Human Thinking and Problem Solving

The research on human problem solving has presented a number of strategies we can use in order to reach a solution. Present a detailed examination of these strategies alongside a critical exploration of the key barriers that may stand in the way of the individual solving a problem.

Human thinking and problem solving have been a subject of research in psychology since the old ages and for a very long time (Davis, 1966). Various methods of study have been used in order for researchers to understand how human mind works and how individuals develop their way of thinking and simultaneously, people developed several different ways to perceive and carry out steps in order to solve a problem. Problem solving is a mental process and considered to be one of the higher levels of cognitive processes. In 1966, Gary A. Davis stated in one of his studies that research in human problem solving has gained a good reputation for being the most disorderly of all recognizable categories of human learning. Problem solving includes both mathematical and personal problems and people go through almost every kind of problem in their lives seeking for a solution that fits. Peoples’ ultimate goal is to overcome the obstacles and barriers, so, they form some strategies in order to reach their goal. The best strategy for solving a problem depends on the specific situation that the individual is located and problem solving involves discovering, analysing and solving problems. In every problem there is no obvious way or path of reaching the goal, solution or best result and both the level of difficulty and the goal of the problem are important.

Most problems can be described and separated into three major parts, the goal state which is the desired end point of the problem solving activity (Ashcraft, 2008), the initial state which is where an individual begins to solve a problem, and the operators which are the mental actions that can be exerted to the problem so that people can proceed from initial state to the goal state. Considering these components, and as problem solvers, individuals go through an amount of stages to find a solution to a problem. This essay will present and undergo through a critical exploration of the strategies that people use to reach their goal and the obstacles that may stand in this procedure.

When solving a problem, perception is an important thing and individuals have to make sure to recognize and understand the actual problem. Representing the problem in their memory is a part of mental process as well as considering relevant information that applies to the present problem. Moreover, identifying various aspects of the problem and evaluating alternatives is also very important and helps to the procedure of reaching the ultimate goal and apply solution. Problem solving is not a flawless procedure and barriers make the process of solving slower and sometimes inefficient. One of the strategies that has been used much and is still used in problem solving is algorithms. Many people would find a connection between algorithms and heuristics but the truth is that they are two completely dissimilar techniques. An algorithm is a set of rules and the procedure of solving a problem using algorithms has to be produced step by step. Algorithms always give the right solution to the problem but even if an algorithm guarantees an accurate answer and it is consistently right, it is not always the best approach to human problem solving and it could make the process very hard to the individual. Solving a problem while using algorithms can be extremely time consuming and this is not practical for many situations. For example, if someone was trying to figure out the possible number combinations to a safe using an algorithm, it would take a vast amount of time.

Algorithms are usually used in computer programs and development of computer systems in order to be able to perform tasks just like humans do. This is known as Artificial Intelligence. But the difference is that artificial intelligence is not like human intelligence and it is not fully related to human problem solving (Neisser, 1963). There are differences which are inevitable and those differences cause negative analogies as well as sources of human inconsistency cause negative analogies too, because they are not represented in computer programs (Elithorn & Jones, 1972).

On the other hand, heuristics is an approach to problem solving which employs an imperfect method but is a sufficient strategy for the immediate goals. There are many problems for which algorithms do not exist. In the absence of an algorithm, problem solvers must use a heuristic instead of algorithms, a general problem-solving strategy that may or may not produce a successful outcome and that means that heuristics do not always work. Unlike algorithms, heuristics do not always guarantee a correct solution or answer, however using this problem solving strategy does allow individuals to simplify complex and difficult problems and decrease the total number of possible solutions to a more achievable and reasonable set. Rubenstein et. al 1960, supported that the use of a wide variation of signs is obtained from the structure of the problem and general experience with related problems appears to be significant in human problem solving. Heuristics can be applied to mathematical problems as well as problems in peoples’ everyday lives in a generally simple way such as observation or in a mathematical problem by using a pencil and paper.

An example of a heuristic problem solving technique is means-end analysis and it is used for limiting search. The problem solver within this technique starts by visualizing the goal of the problem and in that point determines the best strategy (Ashcraft, 2006). The learner identifies a pathway to the solution and sets up a goal or a sub-goal while he or she is looking for the difference between the current state and the goal state. Furthermore, as all problems have operators, the problem solver seeks for an operator that eliminates the difference between the two states and applies this operator. An example of means-end analysis is the Tower of Hanoi problem, which is a well-defined problem. Well-defined problem means that the initial and goal state as well as the operators, the individuals need to use, are clear and understandable. The Tower of Hanoi needed no special training and the task was to move all of the rings from peg A to peg B, with as less as moves as a person could. The problem solver could move only one ring at a time and he or she could not place a larger ring on the top of a smaller one. Also, rings could only be placed on the pegs and not anywhere else. In this sort of problem, all of the information needed to solve the problem was in the initial state.

Another strategy for problem solving is the Insight one. As the name says, the solution to a problem in insight strategy can appear as a sudden insight. According to researchers, insight is when a problem cannot be solved using conventional methods (Metcalfe & Wiebe, 1987) and the problem solver realizes that the solution involves unusual methods and that the problem needs restructuring (Wertheimer et. al., 1959). Insight is usually an unconscious process and the behaviour towards problem solving is driven by internal factors (Sternberg & Davidson, 1995; Bowden, 1997) and it may happen if the problem solver realizes that the problem is alike to another problem that they have dealt in the past.

One of the barriers that can also be combined or linked with the insight strategy is the mental set. Mental set is the tendency that people have to solve certain problems in a secure way based on previous solutions to similar problems (Luchins & Luchins, 1959). According to a study that has been conducted by Michael Ã-llinger, Gary Jones, and Günther Knoblich in 2008, about mental set, people only use solutions and process of solving the problem that have worked in previous times while dealing with same problems rather than looking for substitute ideas. A mental set often works as a heuristic strategy, making it a useful problem solving implement. However, mental sets can also lead to inflexibility, making it more complex and inefficient to find solutions that fit and they do not tend to be correct. Functional fixedness is one kind of mental set and it is likelihood for an individual with functional fixedness to view problems only in their “normal” way. Functional fixedness is an obstacle that prevents people from seeing in every way all of the various and different options that might be available to find a solution.

Gestalt psychologist Karl Duncker (1945) made a cognitive performance test known as the “Candle Problem” in his effort to measure the influence of functional fixedness in problem solving. The experiment was pretty simple as participants had to find a way to tie and fix one candle on the wall in order to not drop onto the table, using a book of matches and a box of thumbtacks. The solution to this problem was to empty the box of thumbtacks, use them to pin the box to the wall and put the candle in. The result was that minimum participants tried to use the box of thumbtacks to put the candle in because of their fixation about the box. The functional fixedness did not allow them to use the original box of thumbtacks as a candle-holder.

Functional fixedness and insight can be somehow linked. Maier’s (1931) two-string problem showed a hint of functional fixedness. This problem requires the individual to tie two hanging strings together although the one cannot be reached while the other one is held. The insight comes when individual realizes that an object like the hanging string, can be attached to one string and then that string can be swung. In Maier’s study with the two-string problem, less than 40% of the participants solved the problem without any clue.

There are always barriers when people are trying to solve a problem and another one of them is irrelevant or misleading information. When solving a problem it is very important to distinguish and separate the relevant and irrelevant data about the problem. Irrelevant information will possibly lead to false solutions and wrong answers and when a problem is very complex it logically becomes easier for the individual to focus on misleading information. Moreover, assumptions which people make when dealing with a problem, where they make assumptions about the barriers that prevent certain solutions.

In conclusion, barriers and obstacles are always associated with problem solving and no one can solve a problem easily or at least without using some strategies. Most of the time the solution is extremely simple and people cannot imagine this. Every individual has to follow the appropriate steps in order to reach their goal and there are several strategies which can be used. The essay discussed about the differences between the strategies about human problem solving that individuals utilize and the obstacles that they have to overcome in order to arrive to their ultimate goal. People must try finding a link that will help them solve the problem in a logical way and not always thinking about complex procedures and solutions. Individuals have the ability to overcome the barriers that stand in their way and this is gained with experience and exploration.

References

Adamson, R. E. (1952). Functional fixedness as related to problem solving: A repetition of three experiments. Journal of Experimental Psychology, 44(4), 288-291.

Davis, G. A. (1966). Current status of research and theory in human problem solving. Psychological Bulletin, 66(1), 36-54.

Elithorn, A., & Jones, D. (1973). Artificial and human thinking: [proceedings of the NATO symposium on human thinking – computer techniques for its evaluation, held at st Maximin, France, 17-20 august, 1971].

Ã-llinger, M., Jones, G., & Knoblich, G. (2008). Investigating the effect of mental set on insight problem solving. Experimental Psychology, 55(4), 269-282.

Pylyshyn, Z. W. (1963). Search strategy and problem structure in heuristic problem-solving. Canadian Journal of Psychology/Revue canadienne de psychologie, 17(3), 291-301.

Cherry, K. (2016, August 31). How do we solve problems? The strategies we use & obstacles we face. Retrieved February 15, 2017