Karl Hayo Siemsen
Learning by Gestalt
A team was selected, some people with an understanding of mathematics, some
engineers and myself – maybe a gestalt psychologist. This team brings to mind
the ideas and cooperation between Eino Kaila, the Nevanlinna family and their
PhD students Ahlfors and Kurki-Suonio. All members of the team agreed that
the main task was to optimize our mathematics lessons for engineering students.
This is normally a hard task with a high dropout rate. We had to admit we would
fail, if we continued the conventional strategy.
Ahlfors had made a general proposal, influenced by Nevanlinna, Kaila, Wittenberg,
Polya, Kline and Wertheimer (Fig. 1):
Hadamard: “The object of mathematical rigor is to sanction and legitimize the
conquests of intuition, and there never was any other object for it.”
5. Genetic method. “It is of great advantage to the student of any subject to
read the original memoirs on that subject, for science is always most completely
assimilated when it is in the ascent state.” wrote James Clerk Maxwell. There
were some inspired teachers, such as Ernst Mach, who in order to explain an
idea referred to its genesis and retraced the historical formation of the idea. This
may suggest a general principle: The best way to guide the mental development
of the individual is to let him retrace the mental development of its great lines, of
course, and not the thousand errors of detail.
This genetic principle may safeguard us from a common confusion: If A is logically
prior to B in a certain system, B may still justifiably precede A in teaching,
especially if B has preceded A in history. On the whole, we may expect greater
success by following suggestions from the genetic principle than from the purely
formal approach to mathematics. (Italics highlighting by author)
Fig. 1 Some excerpts from Ahlfors: On the mathematics curriculum.
The proposal was influenced by Ernst Mach (not by Ernst Mach the physicist,
but by other, less known aspects of Mach “in the same body”). We traced his
approach and ideas, carefully transferring them to the present time. As engineers
we analyzed the traditional linear model of learning, found many strategic errors