Is there more to representative learning design than meets the eye?

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 Is there more to representative learning design than meets the eye?


                                              Photo by JESHOOTS.COM on Unsplash

This was an article that I originally wrote for my old blog before I started a new one here


In this first blog post I’m going to be taking a closer look at the concept of ‘Representative Learning Design’ (RLD) in sport. The concept comes from work by scientist Egon Brunswick from the 1950’s. Brunswick’s idea was that the constraints of the experimental design should closely match the constraints of the environment that the results should apply to. RLD is a very important concept for coaches to understand and will help them to design more valuable sessions for their athletes.

What is Representative Learning Design?

“RLD is a framework for assessing the degree to which experimental or practice tasks simulate key aspects of specific performance environments” (Krause et.al, 2018).

The basic concept behind RLD is examining how closely practice tasks replicate the demands of competition. Tasks that closely simulate the demands of competition/performance environment are considered highly ‘representative’ while tasks that don’t are considered to be low on the scale of representativeness. The coach will have to have a good knowledge of the demands of the competition/performance environment to design more representative tasks for practice. However, the coach will also need to understand that the demands for each of the individual athletes will be different and will need to take this into account when designing the sessions

Why is it beneficial for coaches to understand this concept?

“One of the most important concerns for coaches is the degree to which what one learns in practice transfers to the competitive environment” (Renshaw et.al, 2019)

Is what I’m doing in practice going to help my players get better in the competitive environment? This is an important question that every coach should be asking themselves.  A key point here is that ‘transfer’ can be both positive and negative. What you work on in practice can also be detrimental to performance in competition. If the practice is helping the players performance in the competitive environment, we would consider that ‘positive’ transfer while if what you are doing in practice is making performance worse, we would consider that ‘negative’ transfer.

How can we make sure what we are doing will transfer to the performance environment?

“When practice replicates the performance environment, skills are more likely to transfer” (Krause et.al, 2018)

When the practice design replicates key aspects of the performance environment the learning is more likely to transfer. Because the performers are getting used to performing the skill in an environment that adequately represents some of the key aspects of the performance environment the skill is more likely to transfer.

“Practice task designs with non-specifying information variables lead to slower rates of learning because of the less effective transfer between practice and competitive performance.” (Button et.al, 2020)

On the other hand, if the practice design contains information that is irrelevant to performance in the performance environment it will have less effective transfer and could potentially even have a negative impact on performance.  

What exactly do we need to represent in practice design?

There are few elements to representative learning design that need to be met for a task to be considered ‘representative’.

(i)“Representative learning design in practice is predicated on the key principle that movements typically need to be coupled to specifying perceptual variables in practice tasks that simulate competitive performance environments.” (Button et.al, 2020)

‘We must perceive in order to move, but we must also move in order to perceive’ (Gibson 1979). When an individual moves, further information is created and this in turn supports further movements. The coach must not separate perception and action from each other, the two are interwoven. The coach needs to maintain the relationship between key sources of information and action for the players. The key source of information in tennis is the movements and shots of the other player. The actions that the player selects is based on the information they are getting from the other player.

(ii) “practice simulations need to be based on a detailed sampling of the informational variables available in specific performance environments for athletes to use for regulating their behaviours.” (Button et.al, 2020)

The information that is available to performers during practice should aim to replicate the information that’s available to the performers during competition. Skilled performers are those that are more ‘sensitive’ to the information that is available to them. They only become more skilled through direct exposure to this information. An example of this is how ‘expert’ players are a lot more skilled at picking up information from the actions of the player hitting the shot on the other side of the net or reading the location of the serve based on the other players actions. Therefore, coaches need to make sure that the informational variables in practice are as similar as possible to the informational variables available in competition.

(iii) “the constraints of training and practice need to adequately replicate the performance environment so that they allow learners to detect affordances for action and couple actions to key information sources within those” (Pinder et.al, 2011)

This is a topic that I will be diving much deeper into in a future series of blog posts. For now, I’m going to give a very brief explanation. Constraints are boundaries that limit the solutions the performer can use the solve the movement problem. While they limit the number of solutions, they don’t prescribe the solution that the performer must use. There are 3 categories of constraints: task, environmental and individual. The coach must make sure that the constraints of the practice tasks adequately match the constraints of the performance environment. Court surface is an example of an environmental constraint. If a player is getting ready to play a grass court tournament they should be playing on grass in practice or a surface that replicates the demands of a grass court as much as possible.

(iv) “In sport, performers need to be able to adapt to task constraints while performing under differing emotional states induced in competitive performance that can influence their cognitions, perceptions, and actions (Headrick et.al, 2015)

The coach must try to simulate the emotions that would be present during competition during practice. This is often an overlooked element of RLD. Emotions can have a significant effect on performance and the players must become ‘comfortable being uncomfortable’. Increased levels of emotion during practice also stops players ‘going through the motions’. A key point here is that the level of emotion the coach arouses needs to be appropriate for the player.

Conclusion

I have given a brief overview of the theory behind RLD and I will be going into how to apply some of the theory in my next blog post. I am going to put links to further resources below that you could visit if you wanted to dive deeper into the topic and they do the topic a lot more justice than I could in this blog post. If there are any questions or feedback about anything that is in the blog, I’d love to hear. I’m going to finish the blog with this question. ‘Do your practice activities look and feel like the competition? If not, why?’

Key terms

  • Action-fidelity- “Action fidelity promotes the idea that a coach must ensure that the movement solutions the performers exhibit and develop in the practice environment will be effective when transferred to the performance environment” (Renshaw et.al, 2019)
  • Functionality- Functionality refers to the degree to which an athlete is able to use the same information sources (i.e. visual cues) present during competition to contextualize their decisions and movements (Pinder et.al, 2011)
  • Specifying Info- Sources of information that are useful in regulating specific actions in a number of different scenarios
  • Non-specifying info – This is the information that is not useful for regulating actions.
  • Affordances- opportunities for action.

Resources/Further Information

Books

  • Non-Linear Pedagogy in Skill Acquisition: An Introduction
  • Dynamics of skill acquisition: An ecological dynamics approach. Human Kinetics Publishers.
  • The constraints-led approach: Principles for sports coaching and practice design. Routledge.

Papers/Research Articles

Podcasts

References

  • Button, C., Seifert, L., Chow, J. Y., Davids, K., & Araujo, D. (2020). Dynamics of skill acquisition: An ecological dynamics approach. Human Kinetics Publishers.
  • Headrick, J., Renshaw, I., Davids, K., Pinder, R. A., & Araújo, D. (2015). The dynamics of expertise acquisition in sport: The role of affective learning design. Psychology of Sport and Exercise, 16, 83-90
  • Krause, L., Farrow, D., Reid, M., Buszard, T., & Pinder, R. (2018). Helping coaches apply the principles of representative learning design: validation of a tennis specific practice assessment tool. Journal of sports sciences, 36(11), 1277-1286.
  • Pinder, R. A., Davids, K., Renshaw, I., & Araújo, D. (2011). Representative learning design and functionality of research and practice in sport. Journal of Sport and Exercise Psychology, 33(1), 146-155.
  • Renshaw, I., Davids, K., Newcombe, D., & Roberts, W. (2019). The constraints-led approach: Principles for sports coaching and practice design. Routledge.

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