518 Procedural Memory and Skill Acquisition
visual search skill. Contrary to the results of Cooke et al.,
Fisk and Hodge did not find good retention of varied-
mapping search. The major difference in the two studies is
that the performers in the Cooke et al. study showed evidence
of automaticity at the end of the initial learning of the task,
whereas those in the Fisk and Hodge study did not. It appears
that a shift in strategy, or simply the effects of overlearning,
has significant consequences for retention.
MODELING SKILL
Although response selection is the locus of learning in many
tasks, it was argued above that response selection does not
become automatic in the sense that, after learning, stimuli au-
tomatically trigger the correct response without regard to the
nature of the relationship between stimulus and response.
This finding is at odds with one of the most developed mod-
els of practice effects, the chunking hypothesisof Newell and
Rosenbloom (1981; Rosenbloom & Newell, 1987). The
model assumes a production-system architecture in which
stimuli are related to responses by means of rules (e.g., “if the
mapping is incompatible and the right light is on, find the key
opposite to the light and press it”). The chunking hypothesis
predicts that performance will improve as a function of prac-
tice and that the learning curve will follow a power function.
Learning occurs by means of pattern-recognition processes
whereby increasingly complex patterns of stimuli and re-
sponses are learned. In other words, learning is based on the
chunking of stimulus and response patterns. Although it pre-
dicts the general pattern of improvement in simple tasks quite
well, it contains no provision for long-lasting effects of fac-
tors such as stimulus-response compatibility.
Many models of learning have been based Anderson’s
(1982, 1993) production system architecture. Productions
have several properties that are consistent with empirical
generalizations about skill, such as transfer based on com-
mon elements. The independence of productions, the all-or-
none learning reflected in their creation and their accrual of
strength, and potential abstraction make them an appropriate
vehicle for the elements of learning.
Many neural network, or connectionist, models of learn-
ing have also been developed, although their scope has usu-
ally been rather limited. For example, J. D. Cohen, Dunbar,
and McClelland (1990) developed a model of the Stroop ef-
fect based on the strength of learning to read words versus
name colors. The model provides a demonstration of how the
strength of learned associations between stimuli and particu-
lar types of responses can produce automatic behavior.
Unfortunately, the model has been shown to be rather limited
in scope, working in its particulars only when the maximum
number of stimuli is two (Kanne, Balota, Spieler, & Faust,
1998).NEW DIRECTIONSAs in other areas of cognitive psychology, we can expect to
see an increasing number of studies devoted to attempts to
discover where in the brain learning occurs. We can expect
that such studies will continue to shed light on issues such as
the nature of procedural and episodic memory or whether sep-
arate systems underlie implicit and explicit learning. Just as in
other areas, the degree to which this knowledge helps us to
understand the processes by which skills are acquired remains
to be seen. Increasingly, more emphasis is being placed not
just on what is learned, but on what is not learned. Ohlsson
(1996), for example, has proposed a theory of learning based
on making mistakes in which what is not learned at one time
becomes the basis for what is learned at another time.
Unskilled performance is characterized by ignorance of
what to expect, what to do, or when to do it; lack of knowledge
of interrelationships among variables and of what information
is relevant; difficulty in combining information; insensitivity
to relevant sensory or perceptual discriminations; and a lack
of production proficiency. Progress has been made in under-
standing how these relations, skills, and proficiencies are ac-
quired as a function of experience, and in understanding what
sorts of experiences lead to the greatest improvements. The
future of research in skill acquisition is as broad and as bright
as in all of cognitive psychology. We can expect to see many
more questions, and answers, as to the nature of the processes
that allow the aforementioned changes to occur.REFERENCESAckerman, P. L. (1988). Components of individual differences
during skill acquisition: Cognitive abilities and information
processing.Journal of Experimental Psychology: General, 117,
288–318.
Ackerman, P. L. (1992). Predicting individual differences in com-
plex skill acquisition: Dynamics of ability determinants. Journal
of Applied Psychology, 77,598–614.
Allard, F., & Starkes, J. L. (1980). Perception in sport: Volleyball.
Journal of Sport Psychology, 2,22–33.
Allard, F., & Starkes, J. L. (1991). Motor-skill experts in sports,
dance, and other domains. In K. A. Ericsson & J. Smith (Eds.),
Toward a general theory of expertise: Prospects and limits
(pp. 126–152). New York: Cambridge University Press.