My work is centred on the following statement: to support coaches in delivering enjoyable and engaging learning experiences. There are several key words within that “mission statement”, and one of them is learning. I am looking to support coaches deliver sessions that their athletes learn from. Learning can be described as developing a more functional relationship between an athlete (or coach) and their environment (Wood et al., 2022). Without getting too deep into representativeness (discussed more here), it is important that for an athlete to develop a stronger relationship with their environment, they must spend time in that environment, or environments that are similar (i.e. so their skills can transfer). However, representativeness must also be balanced with suitable challenge; and an impoverished task, while not suitable for representative learning or transfer, may provide a suitable challenge for an athlete to grow (detailed below in the challenge-based framework - an athlete may learn, but does it transfer?). In short, the learning experience is directly influenced by the initial skill level of the athlete.
Coaching hurling in Brisbane. With next to no opportunities to play hurling in schools or clubs in Australia, all players are novices - which this directly influence my practice design and my coaching strategies during the session.
With my key focus point as a practitioner (and researcher) being on learning, or developing skilled athletes (which I have also touched on here), I have been working to identify a few key non-negotiables/rules/governing laws that I would encourage coaches to abide by, a framework to guide them. This learning design framework, made up of 4 learning design principles (LDPs), is the topic of this post. I have detailed the modified STEP model for practice design previously, and I still stand by those principles (as I referred to them then). But on reflection, they could be better framed as 1) methodological considerations that can all be manipulated to achieve any given LDP; or 2) micro-principles of practice design (focused on the design of practice tasks), while the LDPs can be considered as principles that guide a coach’s intention/reflection. Either way, I think there is room for them all, and my aim is not to hinder, but rather help practitioners apply key principles of skill acquisition to their practice. My four LDPs are:
Athlete-centred environment
Active learning time
Concise communication
Optimal challenge
Athlete-centred environment
Lots of programs everywhere claim to be athlete-centred and it took me a long time to figure out what athlete-centred means, or more specifically what it means to me. An athlete centred environment, in my view, is an environment where athletes are making decisions. This can occur on two levels, 1) decisions on the execution of skills within a task; and 2) decisions around the designing of tasks (Representative co-design (Woods et al., 2021)).
Within a task, for an athlete to make decisions, variability must be present. If variability is not present, then athletes have no decision to make. A task which requires an athlete to move from one cone to another, and on their way must execute a pre-determined skill is not an athlete-centred task. It is coach-centred. The coach is making the decision. The athlete is just executing, the drill is action focussed. This may be suitable for novice athletes and allow them to grow, but it will not challenge the skilled athlete to learn or become more adaptable/skillful (read more about skill adaptability; more on challenge point in the final principle). The easiest way to force an athlete to decide is to include an opposition. Game-based practice or play is a crucial ingredient in the development of skilled athletes.
Representative co-design involves inviting athletes to give their opinions on how to design practice tasks. While empirical knowledge from research is an important part of the design of training, it must be combined with experiential knowledge of practitioners to enrich the training experience. To further enhance the training experience, athletes can offer their views on what they see and the issues they face when on the field of play. This enables athletes to be more autonomous and take control over their learning experience. The training experience then becomes a collaborative environment rather than an autocratic dictatorship.
Active learning time
Active learning time (ALT) is a good measure for coaches to gauge how much activity their athletes are getting within their session, particularly if there is a big group. ALT is calculated by dividing the number of active athletes in a task by the total number of athletes, multiplied by the duration of a task (Eather et al., 2019). For example, a task that involves 3 athletes per rep out of a group of 22, for a duration of 8 minutes, ALT would be calculated:
(3/22) x 8 = 1.09 mins ALT
If we extrapolated this to a 60-minute session, it would read as:
(3/22) x 60 = 8.18 mins ALT
This would inform us that even though athletes are training for 60 minutes, they are only involved in activity for just over 8 minutes of the session. If we compare this to a game scenario one game of 5v5 and two games of 3v3, for 20 mins, ALT would be calculated:
(22/22) x 20 = 20 mins ALT
Which suggests that for 100% of the training session, athletes are active (not considering water breaks etc.). This is not to suggest that athletes should be active for 90-100% of their sessions every session, sometimes drill work may be necessary. But it is a measure to guide a coach towards what they want to achieve.
Another measure that may be more familiar to some practitioners is time on task (TOT). TOT involves calculating the time that an athlete is active in a task, compared to the time that an athlete is inactive in the same task. For example, in a shooting exercise in soccer, a player must shoot and then turn and receive a pass and lay it off for the next shooter. In total, the time a player is active is 8 seconds. After this the player joins the back of the line to wait for their next turn, which turns out to be a 45 second wait. This task continues for 10 minutes. TOT could be calculated as:
8/45 = 18%.
Extrapolating this to a 60-minute session, athletes would be actively engaging in an activity for 10.8 minutes.
An important point is that 90-100% ALT or TOT is not necessarily good. The balance is probably somewhere in between the very high and very low percentages, with it all depending on the context. However, one or both measures can be used to assist coaches in ensuring that athletess are getting an appropriate amount of opportunity to engage in learning tasks.
Data collection set-up for my research at QUT and Ambrose Treacy College.
Concise communication
Coaches communicating is something I have discussed before, and I will touch briefly on it again here. If training is set up for athletes to explore their affordance landscape, a coach instructing them on what to do is completely contradictory. If a coach is instructing the athlete on what to do, are they continuing to explore their environment, or are they just following instructions? A more suitable strategy in this instance is to utilise questioning to facilitate and gauge understanding and learning, and to guide an athlete’s attention. Questions like:
"Where is the space?"
"What else could you have done?"
"How can you make it easier for yourself/your teammate?"
"When is that a suitable solution?"
Using questioning during training like this can also be termed “coaching on the run” (Harvey & Light, 2015). Here, the coach doesn’t need to stop training, ask players to freeze or huddle up to deliver a message, they can simply ask a question to guide an athlete’s attention, and then the athlete can simply show their understanding. Certainly, there are times when stopping to check for understanding via a verbal response is important (Collins et al., 2022). In this case, stopping play (reducing ALT or TOT) to grab the attention of athletes within a session to instruct or give feedback may lead to a marked improvement in execution within the session, which could be a necessary intervention to prevent a negative response to the challenges of the task. An important consideration in this instance is performance vs learning, and what the session intention is.
However, in line with balancing representativeness and suitable challenge (i.e. context matters), there may be times that giving instrutions or feedback, or cueing are appropriate, suitable and necessary coaching strategies. Viewing this through a constraints-led approach, an instruction is a form of constraint, with a constraint being defined as a source of information that regulates action (see more about constraints-led coaching). Instructional constraints may be required depending on the skill level of the athlete, or other contextual factors like when the coaching intervention is taking place. One example being half-time in a youth or adult rugby fixture (novice or skilled athletes). It can be a short break, and coaches may have 60-180 seconds to deliver a message. Here, coaches don't have time to ask the group and potentially get 10 different answers. They don't have time to guide the conversation around to where they want it. They want to guide their athlete's performance, and an instructional constraint might be the quickest and most efficient way to do this.
Optimal challenge
This is possibly one of the most critical considerations for coaches when designing their training tasks, and something I regularly refer to and discuss with coaches. The extended challenge-based framework presents three types of practice: practice to learn, practice to transfer and practice to maintain skills (Hodges & Lohse, 2022; see below). To simplify, this can be framed as the goldilocks principle of practice design – coaches do not want practice that is too easy because the difficulty is too low (no learning takes place), coaches do not want practice that is too hard because the difficulty is too high (this may be detrimental to the player’s confidence), but they want just the right amount of difficulty in practice, to lead to desirable difficulties (Bjork & Bjotk, 2020).
Challenge based framework (Hodges and Lohse, 2022). Detailing the three types of practice.
To operationalise the challenge-based framework and the difficulty of practice, it is important to consider the impact enhanced difficulty will have on athlete performance and athlete mindset. An increase in difficulty will bring an increase in errors. Errors are not necessarily bad, but they are often viewed as a failure. Coaches could alter their relationship with errors and failure, and instead view them as learning opportunities. However, the application of the challenge-based framework is highly individual. Therefore, it is not enough to simply view the number of errors an athlete is making in response to a task. Rather, the athlete’s response to their errors is more important for the benefit of a task. Some athletes may be comfortable succeeding only four out of ten times, while others may need to succeed eight out of ten times to feel good. As athletes are complex adaptive systems (Button et al., 2021), an athlete’s response to errors could change negatively day-to-day, week-to-week, or on a longer timescale; so difficulty may need to be modified accordingly.
Practitioners could ask themselves three questions regarding their session:
What is the aim of the session (practice to learn, transfer or maintain)?
Subsequently, what is the difficulty level required?
How are the athletes responding to the difficulty?
This appraisal process can be implemented throughout a session to constantly reassess the practice design within a given session. It is a complex problem. For example, if a coach plans a practice to learn session, with a high relative difficulty, but the athlete(s) respond very negatively, the coach has 2 options:
Push the athlete through the session regardless of their response, and hope that the motivational cost of the excessive challenge is not too much.
Review the session aim and adapt accordingly.
There are pros and cons to both, and that’s where a coach needs to be agile in their approach to make a well-informed decision on how to progress.
Summary
The four LDPs (athlete centred environment, active learning time, concise communication, optimal challenge) can be used as a framework for practitioners to ensure that the training environment is going to maximise the learning experience for athletes. I utilise them when working with coaches to provide a framework for myself and the coach to guide a debrief. I ask questions like:
"How many decisions did athletes make?"
"What were players doing in between shots (long lines of waiting)?
"Are your athletes dependent on your feedback? Are they able to detect and correct errors?"
"Did players get better?"
The most important question: "Why did you do that?" "What were you trying to achieve?" If they don't have a strong rationale for these questions, then that dictates the coach education interventions that follow.
Combining these principles with the STEP model for practice design, PEAQ coaching behaviours framework, and taking variability (and differential learning & the contextual interference effect) into account, a practitioner will only be limited by their own creativity in the activities and sessions they design (in partnership with their athletes).
References
Bjork, R., & Bjotk, E. (2020). Desirable Difficulties in Theory and Practice. Journal of Applied Research in Memory and Cognition, 9, 475-479. https://doi.org/10.1016/j.jarmac.2020.09.003
Button, C., Seifert, L., Chow, J. Y., Araujo, D., & Davids, K. (2021). Dynamics of Skill Acquisition: An Ecological Dynamics Approach. https://doi.org/10.5040/9781718214125
Collins, R., Collins, D., & Carson, H. J. (2022). Show Me, Tell Me: An Investigation Into Learning Processes Within Skateboarding as an Informal Coaching Environment [Original Research]. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.812068
Eather, N., Jones, B., Miller, A., & Morgan, P. (2019). Evaluating the impact of a coach development intervention for improving coaching practices in junior football (soccer): The “MASTER” pilot study. Journal of Sports Sciences, 38, 1-13. https://doi.org/10.1080/02640414.2019.1621002
Harvey, S., & Light, R. (2015). Questioning for learning in game-based approaches to teaching and coaching. Asia-Pacific Journal of Health, Sport and Physical Education, 6, 1-16. https://doi.org/10.1080/18377122.2015.1051268
Hodges, N. J., & Lohse, K. R. (2022). An extended challenge-based framework for practice design in sports coaching. J Sports Sci, 40(7), 754-768. https://doi.org/10.1080/02640414.2021.2015917
Wood, M. A., Mellalieu, S. D., Araújo, D., Woods, C. T., & Davids, K. (2022). Learning to coach: An ecological dynamics perspective. International Journal of Sports Science & Coaching, 17479541221138680. https://doi.org/10.1177/17479541221138680
Woods, C. T., Rothwell, M., Rudd, J., Robertson, S., & Davids, K. (2021). Representative co-design: Utilising a source of experiential knowledge for athlete development and performance preparation. Psychology of Sport and Exercise, 52, 101804. https://doi.org/https://doi.org/10.1016/j.psychsport.2020.101804
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