Figure 5.1 1 vs 1 shooting/dribbling practices in field hockey are ‘fed’ by the coach with players rotating their receiving positions to create repetition of practice, without repetition.
5 The environment design principles
In the first three chapters we introduced the theoretical concepts of ecological dynamics to provide practitioners with the knowledge base to design effective CLA sessions. However, the key challenge for coaches is how to put these ideas into practice. To emphasise the key role that coaches play in the creation of effective practice environments, we proposed that coaches should see themselves as environment architects or learning designers. However, integrating complex theoretical ideas into learning design can be highly challenging as employing new ideas in practice can be a daunting and confusing task. It is this gap, between the theoretical underpinning and the practical application of a CLA, that is often cited as the most significant barrier coaches face as they negotiate the pragmatics of environmental design (Greenwood et al., 2014). The aim in this chapter is to address this issue, by introducing the Environment Design Principles (EDP). The EDP are provided as a potential solution to this problem, a bridge that practitioners can use to link the complex theoretical concepts in successful practical applications. Just like a bridge, the EDP are designed to support the practitioner’s journey, providing a clear route between what would otherwise be two disconnected and distant locations (i.e. theory and practice). We hope that, through engagement with the four Environment Design Principles, coaches will feel more confident in exploring and adopting CLA into his or her practice. In summary, we propose that the EDP framework underpinned by the theoretical concepts of ED (Chow et al., 2016) discussed in Part I, will support a more nuanced understanding of CLA and enable practitioners to make more accurate and informed decisions in the design of practice environments. Ultimately, the provision of more innovative and robust practice environments is likely to facilitate a greater level of transferable and targeted skill development.
Environment Design Principles
The EDP operationalise the CLA by providing user-friendly principles to support coaches in the practice environment design process. The EDP consist of four principles that capture the core theoretical foundations of ecological dynamics (ED). The key principles are: (1) Session intention, (2) Constrain to afford, (3) Representative learning design (including purpose and consequence), and (4), Repetition without repetition (which is framed around manipulating variability to enhance adaptability and increase or decrease (in)stability). Each principle has its own unique purpose, resultantly impacting upon decisions a coach will make in the environment design process. While each principle is valuable in its own right, it is through the integration of all four principles that the framework is able operate effectively and efficiently. In this way, the EDP looks to support practitioner decision-making, as coaches engage in the messy process of practice design. We will introduce and unpack each principle throughout this chapter.
1. Session intention
Guiding principle: the intentions of the session act as an overriding and organisational constraint.
Principle 1 emphasises the role and importance of session intention in the environment design process. The intention of the session is an integral driver of coaches’ decision making as they plan, prepare and deliver their practice environments. The importance of intentions and the impact they have on the interaction between performers and the landscape of affordances was introduced and explored in Chapter 3. As environment designers we need to appreciate that intentions do not just impact on our decision-making as coaches, but act as an over-riding constraint (individual) on performer and team cognitions. These, in turn, influence the perceptions and actions of performer(s) within a practice environment. Therefore, as a coach engages in the environment design process, it is critical that they establish the primary goal(s) (intentions) of the practice session as a first step. In practice, a coach has the opportunity to shape emergent behaviour through the application of a CLA. As previously indicated, the various constraints can be added, removed, adjusted or repositioned within the practice environment. This manipulation process is both complex and nuanced, requiring careful consideration, consideration that is governed by the session intention.
The goal of the practice environment can vary considerably for the coach and performer. For example, the intention of the session could be to learn a new skill, a cricket player developing a new shot to add to their repertoire, or a gymnast developing a new move on the beam. Alternatively, it may be the aim of the coach to improve players’ tactical awareness while executing a zonal defensive system in soccer. The coach may wish to enhance the performer(s) collective understanding of counter-attack principles in an ice hockey context. Moreover, a coach may wish to develop the ability of his high jump performer(s) to cope and ultimately execute under extreme pressure. Or, perhaps, the intention of the session is to invite players to attune to the performance environment. In addition, with the increased input from sport science it is becoming increasingly common for practice environments to be specifically designed with the physical preparation of performers as the primary objective. For example, there is significant research on the use of small-sided games as a conditioning tool for soccer players (Hill-Haas et al., 2011). Moreover, the primary goal of the session could be to promote learning, therefore the practice environment needs to be designed to allow learners the opportunity to explore, exploit or execute solutions to the problem they have been set. As previously alluded to, coaches need to appreciate that intentions act as an over-riding constraint on performer and team cognitions, perceptions and actions. With this in mind, it is proposed that there must be an alignment between the intentions of the coach and the intentions of the learner(s). A disparity between a performer’s intentions and a coach’s desired actions can lead to failure and ultimately frustration for both the coach and the performer(s). It is therefore imperative that both performer and coach work to develop a shared understanding of the intention of the practice and the desirable intentions within the practice. We provide support for coaches by scaffolding this important process in Chapter 6.
The intentions of a practice session will be influenced by the timing of session. For example, if the session is in pre-season or in close proximity to a competitive performance, it will impact on the intention of the coach and the performer(s). While the development (and ultimately learning) of the performers should be at the forefront of the coach’s long-term planning, it would not be prudent for a coach to only design and provide practice sessions that promote a re-organisation of the movement system. For example, it may not be advantageous to provide a session where learning is the primary objective the day before, or morning of, an important match or performance. The potential for an increased level of failure within these sessions (and associated performer frustration) could negatively impact on the competitive performance of the individual or team. Consistent with the example above, there may be practice environments in a performer’s session, week or season where the primary goal will be performance preparation, where the performers attune to the performance environment by practising or rehearsing. For example, a tennis player may take to the court the morning of a game and rehearse by ‘practising’ against a partner, a rugby union team may participate in a ‘team run’ the day prior to competition, while it is common for a netball team to engage in a ‘surface training’ session in the lead-up to a competitive fixture.
It is integral that the intentions are matched to the needs of the performers. For example, a key consideration when setting session goals is a careful assessment of the current skill level of the learners. Appropriate knowledge of a learner’s level is essential as it guides session focus and design. Current popular learning stage models include the three-stage models of Fitts and Posner (Cognitive, Associative, Autonomous) (1967) and Newell (Co-ordination, Control, Skill) (1985). Given that Fitts and Posner’s model is underpinned and informed by an information-processing theory of motor learning, it does not fit theoretically with CLA, which is predicated on an ecological model of motor behaviour We are also of the belief that it is prudent for models to promote skill learning as the process of adapting or attuning to the environment, rather than viewing skill learning as a fixed outcome due to the connotations this promotes. The better fit for a CLA is therefore Newell’s model. However, the terms used by Newell, particularly the use of the term ‘skill’ to describe the third stage of the model, can be confusing and not helpful in the application of CLA. To address this issue, Renshaw and Chow (2018) propose a two-stage adaptation of Newell’s (1985) model. Stage 1 is a Learning to Co-ordinate phase and therefore this stage is about searching and exploring to develop intra-individual-environment or inter-individual-environment co-ordination patterns (Renshaw & Moy, 2018). Stage 2 builds on Stage 1 and assumes learners have developed basic co-ordination patterns enabling them to move into the Adaptation phase. This phase is concerned with optimising performance through developing stable, yet flexible, co-coordinative structures based on the emergent ability to exploit the individual–environment system (i.e. passive, inertial, and mechanical properties of limb movements (Davids et al., 2008). Session intentions and the subsequent learning design are therefore predicated on identifying the current needs of the performer, which are signposted by reference to the current stage of learning. Evaluation of current skill level should, therefore, be undertaken in advance of session design. Or if this is the first session with an individual or team, the first task may be used as an assessment. Here, it might be helpful to view the initial activity as a ‘pre-test’ that provides the baseline for current skill level and informs session goals. We build on this point in the next chapter using an adapted version of the GROW model (Whitmore, 2017).
2. Constrain to afford
Guiding principle: ‘design-in’ constraints to offer/invite/encourage learners to explore the opportunities for action related to the session intention.
Principle 2 brings together the concepts of constraints and affordances, challenging coaches to manipulate constraints to systematically design-in affordances to the practice environment. This principle builds on the discussion of affordances presented to the reader in Chapters 3 and 4 by operationalising them for coaches. Given that skill learning is predicated on performers learning to adapt to the environment through attunement to, and exploitation of, key affordances in that environment, it is a key requirement of constraint-led coaching to design practice environments that specifically provide opportunities for performers to become more attuned or adapted to the performance environment (Araújo & Davids, 2011a). However, it is common that performers are unable to ‘pick up’ the key affordances and coaches need to direct their performers search by using constraints that emphasise or exaggerate the presence of available affordances. This process is called constraining to afford. Essentially, this approach requires practitioners to design-in constraints that will make available desired affordances in a practice task, channelling the performer towards their availability in the landscape (Chow et al., 2016). It makes sense that the initial step for coaches is to offer the important affordances that are relevant to the session intention. Designing learning tasks through the manipulation of constraints to provide affordances for action requires practitioners to be ‘problem setters’ who are able to implicitly invite functional perception–action couplings. For example, if a squash player wishes to develop the ability to execute an effective drop shot, the environment must be designed to both offer (provide lots of opportunities) and invite (create the need for) the player to perform the drop shot. The notion of constrain to afford postulates that the decisions to act need to come via performers choosing and not being forced to attune to the affordances in the environment. It is vital to consider that the decision about when to act is as important as the action itself and the two must remain coupled to the performance environment. Indeed, just because an affordance is available does not mean an individual performer should use it; in fact, knowing when a player ‘ought’ to use an available affordance is perhaps just as important as knowing how to use it (Heft, 2003). These ideas are aligned with the suggested re-definition of affordances as ‘invitations for action’ proposed by Withagen et al. (2012, 2017).
In simple terms, well-structured environment design must offer performers the opportunity to move beyond ‘what’ they must do, and towards an understanding that allows them to construct for themselves the ‘how, why, where and when’ of movement in sport performance. In practice, helping performers to learn to recognise the affordances, when, why and ultimately how to use them, requires sampling of ‘the landscape of affordances’ from performance, and ensuring that the most important affordances are available in practice. Chapter 4 introduced and provided readers with a discussion of the affordance landscape. It is essential that the practice environment not only provides the performers with opportunities to attune to a range of possible affordances but solicits (invites) those actions. A useful strategy to aid this process is adopting the principles of exaggeration (see Renshaw et al., 2015; Bunker & Thorpe, 1982). For example, a badminton coach may use a long thin court to encourage the learner to recognise when the space is in front of or behind the opponent. This principle calls for practitioners to manipulate practice environments to encourage performers to engage with available affordances in a more effective and efficient manner as they self-organise to solve the problem presented. An additional example of this principle in action is the use of a taped (tennis) ball in cricket to offer (invite) the batter the opportunity to bat against a swinging ball. We explore in-depth examples of how a coach can adapt their environments to meet this principle in our Constraints in Action chapters located later in the book (Part III).
3. Representative learning design
Guiding principle: ensure that what the learners are seeing, hearing and feeling in the practice environment is similar to the performance environment.
Principle 3 requires coaches to consider the impact that representative design has on learning transfer. One of the most important concerns for coaches who are interested in improving performance is the degree to which what one learns in ‘practice’ transfers to the competitive environment. Representative learning design (RLD) was introduced in Chapter 2 and developed as a principle to focus coaches’ thinking by requiring them to sample the performance environment and ensure that practice and training task constraints are representative of a particular sport performance context (Chow et al., 2011; Pinder et al., 2011). Egon Brunswik (1955) termed this environmental feature: representative design. Paying attention to the principle of RLD ensures that learning tasks contain relevant informational constraints to elicit the emergence of functional behaviours and facilitates attunement to key affordances (Fajen et al., 2009). The importance of promoting the development of functional behaviours in practice (i.e. those that are effective and efficient in performance) is captured in representative task design (Brunswik, 1955) as the concept advocates the need to maintain action-fidelity (Stoffregen et al., 2003). Consequently, coaches need to sample practice environments to ensure that they have similar information flows to a performance environment, making them more representative and maintaining greater action-fidelity. In simple terms, 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. For example, learning to shoot without defenders in a basketball context has the potential to develop an ineffective movement solution when transferred to the performance environment (Gorman & Maloney, 2017). The concept of RLD calls into question the value of practice task designs that are de-contextualised through the provision of overly artificial information sources and task decomposition. As a result, these design faults may potentially inhibit the coupling of perception and action systems during task performance. This element builds on the concept of perception–action coupling presented in Chapter 2. To exemplify, in practical learning interventions, it is important to avoid designing an environment that requires performers to dribble around cones or manikins – with the intention of creating realism in ball manipulation practice. Without information from movements and locations of opposing defenders, spatial (line markings) or temporal (tempo of a ball feed) informational constraints, to exemplify, there will be little strengthening of the functional perception–action couplings required in skilled performance (see Chapter 3 for empirical research studies that support these ideas). This type of practice task design is inefficient and ineffective for all but the most novice learners, and even for that group the shelf-life of cone dribbling is limited. The limitations of this type of design exemplify practice opportunities that do not include specifying information, which can be used to regulate action. Renshaw et al. (2007) demonstrated that batting against bowling machines as opposed to real bowlers led to a re-organisation of the timing and co-ordination of a forward defensive shot and did not facilitate opportunities for batters to learn to utilise information from the bowler’s actions, a key component of expert batting performance (Müller et al., 2006). We also described an example of the limitations of ball machines in Chapter 2. We suggest that RLD embedded in a CLA allows practitioners to design experiences during practice that are more likely to have a significant impact on learning (and therefore enhance performance). A focus on learning to adapt or attune to the landscape of affordances available in performance environments, changes the focus of practice from rehearsal and the memorisation of putatively ‘perfect’ techniques (via the ubiquitous use of isolated drills), towards the engagement in functional and contextually relevant interactions. The change in emphasis from actions to interactions is an important idea in an ecological dynamics rationale for skill adaptation; the latter captures the intertwined nature of intentions, perception and action in goal-directed behaviour.
To advance these ideas of RLD further, and highlight the interaction between emotions, intentions, perceptions and actions, the concept of Affective Learning Design (Headrick et al., 2015) was developed. In simple terms, by adopting ALD, practitioners can check the representativeness of practice session by asking ‘does the practice look and feel similar to the real thing?’ Essential to this design process is ensuring that the task outcome has been given a purposeful intention and that there are clear consequences of success or failure emerging from interactions of athletes with the environment. A failure to ensure this aspect of RLD may lead to athletes ‘going through the motions’ and performing below competition intensity. Consequently, this type of practice design creates similar intentions, emotions and emergent perception–action couplings to those seen in performance context (Maloney et al., 2018).
A pause to gather your thoughts: With great power comes great responsibility – we urge coaches to be mindful and perhaps cautious of the re-organisation their practice environments are shaping. It is paramount that the self-organising process facilitates a re-organisation that will be advantageous to the player when transferred to the performance environment. For example, in soccer, placing cones on the floor for players to dribble around could promote the development of a solution where a player’s vision is directed at the ground rather than scanning the pitch. It could be argued that this would not be a functional fit and is therefore not of any use to the player in the game where there is a need to scan while in possession of the ball. In this example it is important to remember who placed the cones on the ground in the first place before becoming frustrated with a player’s movement solutions!
4. Repetition without repetition (including variability and in(stability))
Guiding principle: ‘design-in’ the appropriate amount of variability and (in)stability to the practice environment.
Principle 4 considers the concept of practice variability and requires coaches to manage how much variability they should design-in to the practice environment. Whereas much of the previous work in skill acquisition has focused on task variability (i.e. blocked versus random practice or contextual interference), variability in CLA promotes coaches to also consider and adjust the environmental variability with the aim of providing an appropriate level of (in)stability for performers.
Figure 5.1 1 vs 1 shooting/dribbling practices in field hockey are ‘fed’ by the coach with players rotating their receiving positions to create repetition of practice, without repetition.
A key feature common across sport is the belief of practitioners that we become ‘skilled’ by doing repetition after repetition. However, evidence in motor behaviour research has highlighted that repeating the same movement over and over again is an impossibility (Bernstein, 1967) and that variable practice is more advantageous to skill learning (Magill & Hall, 1990). Consequently, Bernstein suggested embracing repetition without repetition, thereby providing environments that allow performers to undertake lots of repetitions of achieving the same outcomes in different ways. He proposed that ‘Practice is a particular type of repetition without repetition’ (Bernstein, 1967, p. 134), and strongly advocated against a type of practice that is ‘merely mechanical repetition by rote’, which had already been discredited in his opinion. In designing ‘repetition without repetition’ in practice, performers are provided with opportunities to search and explore to create a range of effective and adaptable movement solutions. Essentially, Bernstein highlighted the need for flexibility in skill development to encourage learners to seek different solutions to the same or similar problems. This principle builds on Chapter 2 where we introduce the concepts of dexterity, degeneracy and repetition without repetition.
Building repetition without repetition into practice is essential in dynamic, complex environments such as sports. For example, in a field hockey game, no two passes are ever identical as the position of team members, opponents, the state of the game, the surface, the time and space available to make a pass, are never the same. Consequently, practice must offer the player lots of opportunities to pass the ball over different distances, in different directions and at different speeds to different team members or to different places for the same receiver. Players must be given opportunities to learn to adapt their hitting co-ordination patterns to cope in many different dynamic situations (see Button et al., 2006). Similarly, in an individual sport like swimming, adaptability is crucial for success and repetition without repetition is a key factor in its emergence. For example, if one was to consider the swimmer who was the best in their state, the majority of their competitive swimming would be undertaken in the centre lanes (the fastest swimmers are allocated the centre lanes in races). It is also most likely that the swimmer is often leading the race and does not have to deal with the wake created by swimmers being ahead of them. Indeed, in the past swimmers have exploited the wake of leading swimmers (see A pause to gather your thoughts, below). However, once the swimmer enters higher-level competitions the chances are that they will be required to swim in the outside lanes next to the walls. It makes sense therefore that swimmers should be prepared for competition by swimming in different lanes and through careful handicapping swimmers could practise ‘chasing’ opponents as well as leading. It would also help prepare swimmers for situations such as being last off the blocks in a short race and hence knowing how best to pace the race. Of course, the added advantage of adding variability like this, is that the swimmer has more opportunity to learn to embrace and exploit the tactical and psychological impact of different race scenarios (see the discussion of ALD above).
A pause to gather your thoughts: At the 1984 Summer Olympics, a 17-year-old Brisbane boy, Jon Seiben, competed in the 200 m butterfly. As a novice and due to his diminutive (175 cm) stature for an elite swimmer (Seiben was known as the Shrimp), he was seen as a rank outsider and given no chance of winning any colour of medal, let alone a gold. Seiben’s challenge was indeed a steep one, given he was up against the legendary Michael Gross, the world record holder, who was known as The Albatross given his 200 cm height and 225 cm wingspan. He also faced the 100-metre butterfly world record holder, Pablo Morales of the United States. However, Seiben and his coach, Laurie Lawrence, had a plan. They decided to swim in the wake of Gross and Morales in the first 150 metres and then attack in the last lap. The strategy worked a treat and Seiben stunned the swimming world, claiming the gold medal in a world record time of 1 m 57.04 s, more than four seconds faster than he had ever swum before.
The previous examples highlight that, practically, coaches can adjust the amount of variability within the practice environment through the manipulation of individual (e.g. intentions, optimising strategy to match the intrinsic dynamics), environmental (e.g. different opponents, surfaces or water conditions) or task constraints (e.g. different competition scenarios, or pitch sizes). The key question for coaches is how much variability to design-in to the practice environment for each performer or group of athletes. Additionally, coaches need to decide whether they are going to control the amount of variability through the systematic or random manipulation of constraints. Orth et al. (2018) addressed these challenges, suggesting that practitioners can utilise systematic and unsystematic approaches by the manipulation of constraints (Ranganathan & Newell, 2013). The unsystematic manipulation of constraints involves practitioners constantly and randomly manipulating task and environmental constraints, for example, randomly changing racquet sizes or ball types when teaching tennis (Lee et al., 2014).
The amount of variability designed into a session needs to be matched to the performer’s current level of skill. For the beginner level player who is at the co-ordination stage, low-task and environmental variability may be initially beneficial to guide exploration towards one or two functional solutions. In contrast, the more expert performer, who is at Stage 2 (the adaptability level), may be presented with greater variability in individual, task and environmental constraints to promote more dexterous behaviour. Rosser (2008) discussed the notion that complex systems (i.e. human beings or teams) are open to (in)stabilities, exhibit complex chaotic behaviour, and that, in attempts to self-organise against these fluctuations, the process of pattern-formation (system re-organisation) takes place. Put simply, the learners in the practice environment will endeavour to make sense (self-organise) of the chaos (instability) they are presented with by forming functional action solutions. This leads us to the purposeful manipulation of control parameters (via task constraints) in the aim of deliberately moving performers into less stable areas to promote a re-organisation of the movement system (Handford et al., 1997). When designing practices for learning, it is essential that coaches manipulate the system to be poised at the critical point, on the edge of chaos (Bowes & Jones, 2006). Knowledge of ‘critical values’ (i.e. the amount of variability that will lead to instability and the search for new solutions) is important for coaches and requires careful management and awareness of the implications for placing individuals in these critical zones (see Chapter 6). This tipping point on the edge of chaos is often the location of the optimum instability for the performer(s) (we describe this as the amber zone in the next chapter). On the other hand, sometimes it is advantageous for a coach to design-in a low amount of variability, as he or she may wish to design practice tasks that do not promote any additional pattern forming or system re-organisation (we describe this as the green zone in the next chapter). In contrast, there will be a ‘critical value’ above which the environment will contain too much variability and as a result will become inherently chaotic and unmanageable (we present this as the red zone in the next chapter) (Davids, 2003). The manipulation of task constraints such as the lane in which a swimmer must race, the score and time left in a combat fight or the number of learners, size and shape of the playing area, number of objects, and equipment scaling in a team sport, will all have significant impact on the amount of information to which performers are required to attend. For example, if a novice performer is placed into a practice environment with a large number of opponents and teammates with a multitude of performance solutions, the environment could become too difficult to perceive and act upon. For some performers, this type of practice task design could contain information overload. In this case, the manipulation of task constraints (e.g. a reduction in the number of opponents and teammates), to reduce the amount of variability, has the potential for better engagement and development of the performers, at a specific stage of learning and development. In summary, individual performers need to be provided with practice task constraints that allow them to explore dexterity in their interactions with the performance environment. The affordances explored during learning need to be well-considered and fit completely with the effectivities of the performers in the group. Essential to this process is the appropriate provision of variability and (in)stability in the practice environment.
The generation of functionally variable movement patterns is an important characteristic of skilled performers operating within a dynamic environment. The importance of this variability was emphasised in Chapter 2 where we introduced the concepts of ‘dexterity’ and ‘degeneracy’ (Bernstein, 1967, p. 228). We propose designing-in the appropriate level of variability to the practice environment will align the practice environment with the repetition without repetition principle, thus facilitating the development of performers with a greater ability to organising their body in many different ways to solve any emerging motor problem correctly, quickly, rationally and resourcefully. As a result, a coach must manipulate task constraints in practice environments to offer both repetition and variation (i.e. repetition without repetition) to facilitate this process (Travassos et al., 2012).
Summary
In summary, the Environment Design Principles (EDP) provide a framework to guide coaches as they navigate the complex and nuanced process of practice design. The four distinct principles provide coaches with the tools required to bridge the gap between the theoretical underpinning and the successful application of a CLA. Coaches should endeavour to meet the four guiding principles by attending to the following elements throughout the design, adaptation and delivery of their practice environments:
1 Session intention
• Employ a clearly established session intention as an organisational constraint as you design your session.
• Ensure that session intention is aligned with the intentions of your performers.
• Consider the timing of your session alongside the needs of the performers when establishing the session intention.
2 Constrain to afford
• View yourself as a ‘problem setter’ who designs practice sessions to facilitate implicit skill development.
• Manipulate constraints to design-in specific affordances for performers to engage with in your practice landscape.
• Avoid ‘over constraining’ to force and instead aim to invite engagement with specific affordances through a process of exaggeration.
3 Representative learning design
• To maximise the potential for learning transfer ensure you consider the impact of representative design.
• Use task simplification rather than task decomposition to ensure higher levels of RLD.
• Design-in RLD to your practice environment by ensuring that perception–action remain coupled.
• Ensure you have considered amplitude of ALD in the design of your practice environment.
4 Repetition without repetition
• Encourage the development of dexterity by ensuring with repetition without repetition rather than repetition after repetition is evident in the practice environment.
• Determine the appropriate amount of variability to match the current abilities of the performers.
• Decide if the variability is to be systematically or randomly designed-in to your practice environment.
• Deliberately design-in a period of (in)stability for your performers by adjusting the amount of variability within your practice environment.
The following chapter (6) provides coaches with a stage-like model, scaffolding the coach through the process of designing and adjusting their practice environments, supporting the application of these complex ideas into their practice.