THE USE OF KNOWLEDGE IN PROBLEMS SOLVING
Marizete Rodrigues da Costa & Adriana Benevides Soares
Universidade Gama Filho – Programa de Pós-Graduação em Psicologia
Rua Manuel Vitorino, 533 – 20740-280 Rio de Janeiro – R. J.
Thought, the only ability that separates man from the rest of the animal kingdom is
understood by authors Eysenk and Keane (1996) in its properties of character, extension, nature,
and quantity of knowledge used in different problem solving tasks. They state that only the
thought presupposes awareness; however, we should remember that usually we are aware of the
thought’s product instead of the thought’s process in itself. Eysenk and Keane emphasize that the
thought tasks differ regarding to the quantities of knowledge used: it can be minimum knowledge
or intense knowledge. Finally, they suggest that the knowledge can vary its direction in situations
of minimum knowledge that involve specific goals.
Therefore, the objective of this article is that day to day thought situation can involve a
complex mixture of solving problems, reasoning and decision making.
A historical review of the use of knowledge in solving problems can be searched by two
different approaches. The first, during 50’s and the beginning of the 60’s began with the followers
of the Gestalt school of psychology who theorized that animals as well as human do not solve
their problems by a “mere” reproduction of learned reactions; but they involve insight and
restructuring. This statement suggests that a subtle tip results in reorganizing the problem in a
way that produces a solution.
According to Gestalt’s theorists, using past experiences in problem solving generally leads to
failure rather than success, in other words, when people use past methods routinely or assume
that the object should be used in their habitual form in general they lose their way.
In reaching the desired goal by using knowledge, obstacles and facilitators will arise. One of
the obstacles is functional fixation; it consists of a fixation on normal function of an object, which
makes it difficult to think of its use in different functions. Facilitators give an overview, which allow
us, use more complex methods, such as restructuring, insight and transference by analogies. This
position, according to the gestalts, represents thought in dynamic aspects that goes beyond a
reproductive thought. This school of thought left an important legacy of experimental materials
and evidences for the theory of procession information. The emphasis on a natural orientation to
non-associated goals of thought, furnished material for the process information approach.
On the whole, the Gestalt theory can be condensed to the follow terms:
 Problem solving behavior is as reproductive as productive;
 The resolution of reproductive problem solving involves a re-use of previous experiences
and can ruin a successful solving problem solution, by the functional fixation which follows
a successful solution;
 The resolution of productive problem solving is characterized by insight of the structure of
the problem and by the productive reconstruction of the problem;
 Insight frequently occurs suddenly and is followed by the “ah-há!” expression.
The second historical approach was the theory of information processing. It tried to explain
the finding of the initial research, allowing a general evaluation of the progress on problem solving
research. In this approach, researchers Allen Newell and Herbert Simon (1972), of CarnegieMellon University, contributed to the development of this theoretical outline. By the end of the
50’s, they produced computerized models of psychological phenomenons and accomplished
epics findings in the cognitive psychology and artificial intelligence. The spacial theory on problem
solving created by them (retold in Human Problem Solving) remains the center of problem solving
research.
Basically, the theory of information processing characterizes problem solving is like an inner
search and being lead through a variety of possible alternatives. This search is guided by various
heuristic methods, or practical rules, that coordinates the appliance of many operators used in the
transformation from one state to the next. A detailed organization of these aspects is:
* People’s behavior on problem solving can be observed as a production of steps of
knowledge by the application of mental operators, moving from an initial state toward a goal state;
* The operators classify the regular movements allowed and the restrictions that explicitly
obstruct a movement if certain conditions are applicable;
* For every kind of problem there is a great number of alternative routes from an initial state
to a goal state; the group of these states, created by the regulatory operators, is called the basic
space of the problem;
* A certain problem could have a large number of alternative possibilities; people use
strategies or heuristics methods to move efficiently from the state to the goal state.
Heuristics methods create practical rules that guarantee a solution for the problem, but if
they are successful, they will save time and effort.
All these process occur within a specific cognitive system, in other words, there might be
limitations related to memory work and the speed that this information can be stored and
recuperated from long-term memory.
Consequently, performance improves as we get closer to the important goals/sub goals and,
it shows difficulty when is far from an important goal.
Divide the problem into many simple sub problems, to solve each one at a time, leads a
person to learn different strategies, becoming more efficient in problems solving.
The way we understand a problem should have an important effect on if we are able to solve
the problem:
- Problems with the same structure (isomorphic) will have meaningful effects in the solving
ability;
-The application of rules, such as alteration or the movement of problem influences the
solving complexity, which means, that the facility of learning and applying rules, come from actual
knowledge or inherent memory charge to the ease of problem solution;
-The structure of the problems presentation affects the use of knowledge in its solution.
Problems that are well structured, with a well defined path towards the solution, where the
operators, in which initial state and goal state are clear and precise, the subjects tend to have a
little specific knowledge about it, using general and heuristic knowledge. Badly structured
problems, sub specified in many ways, demand the use of substantial quantity of specific
knowledge of control, because they become better structured by the use of knowledge they show
an obscure and unavailable way of solution.
One of the main differences between well-defined problems like puzzles and badly defined
problems, but an everyday thing, is the quantity and specificity of knowledge brought to the
problem’s situation.
The strength of the information processing theory is its success in accomplishing
predictions; its weakness is manifested by the limited scope of problems situation, which was
already applied.
The nature of knowledge was also examined in researches of skill, confirming that
differences in knowledge result in behavioral varieties between learners and experts. Someone
who is, for example, beginning to learn Physics needs a considerable amount of knowledge, in
relation to another person, who has the same mental capacity who has been studying Physics for
many years. One main characteristics of the cognitive performance is that people become better
with experience. They become experts and manifest what is generally called specialty or
expertise. Recent attempts were made to extend the cognitive theories of problem solving and
memory of understanding Human expertise. Distinguished differences regarding quantity and the
type of knowledge of experts and beginners have been shown by this research through chess
games, problem solving in Physics and computer programming. There are elaborated theories
and many times computed generated model on knowledge acquisition in these areas. One
example is J.R. Anderson (1982; 1983; 1987a) who created a general theory of ability acquisition
as part of his cognitive architecture ACT (Adaptive Control of Thought), which can be used in
learning abilities under a variety of different domains of expertise.
Besides the research on differences regarding beginner/expert, many other research lines on
problem solving examined creative resolutions solving analog problems. Sometimes we can have
creative solutions even if we don’t have a previous knowledge related to this specific problem.
How do we achieve that? According to Walla (1926), some behaviors and reactions organize and
facilitate the problem solving. They are:

Preparation: Preliminary attempts are done on the problem that is being considered and
formulated;

Incubation: the problem is put aside to work on other tasks;

Enlightment: the solution comes as a sudden insight;

Verification: the person who is trying to solve the problem tries to verify that the solution
actually works.
Research on problem solving is one of the most important lines of investigations for
Cognitive Science. We can see that this area is distinguished by the traditional empirical research
with an alliance to the construction compute generated models. This data is important to evaluate
the success of these approaches and to explain what has been learned. Therefore, the question
is: Is knowledge the key?
The key to our actual understanding of the problem solving lies in what we believe to be
knowledge’s role. In this article, we can see that the essential task performed by the researchers
was to capture the different types of knowledge that people need in problems solving. Actually, we
can conclude that the problem solving methods can be classified in regards to quantity, specificity
and knowledge possession.
solving: *
Carbonell
(1986) suggests the following diagram for problems
General Plan Methods
Weak
c
d
Specific Plans
a
New Problem
b
Old Problems solved
(a) Specific plans are installed (b) the use of a problem previously encountered applying it to the
actual problem, (c) General plans are applied to reduce the problem, (d) Apply weak methods
to heuristically investigate a possible solution, or (e) Use a combination of all these steps.
We can conclude that the researchers suggested many different types of knowledge are
used in problem solving task. People can use a combination of different methods to solve a
specific problem. Although, the key is that the different methods of problem solving can be
distinguish by the amount and types of knowledge that are used.
BIBLIOGRAPHY
EYSENCK, M. W. & KEANE, M. T. (1996) - Psicologia cognitiva. Porto Alegre: Editora Artes
Médicas.
POZO, J.I. (1998) - Teorias cognitivas da aprendizagem. 3. ed. Porto Alegre: Editora Artes
Médicas.
STERNBERG, R. J. (2000) - Psicologia cognitiva. Porto Alegre: Editora Artes Médicas.