Thinking and Deciding

42 THE STUDY OF THINKING
Training and debiasing
One way to test a prescriptive theory about thinking is to try to improve it through instruction
and then show some effect of the instruction on something else. This avoids
the problem of looking for correlations between good outcomes and good thinking.
Such correlations can result when the outcomes and the thinking are both influenced
by the same factors, such as general mental ability. Training studies can use a control
group, which is not trained, so that any later differences between the trained group
and the control group can be ascribed to the training. Another advantage of these
studies is that it often leads to a promising educational technique. These studies are
also called “debiasing” because they attempt to reduce a bias.
Transfer of learning is the effect of learning in one situation on learning or behavior
in a very different situation. If we are teaching thinking, transfer is essential.
Because thinking (as defined in this book) is what we do when we do not know
what to choose, desire, or believe, thinking will be most essential in situations that
we have not encountered before. Can teaching of thinking transfer? A number of
studies suggest that it can.
Some studies have examined the effects of certain courses on reasoning about
judgments and decisions. Schoemaker (1979) found that students who had taken
a statistics course gave more consistent answers to questions involving choices of
gambles. Students who had not taken the course were also more likely to bid more
than the maximum amount that could be won in order to play a gamble in which
money could be won, and more likely to require more money than the maximum
loss in order to play a gamble in which money could be lost.
Fong, Krantz, and Nisbett (1986, experiment 4) found that statistical training
transfers to solving everyday problems involving statistical reasoning. Half of the
men enrolled in a college statistics course were interviewed by telephone at the beginning
of the course, and the other half were interviewed at the end. The interview
(conducted by a woman experimenter) ostensibly concerned sports and began with
questions concerning sports controversies (such as what colleges should do about
recruiting violations) in order to hide the fact that the basic concern was with statistics.
Then subjects were asked such questions as why the winner of the Rookie of
the Year award in baseball usually does not do as well in his second year as in his
first. A nonstatistical response might be “because he’s resting on his laurels; he’s not
trying as hard in his second year.” A statistical response (based on the principle of
regression to the mean in numerical prediction explained in Chapter 15) would be “A
player’s performance varies from year to year. Sometimes you have good years and
sometimes you have bad years. The player who won the Rookie of the Year award
had an exceptional year. He’ll probably do better than average his second year, but
not as well as he did when he was a rookie.” Students gave more good statistical
answers of this sort at the end of the course than at the beginning. Therefore, these
students did transfer what they had learned to cases where it is relevant.
Nisbett, Fong, Lehman, and Cheng (1987) carried out other studies in which they
examined the effects of various kinds of university instruction on statistical, logical,