Insight learning was first developed by Wolfgang Kohler (1887-1967). This theory of learning differs from the trial and error ideas that were proposed before it. The key aspect of insight learning is that it is achieved through cognitive processes, rather than interactions with the outside world. There is no gradual shaping or trial and error involved; instead, internal organizational processes cause new behavior.
Sultan the Chimpanzee and Insight Learning
Kohler's most famous study on insight learning involved Sultan the chimpanzee. Sultan was in a cage and was presented with a stick. He could use the stick to pull a piece of fruit close enough to the cage so that he could pick it up. After Sultan had learned to use the stick to reach the fruit, Kohler moved the fruit out of range of the short stick. He then placed a longer stick within reach of the short stick. Initially, Sultan tried to reach the fruit with the short stick and failed. Afterwards, Sultan looked around, used the short stick to reach the long stick, and used the long stick to reach the fruit. Sultan was never conditioned to use one stick to reach another; instead, it seemed as if Sultan had an epiphany. The internal process that lead Sultan to use the short stick in order to reach the longer stick instead of the fruit, is a basic example of insight.
Differences Between Insight Learning and Other Learning Theories
A basic assumption of the learning perspective is that only behavior that can be seen may be studied, and that human behavior is determined by conditioning. Insight learning suggests that we learn not only by conditioning, but also by cognitive processes which cannot be directly observed.
Initially, it was thought that learning was the result of reproductive thinking. This means that an organism reproduces a response to a given problem from past experience. Insight learning does not directly involve using past experiences to solve a problem. While past experiences may help the process, an insight or novel idea is necessary to solve the problem. Prior knowledge is of limited help in these situations, and learning occurs through cognitive processes.
Insight problems are tasks that may involve insight and require something new and non-obvious to be done. In most cases, they are difficult enough to predict that the initial solution attempt will be unsuccessful. When solving a problem of this kind, the researcher often has a so called "AHA!" experience or "Eureka" moment. This occurs when the solution pops up all of a sudden after there were no ideas about how to answer the problem, and no progress was being made. An example of this type of problem is the chain task (Figure 1). To see the solution to this problem, see below.
Insight v. Heuristics
Insight should not be confused with heuristics. A heuristic is a mental shortcut that allows us to filter out overwhelming information and stimuli to make a judgement or decision. Heuristics help us to reduce the cognitive burden of the decision-making process by examining a smaller percentage of the information. While both insight and heuristics can be used for problem solving and information processing, a heuristic is a simplistic rule of thumb, or habitual automatic thinking that frees us from complete and systematic processing of information.
Insight is not a mental shortcut, but instead arriving at a novel idea through cognitive means. Rather than being habitual or automatic, insight involves coming up with a new idea that does not result from past experience to solve a problem. While heuristics are gradually shaped by experience, insight is not. Instead, internal processes lead to new behavior. An example of this is the realization of how to solve the chain task from above. The solution (Figure 2) involves the realization that instead of linking the four chains directly, a single chain can be broken to connect the other three.