In 1944, President Roosevelt attributed the coming victory over the Axis to America’s scientific leadership in the development and application of innovative technologies to war. He envisioned that it was important that the same efforts should continue during the coming peace. The vision was that American institutions like schools would improve their practices by the implementation of innovative technologies.
But history has shown that institutions like schools are prone to adopt potentially innovative technologies, not to innovate, but to continue to do traditional work only more efficiently.
When computers entered education its adopters were quick to use the “innovative” technology to serve the traditional purposes of schools—the transmission of knowledge from teacher/computer to student.
In the 1960s a Stanford University collaboration with IBM led to the introduction of “computer-aided [or assisted] instruction (CAI) into some elementary schools. A mainframe computer delivered “a linear presentation of information with drill and practice sessions.” (Arnold, 2000)
Even when the personal computer was introduced in the late 1970s the idea that in addition to their usefulness in playing games, entertainment, keeping recipes, and banking, they could also play a role in schools.
In place of the live teacher there would a computer program that would dole out information to the students. It would even automate the checks for “understanding” by administering quizzes and tests. Learning was defined as a change in behavior; learning was correctly choosing the right answer to the given question. A correct choice would elicit a pleasant chime; a wrong one would result in a harsh buzz.
On the other hand, there were factors that pushed institutions to rethink the uses of innovative technologies.
The advent of the computer itself was a catalyst for change.
In 1940 Alan Turing had created “Colossus” a computer that made it possible for the British to read the German military’s “unreadable” Enigma code. If reading secret code by a computer was possible, could they learn to do other human-like tasks?
Searching for answers to this question drove changes in computer science, linguistics, anthropology and psychology, and led to the development of the new field of cognitive science.
The launch of Sputnik in 1957 by the Soviets motivated Americans to look critically at the business as usual in science and mathematics instruction, leading to a flowering of innovative mathematics and science curriculum that was published during the decades following.
The new curriculum materials added “critical thinking” and problem-solving” to the traditional school agenda. This focus got educators to begin looking seriously at the previously ignored work of Jean Piaget on how the minds of very young children matured in response to the environments in which they lived.
The currents that supported changing how schools worked: the cognitive revolution, child development, computational technologies, and reform curriculum come together in the person of Seymour Papert.
Two doctoral degrees in mathematics, four years of work with Piaget in Geneva, an engineering professorship at MIT, work with Marvin Minsky at MIT’s Artificial Intelligence Lab, extensive work with children in Brookline, Massachusetts, and his own personality grounded his views that a computer could be a learning tool for children who would program it rather than a teaching machine that would program children. (Stager, 2016)
A technology is embodied knowledge. A pry bar used to lift a rock is the physical embodiment of the ratio of output forces to input forces.
This means that you can “deconstruct” the action of the pry bar back to the science behind it.
In an autobiographical reflection Seymour Papert tells about his early childhood fascination with the differential gearbox of a car. His playful turning of one gear made another turn in a different direction. He saw how a small gear would need to turn many times in order for a larger gear to turn once. Later, when he was in elementary school and met the multiplication tables he thought to himself that they were simply “my gears” in a different form. A small gear with nine teeth turns a larger gear with thirty-six teeth. The little gear will need to turn four times in order for the large gear to turn once so that each of the nine teeth contact each of the thirty-six teeth. His affection for the gears now included the multiplication tables. (Papert, 1980, p.2)
When he discovered that “some adults—even most adults—did not understand or even care about the magic of gears, he wondered why what was “so simple for him to be incomprehensible to other people?” He rejected his father’s suggestion that the difference was “being clever.”
“Slowly I began to formulate what I consider the fundamental fact about learning: Anything is easy if you can assimilate it to your collection of models. If you can’t, anything can be painfully difficult.” (Papert, 1980)
Children’s learning is supported by an environment that is rich resources from which children can build models.
It was for this reason that he and colleagues developed the LOGO language in 1967 at MIT. It was designed to provide tools to help children construct their own models and elaborate others on their own.
Using the LOGO language even young children can create models that they can use to assimilate new understandings with older ones, just as young Seymour assimilated his gears with the multiplication tables. In place an “empty model” like the verbal definition of a square, the child can “walk” the square along with the turtle he directs with LOGO.
“The effect of work with Turtle geometry on some components of school math is primarily relational or affective: Many children have come to the LOGO lab hating numbers as alien objects and have left loving them. In other cases, work with the Turtle provides specific intuitive models for complex mathematical concepts most children find difficult. The use of numbers to measure angles is a simple example.” (Papert, 1980, p. 32)
Seymour Papert passed away on July 31, 2016, at age 88.
Arnold, D. N. (2000). Computer-Aided Instruction. Retrieved from http://encarta.msn.com
Bilikstein, P. Seymour Papert’s Legacy: Thinking About Learning, and Learning About Thinkinig. Retrieved from https://tltl.stanford.edu/content/seymour-papert-s-legacy-thinking-about-learning-and-learning-about-thinking
Novak, M. (2012). Predictions for Educational TV in the 1930s. Retrieved from http://www.smithsonianmag.com/history/predictions-for-educational-tv-in-the-1930s-107574983/?no-ist
Papert, Seymour (1980). Mindstorms: Children, Computers, and Powerful Ideas. Retrieved from http://www.arvindguptatoys.com/arvindgupta/mindstorms.pdf
Stager, G. S. (2016). Seymour Papert (1928-2016). Nature, 537(7620), 308. doi:Obituary
personal computers, LOGO, Jean Piaget, Marvin Minsky, Sputnik, child development, cogntive science, Artificial Intelligence
1 Commodore PET, Radio Shack TRS-80, and Apple ][ all appeared in 1977