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Researched
and Composed by
Jacob Wilson, BSc. (Hons), MSc. CSCS and
Gabriel “Venom” Wilson, BSc. (Hons), CSCS
Abstract
Specificity can be fractionated into several discrete categories. These
include Sensory Specificity, Context Specificity, Pattern Specificity,
Rate Specificity, Resistance Specificity, and Processing Specificity.
The purpose of this article was to review each of these categories.
Introduction
The previous articles discussed the theoretical rationale for Henry’s
(1958) Specificity of Learning hypothesis. Thorndike’s and Woodworth’s
(1901) Identical Elements of Transfer Theory suggested that the transfer
of training from one task to another would occur proportionally to the
amount of shared elements between tasks. Hull’s (1943, 1952) theory
would suggest that the elements were performance variables such as the
lighting in the environment, and internal states such as arousal of an
organism. Therefore practicing in one environment could predict
performance in another environment proportionally to the similarity of
conditions. Guthrie (1950, 1952) suggested that these elements were
numerous bonds between environmental and internal stimuli which could
initiate the desired response. These bonds represented the acquisition
of skill, and were specific to the situation they were acquired in.
Therefore, Guthrie (1950, 1952) suggested that learning was specific to
each situation, and that the learner should therefore practice in as
similar a situation as possible to the desired criterion goal. Finally
the most current and dominant theory for Specificity was provided by
Henry (1958). He suggested that each Motor Task required a large
collection of underlying attributes, which supported the task. By
changing the task participants would change the underlying attributes
supporting that task. As with previous theories, transfer of training
occurred only in so much as the underlying attributes of the task were
similar. In this context, the purpose of this paper was to identify the
broad variables which determine the similarity of the elements, bonds,
or attributes which underlie any two tasks. These variables or types of
specificity include Sensory Specificity, Context Specificity, Pattern
Specificity, Rate Specificity, Resistance Specificity, and Processing
Specificity.
Sensory
Specificity
Work by Adams (1971) led Proteau (1992) to propose the Specificity of
Practice Hypothesis, which suggests ‘that learning must be specific to
the sources of afferent feedback used to guide one's movement during
practice (Trembley and Proteau, 1998).’
In greater detail Proteau (2001) posits that ‘ learning appears to be
specific to the sources of afferent information used to ensure optimal
accuracy during practice; and when that information is withdrawn in a
transfer test, performance suffers because the individual has no
reliable source of reference with which to evaluate his or her
movement.’ In this context ‘ learning involves a sensorimotor
representation that integrates the motor components with the sensory
information available during practice (Schmidt and Lee, 1999).’
Therefore performance on transfer will be proportional to the similarity
of those conditions to that of the practice conditions.
In this context Proteau, Marteniuk, Girouard, and Dugas (1987)
investigated the effect of increased practice on the reliance on visual
information. They had participants practice an aiming movement for 200
or 2,000 trials under either a full-vision condition or a condition in
which they could see only the target to be reached (target-only
condition). After acquisition, both the visual and target only
conditions performed under target only conditions. It was found that
notably greater errors in performance were found in the condition that
originally performed with vision. However, what was most interesting
was that the error was greater in the 2,000 trial condition than the 200
trial condition. This suggests that as practice continues, participants
become more and more reliant on the sensorimotor representation.
Even more intriguing was a study by Proteau, Marteniuk, and Levesque
(1992). They examined the effect of adding vision to a group, which had
practiced under target only conditions. Results indicated that the
addition of vision actually degraded performance! This also provides
evidence that Specificity increases as a function of practice.
It is therefore critical to consider that there are numerous afferent
sources of feedback that are provided by internal and external
environments. The source, which allows the participant to succeed
optimally, will have the greatest influence on the sensorimotor
representation created. Trembley and Proteau
(1998) has refined his hypothesis further to state that learning is
specific to the source(s) of afferent information which permit(s) one to
obtain optimal performance during practice ( See, Proteau, 1992 for a
full review of supporting evidence). This has several practical
implications. For example, investigations which study elite athletes’
use of afferent information can determine which source of information
best determines an optimal outcome for those elites. This information
could be utilized to accelerate participants along the learning curve at
a much more rapid rate by causing them to focus immediately on that
information.
Context
(Environmental) Specificity
Context Specificity is a concept, which suggests that transfer from one
environment to a second environment in the execution of a criterion task
will be proportional to the similarity of the cues between the two
environments. To clarify, Wright and Shea (1991) state that there are
two broad forms of stimuli within the Context of a situation. The first
are known as Intentional stimuli and are defined as stimuli essential
for achieving the criterion task. The second, denoted incidental
stimuli are defined as stimuli not directly associated with completion
of the task, but that have the potential to become associated with
specific tasks due to their selective presence in the learning
environment. An example of intentional stimuli may be the sight of a
moving target in a tracking task, where as incidental stimuli could be
background noise such as music, temperature, or fragrance.
Context Specificity falls underneath Guthrie’s (1952) theory of learning
discussed previously. Guthrie (1952) proposed that a behavior was
triggered by specific incidental stimuli. Hergenhan and Olsen (2005)
summarize by stating that ‘Guthrie’s advice is always to practice the
exact behaviors that are going to be demanded of us; in addition we
should practice them in the exact conditions under which we are going to
be tested or evaluated. If we want to utilize this information beyond
the testing situation, we must go beyond the classroom and associate
other stimuli with the behavior that the book or class or lecture caused
us to do.’ Therefore learning is not only a matter of practicing the
task, it is also a matter of forming bonds or associations between that
behavior and incidental stimuli. Guthrie (1942) summarizes by
suggesting that ‘we learn what we do in the presence of specific
stimuli.’
Voeks (1950) who studied under Guthrie’s theory developed four
postulates based on its predictions. Postulate 1 is known as the
Principle of Association and states that ‘ Any stimulus pattern that
once accompanies a response…becomes a full strength direct cue for that
response. This is the only way in which stimulus patterns not now cues
for a particular response can become direct cues for that response.’ In
postulate III, the Principle of Response Probability, she states that ‘
The probability of any particular response occurring at some specified
time is a function of the proportion of the stimuli present which are at
the time cues for that response (Voeks, 1950).’
To investigate the effect of incidental stimuli on skill acquisition,
Wright and Shea (1991) had participants work on learning specific
patterns of key pressing movements on a computer. Incidental stimuli in
the form of audio were provided for each specific pattern. After
practicing, participants were allowed to rest. When tested again they
were examined with either the same auditory stimuli, or different
stimuli. It was found that performance in retention was greatest when
the same auditory stimuli were present, suggesting that the stimuli
served as learned or associated cues to trigger the desired response.
This may explain the home advantage, which has been
investigated in sport contests for over 20 years (Bray et al., 2002).
Bray et al. (2002) suggests that results have consistently demonstrated
that there tends to be a performance advantage associated with competing
at home among major professional and collegiate leagues. While a number
of factors have been identified such as the crowd, travel, and rule
factors that could favor the home team (Courneya & Carron, 1992), as
well as confidence associated with a home environment and anxiety on the
road (Bray and Widmeyer, 2000; Jurkovac ,1985, Duffy and Hinwood, 1997),
the influence of outside stimuli remains an important factor
( Courneya and Carron, 1992, Schmidt and Lee, 1999). For example, the
confidence seen at home, may be attributed to past experiences supported
by environmental cues. According to Voeks (1950) when playing at home
the probability of performing a given response increases, which would
therefore tend to result in a greater number of wins. According to
Bandera (1997), situation specific self confidence (self efficacy) will
rise with positive experiences.
Pattern
Specificity
Sawyer (2005) posits that the motor program contains the spatial and
temporal elements within an individual, that when initiated allows for
the expression of complex movement behavior. In this context, the
spatial elements represent the pattern, or geometric aspects of a
particular movement sequence. Two outcomes can occur through adjustment
of movement patterns. First, the pattern can be adjusted such that an
entirely new program is needed. Secondly, if the adjustments are subtle
enough, and practiced for a long enough time, modification of the
program’s spatial elements can occur. In a review on transfer of
training, Uebel (1987) suggests that when choosing exercises other then
the criterion task the participant must be careful with movements that
are similar, but not identical to the task, as they may have a negative
transfer effect.
An example of this can be found in added resistance paradigms. Lockie
et al. (2003) investigated the effects of sled towing on acceleration
sprint kinematics in field-sport athletes. Twenty men completed a series
of sprints without resistance and with loads equating to 12.6 and 32.2%
of body mass. It was found that Stride length was significantly reduced
by approximately 10 and approximately 24% for each load. Stride
frequency also decreased. In addition, sled towing increased ground
contact time, trunk lean, and hip flexion. Upper-body results showed an
increase in shoulder range of motion with added resistance. Paradisis
(2001) investigated the effect of a 3-degree incline on sprint
kinematics. It was found that there were significant changes in posture
on the touchdown and takeoff. Further, stride length decreased by 5.2
%, which was associated with changes in posture along with reduced
flight distance. The authors summarize the results as follows: 'Given
the interaction between the acute changes in step length and posture
when sprinting on a sloping surface, our findings suggest that such
changes in posture will detract from the specificity of training on such
surfaces. ' Far worse however is the danger of negatively changing the
movement pattern. Therefore, any form of practice should be extremely
cautious when tampering with the geometry of the movement.
Resistance
Specificity
In terms of weight training performance within a specific criterion
lift, there appears to be a repetition continuum in which specific
adaptations occur. In a review by Fleck and Kraemer (2004) it was found
that generally 1-6 repetitions had the greatest effect on 1 repetition
maximum performance, 8-12 repetitions had the greatest effect on
muscular hypertrophy, while above this range had the greatest effect on
the ability to perform the exercise at high repetitions while
withstanding fatigue effects. Therefore resistance utilized in weight
training will have specific adaptations.
A second form of resistance training is to add the resistance to a
specific sport task, such as running. As discussed, this can have
negative effects on the pattern of movement. Therefore it is suggested
that if resistance is used, that it is done cautiously, in such a manner
that the pattern is not significantly altered. This may be done by
adding very low resistance. For example Derane (1985, 1990, and 1993)
found in three studies that baseball throwing velocity increased for
both slightly lighter and heavier balls. . There are several
theoretical rationales for this. The first, would fall under the law of
accommodation, which suggests that the response of a biological object
to a given stimulus decreases over time, necessitating the need for
variation. If that variation can be provided, without degrading the
motor program then adaptations may occur. Derenne et al. ( 1993)
suggests that highly specific fast movements could recruit and fire
high-threshold fast muscle fibers to a greater extent. Fast twitch
motor units have a greater capacity to assist in high velocity
movements. Therefore n selective activation of fast motor units in
muscle could be specifically trained.
The issue on added resistance is again changing the pattern of movement,
as was discussed previously. The change in pattern could be due to too
great a load added. However, it can also occur through misplacement of
the resistance. For example, ankle weights primarily provide vertical
resistance to the runner, when the runner is traveling in a horizontal
manner.
Rate / Velocity
Specificity
Rate or Velocity Specificity is a concept revealed through studies which
suggests that performance increases occur to their greatest extent at
the velocity they are practiced at
(Fleck et al., 2004). Further, while significant gains do occur in
performance other than the criterion velocity, they generally increase
with velocities that are closer to the criterion velocity.
Further, if the velocity is changed drastically enough it may actually
alter the order and magnitude of muscular action (Wilson, 2003)
Contractile
Specificity
Contractile Specificity suggests that the greatest increases in
performance will come as a result of the types of contractions utilized
in practice. For example, Schott et al. (1995) investigated the
transfer between isometric knee extension increases in performance and
an increase in several isokinetic movement velocities. It was found
that the results produced typically no significant increases in
isokinetic strength, suggesting that the best way to increase isometric
performance is to train isometrically, and the best way to increase
isokinetic performance is to train isokinetically.
Joint-Angle
Specificity
Joint angle Specificity suggests that performance increases take place
primarily at the criterion angle, and the transfer from one angle to
another is proportional to the proximity of the angles trained. For
example, Knapik et al. (1983) found that training the elbow flexors at
90 degrees results in increased isometric strength at 90 degrees, with
only very small increases up to 20 degrees away from the specific
angle.
Processing
Specificity
There is an old adage which suggests that ‘ perfect practice makes
perfect.’ The individual(s) who proposed this adage first were clearly
ignorant of Processing Specificity, which suggests that the transfer
between two conditions will be proportional to the similarity of the
underlying processes which occur between those two conditions. A key
researcher of processing Specificity is Dr. McCullah of
California
State
Hayward University. She is considered by many as the world’s leading
authority on modeling, and has served as President of the Association
for the Advancement of Applied Sport Psychology and most recently the
North American Society for the Psychology of Sport and Physical
Activity. She has also served on the editorial boards of the top
Exercise Journals in the world, including Research Quarterly for
Exercise and Sport. Of key importance was a study by McCullah and Card
(1990), who investigated the effect of a learning model with Knowledge
of Results (KR) vs. a correct model with KR on performance in a timing
task. They also examined the effects of a learning model who did not
receive knowledge of results. Modeling has been proposed to produce a
symbolic representation of the models performance in a perceptual trace
or reference of correctness (Sheffield, 1961). In this context, the
participant will continually compare his or her performance against the
perceptual trace until it is correct, suggesting that a correct model
would appear to provide the greatest learning, as it would provide a
perfect reference of correctness. However, McCullah and Card (1990)
found that observation of a learning model provided greater performance
in retention than the correct model! The theoretical rationale is
Processing Specificity. Lee and White (1990) suggest that two of the
processes which occur in motor learning are error-detection and
correction in problem solving activities. The correct model does not
display either error detection or problem solving activities. However,
the learning model with knowledge of results provides the learner with
an opportunity to view the model both encounter errors, and make
corrections to problems encountered (Pollock and Lee, 1992) . Therefore
the learner not only produces a reference of correctness, but develops
error detection mechanisms. McCullagh and Card (1990) also provided KR
to the model, so that the model would know if they made an error or
not. According to Adams (1986) this further enhances learning as it
both assists in forming the reference of correctness and allows the
observer to participate in the cognitive activities of the learning
process. This was confirmed in the McCullagh and Card study who found
that the learning model without knowledge of results had worse
performance than the other conditions.
Many practice conditions can be explained by processing specificity. An
example is found in Random vs. Blocked Practice. In Random Practice,
the participant never performs a task consecutively, where as in blocked
practice they perform the task in a consecutive order. In practice
performance is worse in the Random condition than blocked. However,
after a period of rest, it is found that Random practice produces better
learning! This is due to underlying process optimization in the Random
practice condition, and is discussed in depth in the article entitled
conditions of practice.
Summary
Five categories of specificity were discussed. Sensory Specificity
suggests that afferent feedback is integrated with motor elements to
form a sensorimotor representation of the task. In this context, the
closer the sensory information from one situation to another, the
greater the transfer will be. Context Specificity suggests that the
transfer between performing a task in two environments will be
proportional to the similarity of those environments. This is thought
to be due to associations made between the task and incidental stimuli.
Pattern Specificity refers to the geometric representation of a task.
Individuals should be careful not to change the geometric elements of
the program, through mechanisms such as sled towing in running.
Resistance provided in the task will elicit specific adaptations to that
task. Rate Specificity suggests that practice should attempt to mimick
the velocity utilized in a competition setting. Finally processing
Specificity suggests that practice will transfer to criterion in so much
as the underlying processes governing the criterion task are utilized
during practice.
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