to understand them, you have to fully grasp their meaning and context. When you try to explain this principle to another person, you fail most of the time. You have to give that person some kind of a guiding idea, let him go from start to finish and arrive at the conclusion all by himself. Then he will say: “Now I understand this method, I know how it is connected with the information.” At this stage, in order to install the system, the method becomes a substitute for the process of passing data. That’s why I believe that modern education should be largely based on the knowledge of and ability to recognize these patterns. The old concept is all about committing the information to memory.
After that, you have to learn how to identify the system on the basis of this data. It would be interesting to introduce a new history course with an overview of different patterns that existed in different historical periods, instead of talking about facts.
I believe that all of this can be reduced to the problem of seeing things as a dichotomy of wrong and right. Your position on this scale is not really important. What really matters is whether you make any progress or not.
Chris: Progress implies that you are on a correct path and that you’re moving in the right direction along that path, but there are many paths. A person’s effectiveness should be a measure of education.
Anton: We have this notion that we begin to learn when we’re a child and finish learning when we are about 25 years old, but in reality, it is necessary to acquire knowledge all the time.
Alan: Learning is a continuous process, a lifelong process.
Building a first draft list of information-age competencies
Chris: So if gathering and processing information are skills, then one of the other important skills that a person should learn in school is “metacognition”, the ability to evaluate what you’re doing and how well you’re doing with tasks, in order to be able to reflect on, evaluate, and improve your work. You must also be able to work together with others. Other important skills would include ideation, the ability to work effectively in a team, the knowledge of how to carry out a task in a certain amount of time (a day, a week or even a year), in addition to rote skills and tool use for a given trade. Also self-direction and self-assessment. When you are able to assess your own performance, you’ll know in which direction you need to develop further.
Alan: There are so-called cognitive skills that are used in the process of acquiring knowledge. What’s the difference between fast and slow learning? You may think, “Is this the right way to do it? Perhaps, I should use a different tactic in order to solve this problem; for example, to finish a chapter of a book or to make a presentation?” Teamwork facilitates this process, as you have to somehow share your ideas with the members of your team so that they could evaluate it. I believe that collaborative projects will form the basis of the post-education world.
Anton: Education should teach us that there’s always room for mistakes. When a pupil in school makes a mistake, he usually gets a low grade, but perhaps, this is wrong. A person learns by making mistakes.
Chris: So yeah, failure is a key skill. I’d also name such methods as analogy, analysis, deconstruction, systems thinking, and pattern recognition. I would also put an emphasis on such concepts as ontology, epistemology, and healthy skepticism.
Alan: I would also add collaboration, human skills, interaction.
Chris: Representation and demonstration.
Alan: Yes, demonstration and something I would call reflection — the ability to objectively analyze and criticize, especially when it comes to one’s own work. You should be able to say: “I failed, but I learned something” without fear.
Chris: All methods of education should help us minimize the effort needed to get knowledge and focus on the development of our knowledge skills, which, of course, weren’t disregarded before, but still appeared to be less important (especially a generation ago) than knowledge. The ability to build taxonomies and think hierarchically are major new competencies.
Programming as a core competency
Chris: As an undergraduate student I studied typography. One thing I got out of it was that when you look at some text, printed in columns, through blurred eyes, you can easily see the so-called “rivers” of spaces between the words that distract from reading. In essence, this method of blurring your eyes is an attempt to get rid of unnecessary details in order to see the patterns in the system itself. We need tools to do this with the modern glut of information.
For example, what do we see if you try to visualize all of Shakespeare’s works? There are many different ways to do it, each of which help us see different patterns. What if we represented all of the nouns in the plays as red pixels and all of the verbs as blue pixels, does anything emerge? We don’t have easy tools to help us to this sort of thing, to easily represent huge arrays of information in new forms, in one place, as one symbol, for the sake of analysis. Programming is the best tool we have, and so it should be taught.
Alan: Then I would add two more things to our list — the unique nature of software and the unique nature of humanity.
There are a lot of studies on cognitive psychology, evolutionary psychology, behaviorial psychology. Many discoveries were made about people’s behavior, cognitive illusions, and things such as fundamental errors of attribution. All that knowledge was ignored for many years. Hitler, during his time, advanced this field of science, some devilish psychology indeed. He believed in what he called eugenics, a sort of racial discrimination. The Nazis used it to justify horrible things, experimenting on people, just horrible.
So some modern fields of science, concerning human behavior, came to us from a really bad person. Fascists actually changed the course of research studies towards evolutionary psychology for as many as 75 years. The studies of Sigmund Freud and other scientists have influenced this development quite a bit. Freud was a brilliant thinker who really contributed great to researching things like taxonomy and psychology. Many of his ideas, models and studies concerning the human mind were debunked or proved to be wrong. Even up to now, the work of many researchers on cognitive psychology and evolutionary psychology is threatened, pressured by radicals and antifascists.
People have a fundamental character that influences the way they think, and it’s quite understandable. I think it’s very important, especially for interaction designers, to study things like cognitive illusions or the free nature of knowledge in order to use them in the line of work.
Anton: Game design relies on the laws of psychology and understanding of the human nature in order to motivate people to play.
Alan: I also mentioned the unique nature of software. I’m still trying to explain the idea of “low and slow.” Software greatly differs from anything that we know. For hundreds of thousands of years, mankind progressed and evolved in a world surrounded by physical objects composed of atoms. Only 50–60 years have passed since the day we started using programs and virtual objects, and in this time, we couldn’t possibly develop an instinctive attitude towards them, we didn’t have enough time to evolve and adapt to the nature of software. That’s why anything that concerns software is counterintuitive. What seems obvious and natural about it is wrong.
I began studying programming in the early 70s, and at that time, there was almost no collaboration. Everything existed in the form of very energetic rival teams, it was a real old-school, industrial age. It was then that the cascade model was developed, we invented the death march. Almost all of those projects ended in failure, more than half of them closing right after the start. 15–20 years later, the thought that we are actually ahead of everybody dominated the software industry. We understood that software developing was a promising sector, although time-consuming and ineffective. We knew that we could do better and never really considered, in our constant failures, that we were actually building the entire software industry. When we managed to create a piece of code that actually worked, it was mere coincidence! For me, this is proof that the most involved practitioners at least understood the unique nature of the program. And now, we have these crazy ideas like pair programming.
Anton: It was so strange to see two programmers working in a pair; it seemed they were just wasting their time.
Alan: At first glance, that’s how ‘Low and slow’ seems to be. When two programmers are working together on one computer, we eliminate the process of modification and debugging. It’s more effective to have good code, which was developed slowly, than a badly written fast one.
Many people believe that they need something functional or that they want what is cheaper, but that’s not the case, otherwise Mercedes Benz could not sell a single car. After all, there are cars with the same attributes but cheaper price on the market. However, one thing is true, people don’t want to feel cheated, nobody wants to pay more than they have to. People are willing to pay twice for a product that they like, as long as they don’t feel cheated. They must feel satisfied, or they can’t trust the product or its developer.
Originally published at www.cooper.com on December 21, 2011.