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.

## Tiada ulasan:

## Catat Ulasan