Acquisition of skill is a type of learning in which repetition results in enduring changes in an individual’s capability to perform a specific task. With enough repetition, performance of the task eventually may become automatic, with little need for conscious oversight. Any behavior that needs to be learned and that is improved by practice can be considered to be a skill. Making a cup of tea can be considered a skill, just as is drinking it. Skill acquisition in sport generally can be thought of as either learning to coordinate the body appropriately to achieve an intended movement outcome or as learning any of the myriad mental aspects associated with effective movement, such as where to move and when. A highly skilled goalkeeper who saves a penalty kick has learned not only how to fling his body most effectively around the goalmouth to keep the ball out but also when and in which direction to fling his body. In most sports, these different facets of skill cannot be viewed in isolation, as it is the combined synchrony of perceptual, cognitive, and motor processes that culminates in highest levels of performance. Performance of the skill will improve over time as a consequence of repeated engagement in the task (i.e., perhaps deliberate, perhaps not) and will be accompanied by increasingly consistent attainment of the desired outcome, which eventually can be achieved in a variety of conditions, contexts, or environments. For example, a skilled golfer may consistently hit the green from 150 yards and have a higher likelihood of doing so in the pouring rain or when it really matters than an unskilled golfer. A skilled performer can thus be defined as a person with the ability to achieve an intended outcome repeatedly in a variety of conditions and usually with less physical or cognitive effort than a less skilled performer.
The study of skill acquisition dates to work that investigated how field operators acquired telegraphic language skills. At the turn of the 20th century, the effectiveness of telegraphy as a form of rapid long-distance communication relied on operators to be highly skilled at the perceptual, cognitive, and motor aspects involved in transmitting, receiving, and translating Morse code. The work, which examined skill level as a consequence of experience, showed that variability of performance decreased as operators became more skilled, and that their performance was less easily disrupted by outside distractions. Although the work showed that it generally took between 2 and 3 years for operators to become skilled, the progression of learning was not continuous. Plateaus occurred during which performance barely changed, only progressing if the operator did not become despondent and discontinue practice. The researchers argued that performance could not progress to a higher level until attention was freed by the automatization of lower level responses within a hierarchy of habits.
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Although plateaus in performance level are not always observed over the course of skill acquisition, one characteristic that is observed more often than not is a high rate of change in performance level early in practice, with gradual reductions in rate of change as practice continues. This power law of practice has the function log C = log B + n log x, where C refers to performance level, x refers to amount of practice, and B and n are constants.
There is little doubt that the level of performance that can be achieved when acquiring skills is closely related to the extent to which a person practices the skill and the way in which the person practices. Researchers often use retention or transfer tests to determine whether the changes in performance caused by practice are temporary or permanent. By assessing performance sometime after practice has been completed, perhaps a day or a week, it is possible to observe true performance level without temporary practice effects related to factors such as motivation, fatigue, or boredom.
Researchers have examined many methods designed to maximize the enduring changes in behavior that practice must produce for skill acquisition to occur. For example, early work examined whether it was better to practice the different parts of a task independently or together as a whole task. Findings were mixed, and it is probably fair to say that no consensus emerged. The effects of massed and distributed practice have been examined at length. Massed practice involves continuous practice, whereas distributed practice involves the spacing of practice over time. One meta-analysis of 116 studies suggested that distributed practice is preferable for continuous tasks but massed practice is preferable for discrete tasks. A well-known phenomenon is the contextual interference effect, in which interference appears to cause poor performance during practice but good performance during retention and transfer. In particular, the effect is seen when interference is caused by switching randomly between skills when practicing, as opposed to practicing each skill one after the other in a blocked pattern. Two explanations have been proposed for the phenomenon. The elaboration hypothesis suggests that random practice of different skills requires performers to actively retrieve movement solutions each time that they perform, which results in a more distinct representation of each skill in memory. The reconstruction hypothesis suggests that switching from one skill to another during random learning causes performers to forget the previous movement pattern. Consequently, performers must continually reconstruct the movement as they practice. A fascinating adjunct to the contextual interference effect has been added in recent years by the concept of differential learning, which suggests that a significant learning advantage is gained from maximizing interference during practice by introducing stochastic perturbations of performance. In essence, it is argued that a person learns more by trying to achieve the same skill outcome with maximum differences in the manner of execution.
Many factors influence skill acquisition. The difficulty of the skill to be acquired, and the availability of information or the form in which the information is available, play a significant role in the process. Information about potential movement solutions can be acquired by instructions or guidance from an external agent or by observation or modeling. Much research has examined the effects of feedback on skill acquisition. Intrinsic feedback provides sensory information that arises from executing a skill. Visual feedback often seems the most salient, but feedback from the other senses also plays a part in skill acquisition. Extrinsic feedback provides augmented information about performance of a skill, often supplementing the information that is available via intrinsic feedback. In particular, knowledge of results and knowledge of performance are crucial types of extrinsic feedback during skill acquisition. Knowledge of results is extrinsic information about the movement outcome, whereas knowledge of performance is extrinsic information about the movements themselves. The information in both instances is usually provided to the performer verbally (e.g., you missed left or keep your head still) or perhaps by video replay or even diagrams. Most people accrue much information by a process of hypothesis testing in which they devise and test strategies to correct performance errors. There are few cases in which learning takes place in the absence of at least some intrinsic or extrinsic feedback. The challenge point framework proposes that what is learned is a function of the information that becomes available during performance and that the crucial factor is the interaction between the difficulty of the skill to be learned and the level of ability of the performer.
The Cognitive Approach to Skill Acquisition
Cognitive characterizations of the human brain as a processor of information argue that information received by the senses contributes to the development of centralized representations in memory, which are used to control performance using preprogrammed commands that run without the need for modification from feedback (i.e., open-loop control) or from continuous comparison of ongoing feedback with representations generated by previous movements (i.e., closed-loop control). A significant problem for these theories was that a representation needed to be stored for each different movement, creating a storage problem. Subsequently, schema theory was proposed as a solution to the storage problem. Schema theory proposed that a general motor program represents a class of movements (e.g., throwing), but that different submovements are produced by specifying the necessary parameters at the time (e.g., speed or force).
The cognitive approach suggests that during practice movement representations can be updated and improved—using knowledge of results or knowledge of performance, for instance. As a consequence, performance efficiency improves. An outcome of this process is that skill learning progresses through a sequence of stages characterized by fairly distinct cognitive characteristics. At first, when the skill has been little practiced, performance tends to be cognitively controlled as the learner consciously tries to select strategies to use and the relevant information to attend to. Performance tends, therefore, to be explicit, inefficient, and variable. A second stage follows in which the intense need for conscious, cognitive involvement begins to ease. Strategies are cemented and stimulus–response (S–R) associations begin to strengthen. A final stage is characterized by performance that requires very little cognitive engagement. Performance is consistent, efficient, and can occur automatically without conscious intervention. These characteristics are common in many psychological theories of skill acquisition, although sometimes the theories differ with respect to why practice improves performance.
Some theories (e.g., instance theory) are predicated on the belief that practice increases the number of available memory representations that can be accessed to support performance, whereas other theories (e.g., adaptive components of thought [ACT] theory) are predicated on the belief that practice refines strategies and procedures that support performance. These theories often make a distinction between declarative and procedural knowledge that is associated with performance. Declarative knowledge can be thought of as explicit facts or propositions that describe information related to performance and that can be described by the performer, whereas procedural knowledge can be thought of as implicit representations of how to perform, which cannot be described by the performer. Use of declarative knowledge to support skill performance tends to require processing resources and is effortful, but eventually practice allows skills to be executed as procedures, with little or no reference to declarative knowledge. In such cases, far fewer processing resources are used, and performance tends to be more effortless than effortful. Researchers who have used implicit motor learning techniques to inhibit the accumulation of declarative knowledge during skill acquisition claim that this promotes the benefits associated with use of procedural knowledge to support performance.
An Ecological–Dynamical Approach to Skill Acquisition
The ecological approach proposes that information that resides in the environment specifies the options that are available for behavior by an organism (i.e., affordances). Actions and perceptions are coupled, and movements can be initiated without reference to memory representations or motor programs, using only information that specifies the constraints on movement. Practice is seen as a process of educating attention to pick up the specifying information rather than the nonspecifying information in the environment. In tandem with the ecological approach, a dynamical systems theory of movement coordination has evolved in which biological organisms are seen as systems that can self-organize in response to existing constraints or parameters, and that are attracted to stable patterns of coordination. This view emerged as a way to understand the complexities presented by a human motor apparatus that has evolved with countless ways in which to move. Nicolai Bernstein called this the degrees of freedom (df) problem and proposed that skill acquisition is a matter of solving the df problem. He argued that initially movement control is simplified by locking various joints in order to reduce many of the df. Gradually the df are released during practice and the performer becomes able to control or exploit energetic forces, such as momentum or inertia, during movement. This approach provides a perspective to skill acquisition that has yet to be fully reconciled with traditional cognitive approaches in sport.
References:
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- Masters, R. S. W., & Poolton, J. (in press). Advances in implicit motor learning. In A. M. Williams & N. J. Hodges (Eds.), Skill acquisition in sport: Research, theory and practice (2nd ed.). London: Routledge.
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- Schmidt, R. A. (1975). A schema theory of discrete motor skill learning. Psychological Review, 82, 225–260.
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