A problem is any situation that differs from a desired goal. There are well-defined goals and abstract goals. Well-defined goals have a clearly defined given state, a finite set of operators (rules), and a clear goal state. Ill-defined problems do not have specific states, rules or in certain situations clear goals. The Gestalt Principle is one way that problems can be solved it is a systematic problem solving that involves restructuring and representing the information in a different way. Insight is different that productive problem solving, which just reproduces past problem solving, instead it is a product of new and non-obvious sudden problem solving. When objects are presented in a way that displays their traditional function it makes insight much harder as is seen with the match box example. This and the water-jug task show the effects of functional fixidness and mental sets.
There are general problem solving strategies and domain general strategies. The first type of general problem solving was studied by Herbert Simon through his work with computer problem solving demonstrated that every problem is composed of initial, intermediate and goal states. The intermediate state is search or how we navigate from the initial and goal states. This intermediate state or search can be organized or it can be trial and error. One type of problem solving is a means-end analysis which finding a way to see what means lead to an end, with in this strategy sub-goals maybe used to reach the end goal. Sometimes working backward from the end shows possible sub-goals which allow us to the solve the problem. Analogies are another general problem solving strategy in which we describe similar structures and interconnect them to clarify and explain certain situations, but these are not overly generalizable and are often used by experts. Analogical problem solving depends on noticing an analogical connection, mapping the corresponding parts of the two problems, and applying the mapping to generate a parallel solution to the target problem. Schema are another way to conceptualize problems, but they are not a fool proof way to solve problems. Experts on the other hand know more about their field, they organize the problems differently, and they spend more time analyzing the problems. Chase and Simon showed that experts know more as they found that experts are able to reproduce the positions of the chess pieces on the chessboards better than novices, but only when they were actual game positions. Others have shown that experts organize their data differently. It has also been shown that physics professors and students group problems based on different criteria. The professors grouped them based on their deep structure and the students grouped them on more basic features. Experts also spend more time working on a problem.
In the article Functional Fixedness in a Technologically Sparse Culture, German and Barrett explored the role of function fixedness in a low technology culture. Human created objects are generally represented in the brain by the artifacts' mechanical properties, design, purpose or function. We represent them by the goals we have when we use that object. We have different knowledge about artifacts that we do about natural objects, specifically we know more about their specific purpose/design, their mechanical properties, and their goals for use. Studies show that by 6 years old we begin represent objects in our mind by their function. With these classifications come functional fixedness, this causes us to solve a problem slower when the designed function is primed immediately prior to the problem than when the design function is not demonstrated. German and Barrett investigated whether functional fixedness would be observed among people exposed to fewer artifacts that are technologically simpler and that are pressed into a greater variety of uses than is typical in an industrial society. They looked to see if people in nonindustrial societies may have more bricolage or more technological flexibility, could they put unusual things together, or could they improvise better. In the experiment Shuar adolescents were randomly assigned to the function-demonstrated condition of the baseline condition. They were given two task one building a tower using and box and blocks, and one using a spoon to make a bridge. They found that those in the function-demonstration condition were slower to select the box than the baseline, but the solution time was the same. For the spoon task those in the function-demonstrated condition slower times to both select the spoon and complete the task. These results show that subjects in the nonindustrial technology sparse culture were susceptible to functional fixedness just like those in an industrial nation. These results also indicate the representation of artifacts in the mind based on there function is universal.
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