The 'ecological-dynamics' of skill acquisition: Part 1

The separation of humans from their environments is rooted in the foundations of modern science from around the time of the enlightenment (see Svenson, 1998; Glimcher, 2005). A central criticism of which is the presumption that physical phenomena are fundamentally deterministic in nature, which according to Lickliter (2009) is unnecessarily reductionist and not supported by current understanding of biological and psychological development. During the first part of the 20th century the emerging discipline of quantum physics (see Glimcher, 2005) would show that at an atomic and sub atomic level particles demonstrated fundamentally indeterminate behaviour and could only be described probabilistically. Given that ‘learning’ takes place in dynamic and unpredictable contexts, evidence also suggests that living systems are inherently indeterminate (see Hall, 2006) and as such the interaction between an individual and its environment must also be indeterminate in nature (see Chow et al., 2011).

In an indeterminate physical world the environment, and the situations we encounter in it, acts to produce an external flow of energy that the biological organism dissipates by producing its own internal entropy (see Kondepudi, 2012). The organism and its surrounding environment constitute a single system (Turvey, 2009) in which the value of each can be predicted from the value of the other, under all considered circumstances (Beek et al., 2003). With this in mind the appropriate scale of analysis for understanding, and potentially predicting, human behaviour is the interaction between the organism and the environment. As such a biological system, able to exchange energy and matter with the environment, is said to have ‘agency’ because when it interacts with an environment it is subsequently changed by the interaction (Ovens et al., 2013).

The process of producing internal entropy as a dissipative response to external (environmental) entropy is known as ‘catalysis’ (see Cuff, 2007). When stochastic perturbations act to disrupt their system dynamics, open systems strive to self-organise and develop new structure where no previous knowledge of the structures impending form is known (see Stephen et al., 2009). Biological systems display ‘meta-stability’, that is to say that they have access to multiple solutions to performance problems (Phillips et al., 2010). They exhibit nonlinearity in their ability to respond to environmental constraints. Insights such as these have their origins in biology, physics and psychology (see Seifert et al., 2013) and have given theoretical impetus to the development of ‘nonlinear pedagogy’ and the ‘constraints-led approach’ to motor learning (see Brymer et al., 2010).

According to Simon (2007), the field of Ecological dynamics has been responsible for a full scale paradigm shift in thinking about the acquisition of superior performance in sport. The ecological approach was developed, in many respects, as an alternative to highly structured, mechanistic and overly cognitive ‘enrichment theories’ (Araujo & Davids, 2011) such as the theory of ‘deliberate practice’. In enrichment theories environmental stimuli are ambiguous, individuals overcome ambiguity by developing increasingly sophisticated processes and internal structures (see Davids et al., 2012). Instead, in the field of ecological dynamics, physical phenomena are characterised as dynamic, nonlinear biological systems (Seifert et al., 2013), capable of spontaneously self-organising under constraints (Renshaw et al., 2009); making them non-algorithmic, non-computational (see Hanford, 1997; Kondepudi, 2012; Turvey & Carello, 2012) and non-representational within one-dimensional and linear thinking.

 

Talent Development, Physics and Biology

Our bodies and minds are creatures of adaptation and given that biological systems are in continuous state of adaption, our current state of being can be represented as the phase space that we currently inhabit. On a larger scale it is this process that forms colonies of organisms that have been subject to similar interactions. In this way we converge on a phase space as a result of the continuous interaction between organism and environment in a process involving thermodynamic flow of energy. That is to say that both the environment and the organism produce entropy, entropy is the thermodynamic flow that allows us to predict the systems current state of organisation and all potential future states. For example if the organism continuously follows the path of least resistance to a local source of energy it will reach a state of maximum entropy production. In this example the entropy producing organism has overwhelmed the entropy in the environment and will eventually transit towards a state of decline because this is the only direction currently available to it.

Managing upward directional transits in relation to talent development is clearly a fundamental concern for those working within the process. Whilst all of the above may seem like a complicated way of explaining the obvious it is in the rule based detail of these principles that I believe provides the greatest opportunity for successful talent development. Hopefully as the emerging fields of ecological psychology and dynamical systems theory reach the mainstream we will see a greater number of performers/teams reaching their full potential.

Introduction to non-Linear pedagogy Pt 2 - Coaching

The development of non-linear pedagogy is predicated on the notion that the learner is a non-linear dynamical system that produces movement solutions in response to information in its environment.  An agent and its environment are inseparable in which case open systems are susceptible to perturbations that can either fatally disorder it or drive it to self-organise. The view that the biological adaptive process drives the development of talent in this way has given rise to the notion that ‘expertise is an adaptation’ to the many interacting (i.e. psychological, physiological, sociological) constraints acting on the individual at any given time.

The basis therefore of a non-linear pedagogy is that the coach can manipulate the sources that act to constrain performance in a way that guides the performer to a more functional state. For example evidence shows that the manipulation of constraints can lead to the production of successful motor patterns and decision making behaviour (Chow et al 2006). In ‘constraints led coaching’ the coach creates training environments that are designed to induce adaptation in the ‘known’ mechanisms that control performance in the target context – they attempt to build the machine for the race it's in!

Some thoughts on designing learning in a constraint based framework;

-          The key constraints that can be manipulated are: the task (i.e. Rules), the individual (deliberately fatigued), the environment (i.e. the scaling parameters of the playing space)

-          The configurations of constraints by the coach are not designed to prescribe the way the learner behaves but instead guide it (Davids et al 2012)

-          Constraints cannot influence the learning process independently (see Davids 2008) i.e. the technical, mental, tactical aspect of performance must be integrated in to the training environment.

 

-  Practice therefore  should be ‘representative’, if the setting for practice provides more time for participation and it doesn’t invoke physical, psychological and performance adaptation the it should not be considered as a talent development environment (Cobley et al 2012)

-          Practice should designed to drive the performer to the ‘edge of stability’ where they are forced to function at high levels of intensity (Renshaw et al 2012)

 

Introduction to non-linear pedagogy

Extended engagement in practice leads to functional adaptation in the mechanisms that control performance. The emergence of new structure characterises the adaptive process and occurs when specific constraints act to perturb the systems state of homeostasis. In this respect ‘new structure’ emerges even though the system has no previous knowledge of the new structures impending form. Crucially when an athlete experiences a plateau in performance the existing structure of the system will remain unchanged until entropy overwhelms the systems current state of stability. Entropy then, as described by Stephen et al (2009), is an index of disorder or instability acting upon the system driving it to spontaneously reorganise.

The self organising propensity of neurobiological systems can be harnessed for the development of sporting talent. The space in-between stability and instability is known as the ‘phase space’ where the athlete is transitioning from one level of performance to another. This is described by Rernshaw et al (2011) as the meta-stable region of performance where the athlete is poised on the edge of stability in a highly adaptive state. In this respect the developing performer can be thought of as a non-linear dynamical system because what acts to perturb reorganisation of system dynamics in one individual may not be the same in another.   

Conceptualising human development in this way is significant because traditional theories of learning have been unable to show how individual differences can be acounted for and designed into the learning process (Davids et al 2012). For this reason monotonic linear models of talent development aligned to deliberate practice methodology have been unsuccessful (Renshaw et al 2011). 

If this knowledge is to be integrated successfully into learning design, in a way that directly impacts on the talent development process, practitioners will need to have a sound theoretical understanding of the transfer-appropriate processes that govern such thinking.

The Emergent Nature of Skill

Golf is a game played in environments where specifying variables (affordances for action) include: weather systems, topology, surface type and performance pressure; furthermore these specifying variables are non stable and subject to fluctuations.  Regardless of this the golf performer, typically, attempts to overcome these constraints during block practice sessions in predictable environments, leading to inevitable problems in relation to retention and transfer of skill to the performance context.

Not surprisingly research has shown (e.g. Ball et al 2003; Fairweather et al 2002) that no common optimal coordination pattern can exist because each time a skill is performed in ‘real life’ it is subject to a set of unique variables (e.g. wind, temperature, slope, physiological status, psychological factors) that will be present to a lesser (or greater) extent each time a skill is performed. In thermodynamics, which predicts a tendency toward entropy, such systems are called ‘open systems’ which are in contrast to ‘closed systems’ that tend to be information impoverished. This effect is seen in skill acquisition during block practice in ‘closed’ contexts where performance tends to be effective during the practice session however retention and transfer tend to be poor, whilst the random prescription of practice tasks, known as contextual interference, has been shown to have the opposite effect (see Lee & Simon 2009).

According Ecological psychologists (e.g.Gibson 1979), specifying variables in the environment are acted upon in the form of a functional (or non-functional) movement response/solution; this is referred to as ‘information-movement coupling’. Under such conditions skill is considered to be an emergent attribute constructed when an agent firstly becomes aware of the key information sources in the environment; and secondly fine tunes the movement response. These interactions produce order through a process called ‘self organisation’ as the human system acts to form coherent spatial and temporal structures (Huys et al 2009).

One way the coach can encourage the self organising propensity of the human system is through a process called constraints based coaching (see Chow et al 2006). In constraints based coaching the practice session takes place with all information sources present and flowing (e.g. the mental, technical, tactical, physical aspects of performance). In this situation the coach can manipulate environmental constraints, such as changing the scaling parameters of the playing field, to induce greater levels of skilled behaviour.

Designing 'representive tasks' in this way according to Davids et al (2007), exemplify how perception, decision making and action (a) are examples of adaptive behaviour, (b) embodies the performer – environment system, (c) function in a task specific manner, (d) are dependent on interacting constraints that are specific to the performance context.   

Instruction Versus Environment

In an earlier post (The Problem with Stack and Tilt) I stated that the most adaptive co-ordination patterns are those that are soft assembled and in tune with environmental fluctuations - this new post is will look at this notion in more detail.

 When movement patterns are soft assembled the player is able to focus ‘externally’ on the anticipated outcome of the action, instead of ‘internally’ on the specific movement itself.  In other words the player begins with the outcome in mind (based on how they perceive the shot/situation) and this perception is then orientated to an appropriate movement pattern – this is called action-perception coupling.

In contrast to this, movement patterns that begin life as instructor led demonstrations of the correct posture, weight shift, arm position, hip action etc.,  have been shown to degrade performance under pressure and in some cases are more detrimental to performance than receiving no instruction at all.

(Typically this type of instruction occurs in highly managed, static environments that are characterised by safety and control. In order to reduce information overload ‘part task' practice activities are learned as a precursor to performing the whole skill)

It is likely that during the initial rehearsal of these new movements the player experiences a degree of improved performance. This is likely caused by practicing in a stable environment that allows fine tuning of movement parameters from one attempt to another. This often results in an artificially high level of performer confidence which often results in poor or negative transfer to a stressful performance situation.

It would of course be wrong to suggest that an emerging performer/novice needs no instruction at all, however skill acquisition practitioners advice that as soon as the learner acquires a rough approximation of the movement pattern they should shift their training to a more random schedule.

Whilst time spent in an instructional context would seem to diminish positive transfer to target context this should not have negative implications for the golf coach/instructor/teacher. Instead it would be hoped that a generation of cutting edge coaching research begings to inform the future direction of the industry.

References

Davids, K; Button, C; Bennett (2009) Dynamics of Skill Acquisition, A constraints led approach, Champaign, Human Kinetics

Schmidt, R.A & Wrisberg, C.A (2008) Motor Learning and Performance, A situation based learning approach Champaign, Human Kinetics

Wulf,G., Lauterbach,B., & Toole,T. (1999). Learning advantages of an external focus of attention in golf.Research Quarterly for Exercise & Spor

The Problem with Stack and Tilt!?

Never before has a golf coaching innovation divided opinion to the extent that the swing classification system known as ‘Stack and Tilt’ has. For this reason it needs no introduction apart to say that discourse on this subject is almost always dominated by arguments about its bio-mechanical principals.

Let me be clear about one thing, bio-mechanically and for the purpose of striking a golf ball, I believe the principals of S&T to be sound; however I also believe that this may well be its critical weakness!

The organisation of the system came about based on the research/advice of noted coach Mac O’Grady and by the principals laid out in the book “the golfing machine”. For this reason I will refer to S&T as being created in a laboratory setting characterised by predictability and control.  The ultimate evaluation of a laboratory creation is the degree to which the system is able to interact with the environment that it was designed for.

It would seem that at this stage in time S&T for many interacts perfectly with the environment that created it, exemplified by impressive ball striking by its advocates in closed contexts, but not so well with its target environment. As such its functionality or fitness in a naturalistic setting has been drawn into question which has hindered its implementation on a far greater scale.

The situation is not surprising, nor is it exclusively an S&T issue; research into motor learning and skill acquisition provides an interesting explanation for this. In open systems movement orientates itself to information sources in the environment (ecological constraints), such constraints (weather, playing surfaces, pressure, perception etc.) shape a systems behaviour and as such the most adaptive coordination patterns are those that are ‘soft assembled’ and able to tune into the prevailing task conditions. In other words the environment creates the movement pattern and not the other way about.

S&T, and any other swing conception, created and learned in a static controlled environment will always orientate best to static and controlled conditions. Unfortunately few sports are played in more unpredictable and interchangeable environments than golf. That is why the research shows that the most transferable skills are those that are created and mastered when all information sources are present and flowing.

Deliberate Practice - Expertise IS in our GENES!

The long held belief that outstanding performance was a result of innate ability has now been replaced by beliefs about the role of intensive deliberate practice.   Why then has there been such a seismic shift away from previously held views regarding the crucial role of innate talent in the developemnt of expertise?

The answer to this question is central to the Ericssons theory of deliberate practice and can be explained by the mediating role of 'gene expression' during the transformation from one level of performance to the next. During this process dormant genes are actively selected (called in to action) as a result of intense and extended practice - in other words the mechanisms of the body, through training, adapt to meet the demands that are being placed on them.

Under these circumstances the superior capacities (physiological and cognitive) exhibited by experts and previously thought to be innate, in fact result from rather than cause the development of expertise. It is therefore not unrealistic to suggest that all healthy individuals have inherited the potential to reach expert levels of performance, as the necessary genes appear to reflect genes contained within all individuals’ DNA.

For example endurance athletes routinely experience hypertrophy in the left ventricular of the heart which speeds up the flow of blood to meet their increased need for oxygen (see below).

hypertrophy in the left ventricular (botton right) of the heart

Another example of adaptation to training and its mediating role in the development of expertise is that of professional musicians. A professional key board player can produce 1800 notes per minute with precision of space and time that is unsurpassed in any other type of human behavior. This is possible because professional musicians’ develop quicker nerve conduction due to the enlargement of myelin cells - this specifically occurs during training activities that require rapid information transfer and temporal precision.
 

In applying this thinking to the development of expertise in golf involves the following: firstly the qualities that allow experts reproduce superior performance in a representative context needs to be identified. Experts often fail to outperform non experts in closed context controlled tasks. Experts, then, are distinguishable from non experts by their ability to perform under the many constraints that affect performance at an elite level. Only once you have learned how they acquired these skills can you go about designing training activities that lead to superior performance in golf.

References

Ericsson, K.A (2003) “How the Expert Performance Approach Differs from Traditional approaches to Expertise in Sport” in Starkes, J.L & Ericsson K.A (Eds), Expert Performance in Sports, Champaign, IL, Human Kinetics

Ericsson, K, A; Nandagopal, K and Roring, R,W (2009) Toward a Science of Exceptional Achievement: Attaining Superior Performance through Deliberate Practice Longevity, Regeneration, and Optimal Health 2009 New York Academy of Science  1172: 199–217

Gruber, H; Jansen, P; Marienhagen, J and Altenmueller, E (2010) Adaptations During the Acquisition of Expertise, Talent Development & Excellence of Expertise, Vol. 2, No. 1, 3-15

Münte, T, F;  Altenmüller, E and  Jäncke, L (2003)”The musician’s brain as a model of neuroplasticity”,  Neuro Science Volume 3  473

Stewart, L. (2008) Do musicians have different brains? Clinical Medicine, 8, 304–308.

The Role of Deliberate Practice

The fact that Anders Ericsson’s theory of deliberate practice (see Ericsson et al 1993) needs no introduction is a reflection of its newly found position in popular culture. Without doubt the most popular hypothesis from the deliberate practice framework is that expert performance is achieved because of an individuals’ prolonged effort to improve and not because of any special or innate talents.
 

If this alone were true then potentially, you and I and countless others would be playing on the PGA Tour by now. Ben Hogan, for example, spawned generations of golfers who were willing to beat balls for hours on end and yet so few went on to achieve the same success. Why then do some people derive more from practice than others?

According to Ericssons research, the answer is simple; when the reproduction of a skill becomes automatic (the autonomous stage of learning), no amount of increased practice/experience will bring about a marked improvement in performance. In other words the autonomous stage of learning means that a skill can be reproduced without any real stress; and here in lies the problem, in order to experience continued adaptations in the mechanisms that control performance we need stress. In the absence of stress no further adaptations will be experienced - we have arrested the development of our potential.

For this reason expert performers’ deliberately circumvent the autonomous stage of learning by seeking out increasingly demanding tasks. Such tasks continuously require them to stretch their performance beyond its current level. They overcome the detrimental effect of automaticity and in doing so acquire the cognitive skills to support their continued learning and improvement.

As Ericsson explains, the future experts and their teachers “…search continuously for optimal training activities that will appropriately strain the targeted systems to induce further adaptations…”

Perhaps then Hogan’s secret was quite simply that above all he developed the ability to practice with the most effective intensity and duration – he had what is known as the talent to practice deliberately!

References

Ericsson, K.A., Krampe, R.T. and Tesch-Römer, C. (1993) “The role of deliberate practice in the acquisition of expert performance”, Psychological Review, Vol 100, No. 3; pp 363-406

Ericsson, K.A (2007) “The Influence of Experience and Deliberate Practice on the Development of Superior Expert Performance” in Charness, N; Feltovich, P,J; Hoffman, R,R &  Anders Ericsson, K (Eds) The Cambridge Handbook of Expertise and Expert Performance, pp 683-703, New York, Cambridge University Press

The Myth of LTAD?!

I was reminded recently about a lecture at the University of Birmingham in 2006 when the presenters had the temerity to talk to us about the “The myth of LTAD”. Up until this point I like many others had accepted LTAD as fact and had welcomed it as a great resource.  So how then could something so well respected, scientific and embraced by so many NGB’s, be a myth?

If the controversial nature of the lecture was designed to pique our interest it certainly worked; during the past five years I have been able to study this closer as it relates to my own area of research.

In making my own assessment with regards to the “Myth of LTAD” I have looked at the model primarily from the viewpoint of its evidence base and the scientific principles around which the theory is built.

The Issues surrounding the evidence base of the model are simple; during the development of the model no scientific/empirical studies were conducted to establish whether expert athletes actually develop via the four key stages proposed in LTAD. Indeed the only research conducted so far regarding how experts develop reveals different activities and stages to those proposed in LTAD (see Williams 2009). As it stands the evidence base for the model constitutes the basic elements of the Canadian Men's Alpine Ski team program spanning three Olympic cycles.

So what then of the scientific principles that form the conceptual framework of LTAD? In terms of validity, within a model, these principles should form laws that govern any observable variances in the phenomena of athlete development.

An example of this would be the so called limiting affect, in LTAD, experienced if the athlete neglects any age related critical and sensitive periods of development,  during these ‘windows of trainability’ the athlete is said to experience accelerated adaptations to specific types of training. Failing to take an advantage of these ‘windows’, it is warned, will lead to athlete never reaching their full potential. Not surprisingly this type of information is intuitively appealing to sports coaches’; and indeed the practical applications of these principles have led some to claim to be world leaders in their field.  

However on closer scrutiny it is not possible, amongst the vast LTAD literature, to find any citations of peer reviewed evidence supporting the “windows of trainability” claim. Indeed the research, non peer reviewed/ non empirical or otherwise, is so scarce that Viru et al (1999) suggest that any conclusion being drawn from them should be considered to be inaccurate.  

This lack of evidence leads to criticism of LTAD as operating in the ‘land of theory’ in that it can only claim to be reflecting ideas, theories, hunches and hypotheses about the development of an athlete. None of which is a problem, we all have theories and hunches about the world but when the model is promoted as absolute scientific fact then there is no doubt that "the myth of LTAD" is a reality. 

References

A, M, Williams & P.R Ford (2009) Promoting a skill based agenda in Olympic sports: The role of skill acquisition specialists, Journal of Sports Sciences, 27: 13, 1381 - 1392

Viru, A., Loko, J., Harro, M., Volver, A., Laaneots, L. and Viru, M. (1999) ‘Critical periods in the development of performance capacity during childhood and adolescence’, European Journal of Physical Education, 4 (1): 75–119.

An Introduction to Teaching Games for Understanding

I recently delivered a presentation at a coaching conference on an emerging pedagogy in golf/sport coaching. The workshop was titled “An Introduction to Teaching Games for Understanding (TGfU)”.

Here is a short blog post for those not already familiar with the TGfU concept.

I describe TGfU as an emerging pedagogy in golf despite the fact that the concept of TGfU was first developed during the 1970s and 1980s at Loughborough University by Rod Thorpe and David Bunker.

Thorpe and Bunker had observed that in the majority of coaching sessions the development of technique took up most of the time; furthermore when game play was included in the session, the techniques that had been learnt laboriously over several sessions did not transfer well to the game itself. As such TGfU arose out of concern about the lack of successful transfer from training to performance in games.

Why then in traditional approaches does the development of technique during practice not transfer well to skilful performance in a game context?

A useful way of thinking about this problem is in terms of Mind – Body dualism. In the majority of cases most golfers still train these two aspects of performance in isolation to each other.

In TGfU the tactical, mental, technical and physical aspects of the game are integrated into a performance context during training. This approach is based on problem solving; the games set problems for children to solve; it creates good game players who are independent problem solvers and tacticians.

To finish with here is an example of TGfU from a situated learning perspective. In a traditional approach to teaching and learning, a young footballer will practice controlling the ball in a static/closed context; in a game based approach to teaching and learning, the young footballer will be asked to make controllable passes during a small sided game. This contextualised way of training forces the player to develop the mutli-disciplinary attributes of successful performance, in an integrated fashion.

So even though it is now more than thirty years since the concept was first developed, research involving this NEW pedagogy suggests that if you want to teach for control and safety, use traditional methods. If you want to help young people become better game players, use TGfU

References

Kirk, D (2005) Future Prospects for Teaching Games for Understanding. In Teaching Games for Understanding

 Kirk, D and MacPhail, A (2002) Teaching Games for Understanding and Situated Learn­ing: Rethinking the Bunker-Thorpe Model, Journal of Teaching in Physical Education, 21, 177 -192

Light, R (2005) Making Sense of Chaos: Australian Coaches Talk About Game Sense. In Teaching Games for Understanding