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Coaching styles and activity design

This is an excerpt from Sport Skill Acquisition by Dave J Collins & Jamie Taylor.

By Michael Ashford and Jamie Taylor

Previous work has suggested that coaches have two broad categories of coaching methods making up their approach to shape performers’ skill learning (e.g., Muir and North 2023). These can be categorized as (1) activity design and (2) coaching style. Activity design refers to the performer experience, which is shaped by activities introduced by a coach. Coaching styles capture two-way interactions between a performer and coach across a coaching episode rather than a distinct moment in time (Pill et al. 2021). How these categories of methods might be considered as part of a coach’s planning is exemplified in figure 5.1, with intentions for impact flowing from the bigger picture nested plan (see chapter 3) and followed by planning of activity design and coaching style.

In tables 5.1 and 5.2 we draw on a pragmatic blending of approaches where coaching methods are perceived as options to select from in practice, with conditional evidence informing their selection in some places but not in others. Table 5.2 is shown in the coaching styles section.

Activity Design

The broad coaching method of activity design captures how coaches can design activities to support a player’s experience to progress toward a desired intention. Figure 5.2 captures key considerations in the effective design of activities for skill learning, which we will now explore in detail. Williams and Hodges (2005) studied the structure of activities focusing on two main features: the variability of practice and contextual interference. These work from constant to variable and from blocked to random. Previous research suggests that constant practice of repeated attempts of a single skill or technique leads to short-term success (Breslin et al. 2012). In such cases, however, a lack of performer understanding and deliberate involvement might lead to boredom and a lack of transfer (Taylor et al. 2023). Instead, variable practice can result in limited success initially but, if applied appropriately, might yield long-term learning and transfer (Williams and Hodges 2005). Blocked practice has been found to be useful for short-term success and in early stages of skill-acquisition (Li and Wright 2000), where it can increase the self-efficacy of performers (Abraham and Collins 2011b), but sole use is often found to limit transfer to performance (Williams and Hodges 2005). Random practice is often detrimental to short-term performance as contextual interference increases (cf. Magill 2011), but it enhances long-term retention and learning.

The same conditionality of coaching methods also has been suggested by advocates of methods of skill development (Renshaw et al. 2019b), though perhaps more tightly parameterized by the two main frameworks used to inform skill-acquisition using the ecological approach: (1) nonlinear pedagogy (NLP; for more detail, see Chow 2013; Correia et al. 2019) and (2) the constraints-led approach (CLA; for more detail, see Renshaw et al. 2019a). Authors advocating for these frameworks have offered alternative conceptions of activity design to move away from part-progressive methods of coaching, instead suggesting that coaching methods should in turn be less linear in nature. Table 5.1 demonstrates the definitions of each of the five pedagogical principles of NLP: information-movement coupling, manipulation of constraints, attentional focus, representativeness, and functional variability. Authors have built on this work to offer four distinct environment design principles making up the CLA, including the session intention, constrain to afford, representative learning design, and repetition without repetition. Session intention should drive the performer’s experience and be aligned with the performer’s intentions and needs (Renshaw et al. 2019). Constrain to afford makes use of practice conditions that invite engagement with specific affordances; for example, by providing a target zone on a fairway for a golfer driving off the tee, the coach might facilitate implicit skill development through information-movement coupling. For both ideas, representativeness of the competitive environment is essential. In this example, the fairway cannot be too narrow (or too broad). Finally, repetition without repetition captures the idea of functional variability, that no movement is absolutely identical or repeatable. Under this thought process, the golfer should explore multiple swings, something that might be encouraged using task constraints.

A few empirical articles have begun to test the efficacy of CLA interventions versus other approaches to skill learning. These studies have shown the four principles of CLA enabling tennis players to develop a larger variety of technical solutions (Lee et al. 2014); baseball players to develop greater technical execution, movement variability, and comparatively better performance outcomes (Gray 2018); soccer players to have more creative actions (Orangi et al. 2021); and baseball players to get more hits (Gray 2020). Notably, however, comparative studies also found no differences in skill-based interventions in weightlifting (Lindsay et al. 2022) or drill-based and small-sided game intervention groups in soccer (Deuker et al. 2023) and no performance differences in tennis (Lee et al. 2014). In all cases, caution should be exercised in interpreting these research findings given critique of the validity of control conditions and the challenge of comparing one entire approach to another. So far, too few studies have been conducted to allow us to reach conclusive standpoints. In short, our focus should be less on theoretical boundaries and more on the appropriate blending of coaching methods.

Historically, the activities that performers take part in have been framed in multiple ways, such as practice structure (cf. Gray 2018), learning activities (Muir and North 2023), training activities (Till et al. 2019), or practice design (Hodges and Lohse 2022). Here we adopt the label activity design to reflect that the acquisition of skill does not just happen on the pitch, court, grass, or arena. It can also happen off field during meetings, debriefs, video sessions (Ashford et al. 2023; Richards et al. 2017), or indeed whenever the performer is reflecting, something very common at high levels (cf. chapter 7). Similarly, activity design may not be set up with the purpose of learning and might be framed toward maintenance or building confidence. The question is whether these experiences happen by design or by chance. Therefore, we identify three key foci to enable effective blending of approaches: task constraints, the focus of the activity, and the nature of the activity.

Task Constraints

In the design of a performer’s skill learning and performance, the manipulation of task constraints is common among different research perspectives. Recent reviews from ecological (Araújo et al. 2019) and cognitive (Williams and Jackson 2019) research approaches advocate the manipulation of constraints to support skill learning. Importantly, however, differences arise regarding the explicit (Ashford et al. 2023) or implicit (Renshaw et al. 2019) use of constraints in practice. Advocates of the constraints-led approach to skill-acquisition suggest the design principle of constrain to afford as being central to effective activity design (Renshaw et al. 2019). Put simply, this means that the task constraints employed within an activity should shape an affordance landscape and, in turn, encourage repetition without repetition, whereby participants are asked to repeatedly explore the execution of a skill without a need or desire to repeat the exact same movement twice (Woods et al. 2020). By this definition, constraints are a constant in every activity because an affordance landscape is always available if a performer can perceive it (Wilson et al. 2018). Under this approach, task constraints such as this can create subtle bridges to the skillful movement in an implicit fashion. For example, a rugby coach may set up an activity that challenges four attackers to score versus two defenders in scoring channels, placed at the two touchlines of a very wide pitch. The activity challenges the players to score, while implicitly, it is challenging the players to execute passes over a wider distance than they usually would.

In contrast, activities where skillful solutions are explicitly shared with players may support performers to understand why the constraints of an activity will shape their skill learning, creating motivation and buy-in to skill learning. Thus, the careful blending of task constraints from different research perspectives can support coaches to consider the conditionality in how they may be employed. First, methods of activity design may afford implicit affordances through information-action loops without reference to knowledge (Correia et al. 2012). Second, coaches can create explicit epistemic affordances, where declarative and procedural knowledge sources guide the perceptual strategies of performers and their requisite movement responses (e.g., I know where to look and what I am looking for). In this regard, constraining to afford implicitly may be summarized by suggesting that individuals must move to perceive or perceive to move, while explicitly, it may be captured by suggesting that what we know determines what we see. In keeping with the rest of the book chapter, however, evidence would suggest there is a time and a place for both (cf. Ashford et al. 2022). Thus, it is the question of whether constraints are applied implicitly or explicitly that forms appropriate blending of approaches through activity design.

The Focus of the Activity

The notion of functional variability in skilled movement is universally accepted in the skill- learning literature (Magill and Hall 1990). No movement is ever identical, even for the most skillful expert in their sport executing a skill that requires a consistent outcome (cf. Portus and Farrow 2011). However, theoretical implications have suggested that this means that working toward optimal technical models is an example of poor practice (Gray 2020). In some cases, especially for more open movements like an open play pass in team sport, a higher bandwidth of variability for effective movement solutions seems logical. For more closed skills, the bandwidth of variability for an effective solution may be tighter. For instance, Green, Tee, and McKinon (2019) conducted a review of studies exploring maximal force production in a scrummaging position in rugby union. Functional variability was a factor, but only from a position of consistent angles at the hip, knee, and ankle joints enabling maximum horizontal force. We suggest that a coach’s focus on skill learning, and by extension the performer’s focus, should embrace the notion of functional variability. However, skill templates that do not limit performers’ movement but perhaps (from an ecological standpoint) shape the search through a set of principles will promote enhanced understanding, learning, and performance over time (e.g., using skill templates with para canoeists; Simon, Collins, and Collins 2017).

The Nature of an Activity

The notion of desirable difficulty is one strongly evidenced in the skill-learning literature (e.g., Yan, Guadagnoli, and Haycocks 2019). Desirable difficulties (Bjork and Bjork 2011) refers to making things just hard enough, but not too hard, to promote learning. This often includes slowing learning down for the performer. However, there is conditionality in how difficulty can be scheduled for performers. On one hand, a massed block of incremental difficulty may be applied progressively, task by task and session by session. Instead, difficulty may be scheduled differently by leaving spaces and distributing challenge between weeks, raising the challenge when a movement is revisited. Therefore, we suggest that coaches should engage in both forward and backward thinking to consider how difficulty is scheduled for a performer with reference to skill-acquisition over time. This can be conducted with a careful, evidence-informed selection of key concepts (see table 5.1) suitable to frame an appropriate performer experience.

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