Futurists continue to stress that our future is going to undergo change at a rate
even greater than present generations have experienced. This implies that
today’s and future problems will have a dynamic component. Such problems
change or evolve as they are being studied. It is evident then that a
fundamental skill for dealing with the future is active problem solving, i.e., the
ability to solve problems which are undergoing change during the process of
resolution.
Problem solving can be divided into two categories, routine and nonroutine:
Routine problem solving stresses the use of sets of known or prescribed
procedures (algorithms) to solve problems. The strength of this approach is
that it is easily assessed by paper-pencil tests. Since today’s computers and
calculators can quickly and accurately perform the most complex arrangements
of algorithms for multi-step routine problems, the typical workplace
does not require a high level of proficiency in routine problem solving.
However, today’s workplace does require many employees to be proficient in
nonroutine problem solving.
Nonroutine problem solving,
stresses the use of heuristics and
often requires little to no use of
algorithms. Unlike algorithms, heuristics
are procedures or strategies
that do not guarantee a solution to a
problem but provide a more highly
probable method for discovering the
solution. Building a model and drawing
a picture of a problem are two
basic problem-solving heuristics.
Other heuristics include describing
the problem situation, making the
problem simpler, finding irrelevant
information, working backwards, and
classifying information.
There are two types of nonroutine
problem solving situations, static and
active: Static nonroutine problems
© Copyright 1980, 1986, 1992, 2004; by Pentathlon Institute, Inc. Mary Gilfeather & John del Regato
have a fixed known goal and fixed, known elements that are used to resolve
the problem. Solving a jigsaw puzzle is an example of a static nonroutine
problem. Given all pieces to a puzzle and a picture of the goal, learners are
challenged to arrange the pieces to complete the picture. Various heuristics
such as classifying the pieces by color, connecting the pieces which form the
border, or connecting the pieces which form a salient feature to the puzzle,
such as a flag pole, are typical ways in which people attempt to resolve such
problems. Active nonroutine problem solving may have a fixed goal with
changing elements, a changing goal or alternative goals with fixed elements,
or changing or alternative goals with changing elements. The heuristics used
in this form of problem solving are known as strategies. People who study
such problems must learn to change or adapt their strategies as the problem
unfolds.
The Mathematics Pentathlon® program
provides experiences in thought processes
necessary for active problem
solving. The five Pentathlon games
within a two-grade division level rely to
a great extent on the use of strategies.
The series of 20 games which comprise
the Mathematics Pentathlon provide
students with experiences in deductive
and inductive reasoning through
the repeated use of sequential thought as
well as nonlinear, intuitive thinking. Such
forms of thought are directly related to
real-life problem-solving situations. Furthermore,
the increased use of simulation
games in business, industry, government
and education involves these types of thinking
skills. Also, the field of robotics and an
ever-growing number of technologies require
such abilities.
A Chart summarizing the differences between routine and nonroutine problem solving
can be found by clicking on the link titled “Problem Solving Chart” found on the home
page.
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