Structured and smooth practice session? A potential red flag.
It’s intuitive to observe a practice session of any sport which runs smoothly, without many errors, with players repeating the same drill ad nauseum and think, “these guys are good – they work so well together, the training looks so slick.” Now sometimes, this might well be the case – context is of course important to understanding what is being observed. Moreover, there is sometimes reason for more straightforward sessions depending on factors such as the skill level of the athletes involved, how close the session is to competition and the competence of the coach. However, a session in which there are very few mistakes and military-style precision are often in fact tell-tale signs of a pedagogical approach to practice design which fails to help those taking part grow.
Traditionally, linear pedagogy has dominated the underpinning of practice design. It presumes a ‘one-size fits all’ coach-led approach, focusing on technical demonstrations, repetition and ‘blocked practice’ (Moy et al., 2015). The purpose is to acquire technical skills in an isolated setting (i.e., without game-context) and latterly introduce tactical and rule aspects of the game (Mitchell et al., 2006; Praxedes et al., 2018). These models often lead to the development of passive players, who often just repeat a coach’s instruction. Although such an explicit approach can mean athletes are able to pick up a movement or skill quite quickly, making them look particularly competent in an isolated training session, this approach ultimately makes it difficult for players to develop cognitive skills such as contextual decision-making (Allison and Thorpe, 1997).
As such, in order to enhance preparation for athletes, practice methodologies ought to be designed which facilitate learning opportunities that promote personal, innovative and adaptive performance behaviours (Correira et al., 2019). The framework of non-linear pedagogy advocates the key methodology of manipulating constraints to facilitate learning (Chow et al. 2006; Renshaw et al. 2016). Grounded in ecological dynamics, this approach highlights the following design principles (Chow, 2013):
- Representative learning design – situations that reflect key aspects of a performance environment, which athletes use as information to regulate their actions;
- Developing game-relevant information-movement couplings, in order for players to develop a perception, decision and action learning loop that reflects the needs of their sport;
- Functional variability – learning designs that promote exploratory activity and adaptive behaviours;
- Prioritising an external focus of attention to reducing conscious movement control. This allows players to create movement patterns in a more procedural fashion, implicitly exploiting available self-organising processes. Such an approach encourages task-relevant focus and reduces the chances of ‘choking’ under perceived pressure.
Such an approach, observationally, will often look ‘messy’ to begin with. That is to say, mistakes will be made, and players will all invariably carry out movements and skills in different ways. However, it allows players to take ownership, master their own development and learn their own unique responses to the environment that they come up against. Now that is not to say that non-linear pedagogy is a silver bullet for coaches and practitioners. Pragmatism is also important here, as undoubtedly explicit instruction and isolated technical practices can have their place within coaching approaches.
What’s important is for those designing practices to self-reflect on their coaching philosophy. Specifically, the following questions could be particularly helpful: why am I using this approach and am I able to justify it? The answers to these won’t only help develop coach knowledge and understanding, they will enhance practice designs to give their players the best chance of developing into the athletes they wish to become.
References:
Allison, S. R. & Thorpe, R. (1997). A comparison of the effectiveness of two approaches to teaching games within physical education: a skills approach verses a games for understanding approach. Brit J Physl Educ, 28, 9 – 13.
Chow, J. Y., Davids, K., Button, C., Shuttleworth, R., Renshaw, I. and Araújo, D. (2006). Nonlinear Pedagogy: A Constraints-led Framework to Understand Emergence of Game Play and Skills. Nonlinear Dynamics, Psychology and Life Sciences, 10, 71 – 104.
Chow. J. Y. (2013). Nonlinear Learning Underpinning Pedagogy: Evidence, Challenges, and Implications. Quest, 65, 469 – 484.
Correia, V., Araújo, D., Duarte, R., Travassos, B., Passos, P. & K. Davids. (2012). Changes in Practice Task Constraints Shape Decision-Making Behaviours of Team Games Players.” Journal of Science and Medicine in Sport, 15, 244 – 249.
Mitchell, S., Oslin, J. & Griffin, L. (2006). Teaching sport concepts and skills: A tactical games approach (2a ed.). Illinois: Human Kinetics.
Moy, B., Renshaw, I. & Davids K. (2015) The impact of nonlinear pedagogy on physical education teacher education students’ intrinsic. Phys Educ Sport Pedagog.
Praxedes, A., Del Villar, F., Pizarro, D. & Moreno, A. (2018). The Impact of Nonlinear Pedagogy on Decision-Making and Execution in Youth Soccer Players According to Game Actions. Journal of Human Kinetics, 62, 185 – 198.
Renshaw, I., Araújo, D., Button, C., Chow, J. I., Davids, K. and Moy, B. (2016). Why the Constraints-Led Approach is not Teaching Games for Understanding: a Clarification. Physical Education and Sport Pedagogy, 21, 459 – 480.