What is skill?
According to the Oxford dictionary, skill is defined as “the ability to do something well”. However, reflecting on what skill is, it is a largely complex and ambiguous term. Skill is synonymous with competency, but it also indicates expertise, mastery and excellence (Attewell, 1990). But on the whole, the term skill is very ambiguous and can mean different things to different people. Regarding skill “acquisition”, there are two conflicting definitions to describe this process.
Skill acquisition: the establishment and subsequent enrichment of internal representations that bring about relatively permanent changes in a learner’s movement capabilities (Schmidt & Wrisberg, 2004).
Skill adaptation: the establishment of a reciprocal, functional relationship between an individual and the environment (Araujo et al., 2004).
When comparing these two definitions, it is clear how ambiguous the term “skill” is. The skill acquisition definition suggests the “relatively permanent” nature of skill, whereas the skill adaptation definition is more indicative of an ever-evolving process. To dive further into the skill adaptation process, there are three key aspects that determine an individual’s skill adaptation level:
Attuned – A quality which describes a performer who has become perceptually sensitive to the most specifying informational variables for achieving a task goal (Michaels & Jacobs, 2007)
Adaptable – A quality which describes a performer who is able to coordinate and control their movement to maintain a more functional performer-environment relationship (Davids & Araujo, 2011)
Dexterous – A characteristic which explains how one is able to organize a movement solution for any emerging, external situation, in any situation and in any condition (Bernstein, 1996)
With these three aspects of skill adaptation, practitioners can construct a training programme with the ultimate aim of making more “skillful” players.
Different Approaches to Skill Acquisition
There are a number of approaches to skill acquisition, and this section will examine two methods of skill acquisition – the “predication” approach of information processing and the “self-organisation” approach of ecological dynamics.
What is it?
A key aspect of the information processing (IP) approach to skill acquisition is that the information from the environment is not enough for a performer to initiate action. Instead, coaches must provide cues the further guide athlete movements or actions. The most well-known model of skill acquisition that fits into the information processing approach is Fitts and Posner’s three stage model of motor learning (Fitts and Posner, 1967).
The three stages within this model are the cognitive stage, associative stage, and autonomous stage. These three stages have also been referred to as the early, intermediate, and late stages of learning (Fitts, 1964). The cognitive stage is dependent on intellectual ability. Performance within the associative stage is shown through correct movement patterns, increased speed, and a reduction in error rates to below 1% (Anson et al., 2005). The final stage is characterised by further increases in speed and accuracy, with diminished error rates, but also increased resistance to stress from other tasks (Beilock et al., 2002). However, a big criticism of much of the laboratory work investigating this model has been conducted over 1 session, or a 3–4-day period, which would indicate the study is limited to the initial cognitive stage of learning (Mowbray and Rhoades, 1959).
There is substantial strength behind the three-stage model of Fitts and Posner. Many textbooks contain descriptions of the model in details, but the origin of the model is rarely discussed. Two papers – Fitts (1962) and Fitts (1964), presented a thorough framework in which skill acquisition could fit in within the three-stage model. The constraints led approach (a typical ecological dynamics method) claimed two important components were missing from an IP approach, namely the bridge between behaviour and biology and the continuity between control and learning. However, looking at these two papers identifies these two aspects, despite few modern resources discussing them.
According to many resources, the information processing approaches to skill acquisition lacked generalisability to motor skills (Anson et al., 2005). Both of these information processing theories in nature – closed-loop theory (Adams, 1971) and schema theory (Schmidt, 1975), were unable to serve as general theories for coordination, control and skill. But as noted previously, there is substantial explanatory strength behind information-processing theories, despite it being ignored by many modern resources.
What is it?
Ecological dynamics (ED) is based on insights in ecological psychology from James Gibson (1979), and concepts in dynamical systems theory. ED emphasises the performer-environment interaction in training design. Performers need to act and identify key sources of information, to aid their decision making and allow for action organisation facilitated by practice micro-structure. The micro structure of practice refers to coaches replicating vital aspects of a player’s performance environment in training (representative task design) to improve the performance of their players in competition (Davids et al., 2017). A methodology of coaching that has been founded on ED principles is Nonlinear Pedagogy, which involves manipulation of key constraints to allow coaches to shape learner’s decision making and actions (Renshaw et al., 2010). Davids et al., (2017) have shown that manipulation of relevant task constraints can help learners identify (become attuned to) information that will determine their actions.
Araujo and Davids (2011) identified several key principles on skill acquisition from an ecological dynamic’s viewpoint. These include:
Information-movement coupling (or perception-action coupling) is the basis for skilled performance and expertise in sport (Arujo and Davids, 2011). As athletes become more skillful in their domain, they develop a tighter bond between their ability to identify information in a performance environment and their actions.
Affordances is a James Gibson term (1986) which identify what an environment offers an animal (or learner/athlete), based on their action capabilities. Affordances can be described as opportunities for action or as invitations for action.
Representative practice design
Practice demands need to mimic the demands of competition. This does not simply refer to the physical demands, but the information that guides actions in competition, must also be present in training.
Effective task constraint manipulation
Task manipulations guide learners to specific affordances within an affordance landscape (Rietveld and Kiverstein, 2014). This is where athletes can explore the environment to exploit affordances, and relevant task manipulation by a coach can help make certain affordances more inviting for an athlete.
Resulting from ED and how it has altered the perception of skill acquisition in a sporting context, coaches could now be viewed as designers, tasked with designing the environment in which athletes must identify and exploit relevant affordances an ultimately develop a stronger coupling of information present and their actions. Through the implementation of ED principles over the last two decades, coaches have progressed from an autocratic instructor through continuous verbal instruction and corrective feedback, to a learning designer, or architect of the environment, to work with the athlete to co-design the key constraints of the practice environment.
An ED approach to skill acquisition allows for a cognitively stimulating and fun environment. Players are always required to think on their feet in training and this forces them to engage in training activities to a higher level than if they were not required to make any decisions. This higher engagement seeks to lead to a greater learning experience from a session, provided the challenge point is within the learner’s optimal bandwidth (Guadagnoli and Lee, 2004). While an ED approach to training may lead to poorer performance in training (higher failure rate), it has been shown to lead to higher learning rates (better performance in competition (Soderstrom and Bjork, 2015).
From a coach point of view, using an ED framework for training can allow for a more creative coaching process. Rather than having a set bank of drills or activities to do, coaches must look at their team’s performance and assess what needs to be improved on for the next game. From this, coaches construct a training environment to help players attune to vital pieces of information, so the players can ultimately make better decisions on the field of play.
Professional sport is often a result driven business, and while ED can provide an optimal approach to skill acquisition, the timeframe in which an ED approach is successful can vary on the athlete’s ability to identify the correct information from the environment that has been designed. Coaches may only have a small window in a training week to pass on vital information that could influence the result on any given weekend. A direct approach is sometimes necessary to ensure that the athletes have all the relevant information at his disposal to allow him/her to perform to their potential.
Depending on a player’s development pathway to professional sport, employing an ED approach to training could be a source of immense stress and frustration, as they are used to direct instruction and following those direct orders. A situation where a player has not found the optimal solution to a problem presented to them by a coach in training, may end up being a massive confidence drain leading into a big weekend game.
Part 2 of my MSc Literature Review can be found here.