Who is Herbert Simon?
Herbert Simon was one of the great scholars of the twentieth century, whose discoveries and inventions ranged from political science (where he began his career) to economics (in which he won a Nobel Prize) to computer science (in which he was a pioneer) and to psychology.
Simon was one of the towering intellectual figures of the twentieth century. He wrote a classic on decision making in organizations while still in his twenties, and among many other achievements he went on to be one of the founders of the field of artificial intelligence, a leader in cognitive science, an influential student of the process of scientific discovery, a forerunner of behavioral economics and, almost incidentally, a Nobel laureate in economics.
Those quotations are both taken from Daniel Kahneman’s Thinking, Fast and Slow. Kahneman is himself a Nobel Laureate for his work on decision making. Kahneman goes on to say of Simon that he is
perhaps the only scholar who is recognized and admired as a hero and founding figure by all the competing clans and tribes in the study of decision making.
As well as the fields which Kahneman lists, Simon also made some contributions to education. Of particular significance for primary and secondary educators is this paper, which Simon wrote with John Anderson and Lynne Reder in 2000, shortly before he died in 2001. It is about mathematics education, but it has applications for all subjects. It is strikingly critical of some very popular educational practices and recommends other practices which frequently get a bad name. For example:
He criticises authentic, real-world learning tasks.
Contrary to the contention that knowledge can always be communicated best in complex learning situations, the evidence shows that: A learner who is having difficulty with components can easily be overwhelmed by the processing demands of a complex task. Further, to the extent that many components are well mastered, the student wastes much time repeating these mastered components to get an opportunity to practice the few components that need additional effort. There are reasons sometimes to practice skills in their complex setting. Some of the reasons are motivational and some reflect the skills that are unique to the complex situation. While it seems important both to motivation and to learning to practice skills from time to time in full context, this is not a reason to make this the principal mechanism of learning.
He defends drill, in the face of criticisms that it drives out understanding
This criticism of practice (called “drill and kill,” as if this phrase constituted empirical evaluation) is prominent in constructivist writings. Nothing flies more in the face of the last 20 years of research than the assertion that practice is bad. All evidence, from the laboratory and from extensive case studies of professionals, indicates that real competence only comes with extensive practice.
He rejects discovery learning, and praises teacher instruction
When, for whatever reason, students cannot construct the knowledge for themselves, they need some instruction. The argument that knowledge must be constructed is very similar to the earlier arguments that discovery learning is superior to direct instruction. In point of fact, there is very little positive evidence for discovery learning and it is often inferior (e.g., Charney, Reder & Kusbit, 1990). Discovery learning, even when successful in acquiring the desired construct, may take a great deal of valuable time that could have been spent practicing this construct if it had been instructed. Because most of the learning in discovery learning only takes place after the construct has been found, when the search is lengthy or unsuccessful, motivation commonly flags.
Simon is also critical of the state of education research.
New “theories” of education are introduced into schools every day (without labeling them as experiments) on the basis of their philosophical or common-sense plausibility but without genuine empirical support.
We see that influential schools have arisen, claiming a basis in cognitive psychology… but which have almost no grounding in cognitive theory and at least as little grounding in empirical fact. This is particularly grievous because we think information-processing psychology has a lot to offer to mathematics education.
So, for instance, in the 1993 draft of the NCTM assessment standard for school mathematics, we find condemnation of the “essentialist view of mathematical knowledge” which assumes “mathematics consists of an accumulation of mathematical concepts and skills” (p.12). We can only say we find frightening the prospect of mathematics education based on such a misconceived rejection of componential analysis.
He is also optimistic that the findings of cognitive psychology can offer a basis for a better understanding of teaching and learning.
Human beings have been learning, and have been teaching their offspring, since the dawn of our species. We have a reasonably powerful “folk medicine,” based on lecturing and reading and apprenticeship and tutoring, aided by such technology as paper and the blackboard–a folk medicine that does not demand much knowledge about what goes on in the human head during learning and that has not changed radically since schools first emerged. To go beyond these traditional techniques, we must follow the example of medicine and build (as we have been doing for the past thirty or forty years) a theory of the information processes that underlie skilled performance and skill acquisition: that is to say, we must have a theory of the ways in which knowledge is represented internally, and the ways in which such internal representations are acquired. In fact, cognitive psychology has now progressed a long way toward such a theory, and, as we have seen, a great deal is already known that can be applied, and is beginning to be applied, to improve learning processes.
Anyone working in the field of evidence-based education needs to consider Simon’s work and this article very seriously.