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Seymour rejected the computer-aided instruction approach in which “the computer is being used to program the child” and argued for an alternative approach in which “the child programs the computer.”
“technocentric” (a term that Seymour popularized). That is, the initiatives focus too much on helping children develop technical skills: how to use a 3d printer, how to define an algorithm, how to write efficient computer code.
Seymour’s constructionism theory adds a second type of construction, arguing that children construct knowledge most effectively when they are actively engaged in constructing things in the world.
But, still, I believe that Seymour would be very frustrated with the approach of today’s ai-in-education efforts. Seymour was interested in applying ideas from ai to engage children in thinking about their own thinking—and learning about their own learning. Most of today’s ai-in-education initiatives have a very different set of goals, focusing on the use of machine intelligence, rather than the understanding of human intelligence.
Seymour provocatively argued for “projects over problems.” Of course, Seymour understood the importance of problem solving. But he believed that people learn to solve problems (and learn new concepts and strategies) most effectively while they are actively engaged in meaningful projects. Too often, schools start by teaching concepts to students, and only then give students a chance to work on projects. Seymour argued that it is best for children to learn new ideas through working on projects, not before working on projects.
“Education has very little to do with explanation, it has to do with engagement, with falling in love with the material.”
In the forty years since Mindstorms, the changes have been more evolutionary than revolutionary. Many of Seymour’s dreams have been unfulfilled.
Slowly I began to formulate what I still consider the fundamental fact about learning: Anything is easy if you can assimilate it to your collection of models. If
modern-day Montessori might propose, if convinced by my story, to create a gear set for children. Thus every child might have the experience I had. But to hope for this would be to miss the essence of the story. I fell in love with the gears. This is something that
Something very personal happened, and one cannot assume that it would be repeated for other children in exactly the same form.
One might say the computer is being used to program the child. In my vision, the child programs the computer and, in doing so, both acquires a sense of mastery over a piece of the most modern and powerful technology and establishes an intimate contact with some of the deepest ideas from science, from mathematics, and from the art of
intellectual model building.
Difficulty with school math is often the first step of an invasive intellectual process that leads us all to define ourselves as bundles of aptitudes and ineptitudes, as being “mathematical” or “not mathematical,” “artistic” or “not artistic,” “musical” or “not musical,” “profound” or “superficial,” “intelligent” or “dumb.” Thus deficiency becomes identity and learning is transformed from the early child’s free exploration of the world to a chore beset by insecurities and self-imposed restrictions.
These “math-speaking” adults do not necessarily know how to solve equations; rather, they are marked by a turn of mind that shows up in the logic of their arguments and in the fact that for them to play is often to play with such things as puzzles, puns, and paradoxes.
The conditions necessary for the kind of relationships with a computer that I will be writing about in this book require more and freer access to the computer than educational planners currently anticipate. And they require a kind of computer language and a learning environment around that language very different from those the schools are now providing.
