A Pragmatic Approach to Skill Acquisition for Physical Education: Considering Cognitive and Ecological Dynamics Perspectives

ABSTRACT

Learning theories provide philosophically informed, basic principles for understanding the mechanisms through which people learn based on a combination of field or laboratory studies. Unfortunately, however, there are several clear conflicts between theoretical approaches and common methods in teaching. Consequently, key challenges among teachers relate to knowing which theoretical approach to adopt and, therefore, methods to apply. This contradiction is even more confusing since some arguments from each approach are coherent with current practice, whilst others are either inconsistent, unclear or even counter to established teaching views. In short, the implications for teachers are, at best, suboptimal. Accordingly, this paper aims to explore the differences in theoretical perspectives and thence, to propose that there is a need for multiple approaches, possibly used in combination. We hope to offer clearer guidance for practitioners and provide some direction to promote better application from researchers.

KEYWORDS:

• Motor learning
• pedagogy
• predictive processing
• professional judgment and decision making
• teaching

A challenge facing physical education (PE) teachers when introducing new skills is to decide on the most appropriate pedagogical approach (Mosston & Ashworth, 1990). Abundant evidence shows that differences in the way skills are taught makes a significant difference to learners’ development of movement competence (e.g., Emmanouel et al., 1992). Unfortunately, however, scientific literature offers several conflicting theoretical perspectives that could underpin such pedagogy, making the planning and design of sessions more taxing and confusing when working within the evidence-based professional framework that teachers are expected to employ (Raiola & DiDomenico, 2021). As such, the purpose of this paper is to explore these different underpinnings and the implications of pedagogical approaches to teaching new skills in the PE context. In doing so, research relevant to both motor learning and the teaching of movements is presented and contextualized within a PE setting.

Within the scientific literature, there have been significant but multiple developments concerning the mechanisms governing motor learning, represented by different theoretical perspectives. In meeting the paper’s purpose, the following objectives are addressed: (1) to outline the predominant theoretical perspectives within the literature, (2) to explain their implications for professional PE practice through exemplar differences in teaching styles and interpretation of how “understanding” might contribute to motor learning and, finally, (3) to consider a new, “predictive processing” perspective in conjunction with the Professional Judgement and Decision-Making approach, as a possible solution that offers a combination approach for motor learning.

Contrasting theoretical perspectives

A cognitive perspective towards learning

Over past decades, and forming the predominant perspective within the field, motor control literature has focused on learning from an indirect perception approach known more broadly as an “information-processing,” or cognitive, perspective (e.g., see Frank et al., 2021). This approach suggests that, at a cerebral level, humans require a structure to interpret, or add meaning to, information before it becomes useable for action: this structure, used to formulate and execute action, has been termed a “motor program.” Cognitive-based theories propose models of information processing that are hierarchically structured and functional in their characterization, through the following features: connectivity, differentiation, integration, organization, quantity, quality, and relative automaticity. Hence, overt behavior is considered as deliberately performed through intentional and planned actions toward a goal.

Furthermore, cognitive theories attribute great importance to knowledge and how it is used (e.g., attention, rehearsal, understanding, memory, and information analysis). These strategies for using knowledge incorporate many factors, including problem-solving skills, memory retention techniques, thinking and meta skills, and the interpretation of presented information (Schmidt et al., 2019). Consequently, and at a much deeper level, increasing a learner’s awareness of acquired knowledge and how to obtain it enhances the quality of learning (Dail & Christina, 2004); in other words, learners benefit from learning how to learn. In turn, activity, experience, and training causes a change in the learner’s perception toward the task and subsequent behavior. Cognitive theorists argue that knowledge underpins this change and is not only a procedural representation of how to do a movement but also includes declarative knowledge of what moves to do and why (Kump et al., 2015). These components of knowledge, when developed in combination with physical training, are explained to help promote positive long-term motor skill development outcomes such a transfer in ability from one context into another (Magill & Anderson, 2021); for example, whole body agility in PE within the game “tag” may positively transfer these movements when later playing rugby.

Considering the importance of interpretation, cognitive approaches are grounded in constructivism, which views learning as the process of constructing new realities through experience as an individual and/or shared amongst others within a particular setting and/or culture (i.e., social constructivism; Sjøberg, 2010). Importantly, learners develop personally meaningful knowledge based on their prior experience of the skill and social norms/expectations/familiarity (Poolton et al., 2007). Subsequently, these constructions are used to inform the utility of new task information, motor control, and practice behavior; the latter through mental training approaches such as imagery (Holmes & Collins, 2001). Beyond the initial experience of performing a motor task, movements are planned and updated using an internalized processing system (Schack & Mechsner, 2006), representing the development of a motor solution with greater organization, clarity and detail. These structures then support and integrate key motor programming functions, such as making decisions and anticipating the likely outcome of motor activity. Consequently, feedback to learners is interpreted using previous experience, knowledge, thoughts, and feelings (Sutton, 2013).

Several teaching methods are used to enhance the learning experience based on the information-processing functions and demands outlined above. One fundamental exemplar is to adjust practice difficulty; therefore, enabling the learner to engage in a process of understanding their movement and associated impact on the outcome (i.e., transition from the verbal cognitive to associative stage of learning; Fitts & Posner, 1967). Notably, this requires a careful balance between promoting successful executions that help to construct an effective representation within long-term memory, but also making some performance errors in practice to encourage retrieval attempts from long-term memory, thereby preventing boredom from setting in and a lack of learning due to overly monotonous repetitions (e.g., Guadagnoli & Lee, 2004). Equally important, however, is to prevent too many errors from occurring, which can cause frustration, disengagement, confusion, and an ineffective representation being developed. Making the movement more manageable by employing part-practice is one such method, especially if the task is complex and the learner cannot clearly process important task-relevant information (Merbah & Meulemans, 2011). Practice scheduling is another method that involves changing the order sequence of to-be-learned skills that puts varying degrees of pressure on the learner to remember what they need to do by drawing on previous experiences (Wulf & Schmidt, 1988). Finally, the use of multiple sources of feedback typify the application of this approach. Understanding the execution process through intrinsic feedback mechanisms (e.g., how the movement felt) is considered a meaningful way of encoding movements for later retrieval from memory. When combined with extrinsic feedback pertaining to the outcome, or several different outcomes, this helps to strengthen the learner’s understanding of why the movement was or was not effective (Oppici et al., 2021). In combining these two sources of feedback, teachers might use questioning methods to encourage learners to notice the difference between successful and unsuccessful executions. Therefore, from this perspective teachers need to consider not only what they can do to change the movement, but also what they can do to address what and how the learner thinks about the movement.

Research supporting the cognitive approach recommends that teachers include within their planning how they will explain the task, the sequence and timing of movements, and then the targeted result of the task (e.g., Metzler, 2017). It is important that when the teacher plans the lesson, they consider the difficulty and requirements of the skill, the rate of learning needed, and the learning abilities of the students (Raiola & DiDomenico, 2021). While the student is practicing, the teacher needs to monitor and verify the progress of the learner and adjust the difficulty accordingly. If the learner needs a fast performance improvement (e.g., for motivational reasons) then the challenge can be made easier, but if the goal is for long-term retention and better transfer to different contexts (e.g., from PE into sports) then the active problem-solving nature and understanding of the task can be emphasized through slower, more complex and challenging training scenarios. In this way, the teacher must engage within a teaching and learning environment, which increases their cognitive load and need to rationalize “why” they are doing what they are doing. Therefore, this perspective emphasizes the importance of a hands-on approach from the teacher.

An ecological dynamics perspective toward learning

A more recent ecological dynamics perspective toward learning has centered on the relationship between a learner and their environment through direct perception processes (Button et al., 2021; Davids et al., 2021). The primary influence of the approach stems from the idea of behavioral functionality and adaptability, as opposed to technical desirability and cognitive processes, within a dynamic and interactive set of conditions (Biesta & Tedder, 2007). Instead of relying on centralized control mechanisms, such as memory or a representation, movement is explained to continuously emerge as a softly assembled co-ordination pattern, resulting from the ongoing and direct exchange of information between the environment, learner, and task dynamics (Newell, 1986). Consequently, understanding movement and its development in context is essential for facilitating effective motor solutions by teachers and their practice by learners.

The origin of the ecological dynamics approach stems from early research into dynamical systems theory (Haken et al., 1985) and is an interdisciplinary combination of multiple theories within the physical and psychological sciences (Summers, 1998), namely, complexity theories, co-ordination dynamics, and ecological psychology concerning direct perception (Bernstein, 1967; Chow et al., 2007; Gibson, 1966, 1977; Heft, 1989; Whitehead, 1981). Indeed, many characteristics of the movement system can be reflected in properties observed within natural and organic systems. These ideas have been brought together to suggest that the continual exchange of information promotes the self-organization of movement patterns through the interaction with key external properties within the environment and/or task requirements. When an interaction is available, the ecological dynamics perspective suggests that an affordance (i.e., an opportunity for action offered by the environment and relative to individual abilities; Gibson, 1979) is present and new movement possibilities can arise. Self-organized movements emerge in this context through a direct coupling between what the learner externally perceives and their actions, a phenomenon known as perception–action coupling. Therefore, learning is characterized by a more attuned perceptual process to other interacting systems within the environment and/or that are relevant to the task, rather than the storage of movement information at a higher-order, cognitive, level of planning.

From an ecological dynamics perspective, teachers should view learning through the observed behaviors of children that can be monitored objectively, be lawfully and systematically described (Lee et al., 2014). As a student becomes more perceptually attuned to their environment, sensitivity for, and ability to “pick up,” information becomes more effective in the process of formulating multiple movement solutions (Cater, 2022). Resulting from the complex fluctuation of environmental and task demands, these affordances need to be understood in a functionally meaningful and context-specific way. Affordances refer to the opportunities and invitations for action that the environment or task provides, considering the relational qualities with an individual’s capabilities and intentions (Gibson, 1979). For example, a tennis player may become more perceptually attuned to changes in wind conditions that may shape changes in the way they impart spin on the ball to execute their shot within a specific game. More generally, as a performer becomes more skilled, they are better able to exploit external (e.g., ground surface conditions, equipment properties, opponent positions etc.) and internal (e.g., muscular strength, stamina, flexibility, height, weight etc.) constraints to search for and utilize affordance-rich sources that inform functionally variable motor solutions (Renshaw & Chow, 2019), whereby every movement is unique. In the initial stage, however, a learner is described as locking, or “freezing,” their degrees of freedom (e.g., joints) in order to create a motor solution because they have not yet attuned to the relevant task or environmental variables and must “search” for specifying (i.e., important and structural) information related to the task. Following practice, the degrees of freedom are gradually released, or “freed,” to form more efficient co-ordination patterns as specifying information is “discovered and stabilized.” Finally, degrees of freedom and environmental information are “exploited,” as explained in the example above (Bernstein, 1967; Button et al., 2021), and these changes are notably observable in context. Accordingly, due to the innumerate and ongoing information exchanges between the learner and the environment within sport and physical activity settings, PE teachers should actively progress motor skill development by introducing numerous movement solutions and creating many opportunities (i.e., affordances) for students to explore.

In this respect, there has been growing research interest in how practice can be altered using ecological dynamics concepts within PE settings (Rudd et al., 2021). Accordingly, the teachers’ role is to co-design activities with learners, rather than provide direct instruction on how to perform a movement. In doing so, the responsibility is placed on the learner to observe different interactions between the task and environmental features (Rudd et al., 2021). Specifically, affordances should not be directly specified in this process, but the teacher should assist the learner in their perceptual search for them. By facilitating a representative practice design, relative to a real-world situation, the teacher promotes the possibility of relevant perception–action couplings (Pinder et al., 2011). In this way, the pedagogical style is less teacher- and more student-centered; the role of the teacher is to assist rather than prescribe how to perform each skill individually and to provide practices that mimic how the sport is played rather than breaking down the skill components (Ellmer et al., 2020).

For the PE teacher, the mechanistic underpinnings mean that effective training involves designing activities that actively represent the competitive, or eventual, environment that meet not only the physical but also perceptual demands. Quality practice in this sense requires exposure to key information sources that enable the individual to become more attuned to picking up important environmental or task properties that affords more functionally variable movement outcomes (Withagen et al., 2012). Task simplification is one form of practice where if the task is excessively complicated, additional constraints should be applied within the environment that direct the learner to explore different solutions rather than prescribing how to make the motor execution simpler (Renshaw & Chow, 2019). Therefore, the task is merely simplified by altering the size of the pitch, size of the ball and the height of nets, for instance, which helps reduce the task difficulty and involvement of degrees of freedom that can then be progressively developed within representative game contexts (Buszard et al., 2014; Tan et al., 2012). Reflecting these ideas, the teacher has a more “humble” or hands-off role in assisting the learner to independently search for solutions whilst ensuring safety.

A core principle? The role of understanding

When learning a new skill, the extent and nature of understanding appears to be an important contradiction between the two theoretical perspectives. From a cognitive perspective, understanding and developing a stored representation in long-term memory of the skill and the movement consequences is essential to facilitate motor learning. Research has found, however, that the preferred understanding modalities of children can vary; that is, while some children like to learn and understand through visual information processing, others like to learn and understand by hearing, and others through a combination approach (e.g., Charlesworth, 2016). Although the categorization of and rigorous empirical support for different learning styles has been challenged (e.g., An & Carr, 2017; Pashler et al., 2008), there seems little doubt from the cognitive literature that children benefit from having a diverse means of understanding during their development (Murphy & Chroinin, 2011).

In contrast to the centralized role of understanding within the cognitive perspective, it seems that understanding, or at least the ability to verbalize this, is addressed differently and to a much lesser extent by the ecological dynamics perspective. For the ecological dynamics perspective, understanding should be developed in relation to tactical, strategic, and environmental knowledge (e.g., rules), rather than in relation to movement techniques (Chow et al., 2007). Proponents of this approach often present the case for developing knowledge of the environment as promoting richer exploration of affordances (e.g., Sullivan et al., 2021). Specifically, this refers to knowledge of available affordances to that individual as opposed to knowledge about the environment, which takes a third-person (e.g., performance analyst’s or an observer’s), symbolic manifestation, and non-situated view of the action execution. Taking a neutral or balanced view, the literature from each perspective seems to suggest that it might be how understanding is expressed that is the crucial difference, rather than whether or not it exists at all. From the cognitive perspective, this is clearly explained as a representation within memory pertaining to both declarative and procedural information (Pereira et al., 2016), whereas from the ecological dynamics perspective knowledge is more contextually situated in environmental terms and not part of a central memory system (Chow & Atencio, 2014). Notably, these two perspectives toward the role of understanding in motor learning contexts change how the PE teacher should engage with learners and implies contradictory teaching methods.

Contrasting implications

For PE teachers, these two apparently well-grounded and researched theories offer contrasting implications; the root of the confusion we alluded to earlier. In this section, we examine some exemplar and common learning tools to illuminate how the theory-to-teaching practice conceptualization would differ when utilizing the two perspectives. The first is the social learning tool. According to cognitive theory, individuals learn not only through their own experiences but also through observation of others. In the context of motor skills and movement, social learning suggests that learners can understand and represent motor patterns, strategies, and even problem-solving skills by observing and then imitating the movements of others (Bandura, 1986). From an ecological dynamics perspective, social learning can be seen as facilitating a social affordance in which observers restrict or expand their search activity. Social learning acts as a means of providing action possibilities for exploration, inviting learners to find functional performance solutions by drawing learners out of their comfort zones. By learning within a social group context, learners can perceive both affordances of others (i.e., information from another person to shape the learner’s actions) and for others (i.e., information that provides a collective resource toward team co-ordination; Silva et al., 2013). Therefore, by observing and interacting with others in their situated context, learners not only explore different movement patterns but also become attuned to different specifying information within that environment (Renshaw & Chow, 2019).

The second tool is demonstration. From the cognitive perspective, demonstrations are used to manage the cognitive load and direct attention to key technical characteristics/components. Demonstrations, a form of visual representation, reduce the cognitive load associated with interpreting verbal instructions, making it easier for learners to focus on the essential aspects of motor skills (Grunwald & Corsbie-Massay, 2006). Demonstrations, when viewed through the lens of an ecological dynamics perspective, align with the concept of affordances. They make salient the opportunities for action within a given environment. By demonstrating movements, it is possible to highlight the affordances present in a particular context for that particular learner, enabling learners to perceive and utilize these affordances to enhance their motor skills (Finney, 2022).

Questioning is a third common tool. From a cognitive perspective, by asking thought-provoking questions it is possible to stimulate learners’ critical thinking and encourage them to reflect on their own motor experiences (Ferguson et al., 2023). This process aligns with cognitive ideas about metacognition, which suggest that self-reflection and self-regulation play pivotal roles in skill development (Zimmerman & Moylan, 2009). From an ecological dynamics perspective, Correia et al. (2019) argue that questioning as a teaching tool is a means to guide learners to explore the affordance landscape. By asking questions, this can prompt learners to search for and discover new movement solutions and become more perceptually attuned to important sources of information in a way that changes the direction of the action exploration (Correia et al., 2019).

These three tools are commonly used by PE teachers to generate understanding and are henceforth the focus of this review (Goodyear et al., 2014; Vincent-Morin & Lafont, 2005). Together, these three learning tools are used regularly to reinforce messages that assist learners to maintain quality physical practice through psychological constructs such as motivation and confidence (Tremblay & Lloyd, 2010). The three learning tools also provide avenues for demonstrating how the cognitive and ecological dynamics approaches can be combined or integrated in practice regardless of their distinctiveness. We suggest that the outcome of all these tools will lead to some degree of understanding and knowledge as a common necessity across the cognitive and ecological dynamics perspectives; however, it is important to understand the mechanistic explanations offered by the current evidence-base to assess how and why each tool is suggestively working which, in turn, informs a teacher’s decision-making process. Table 1 illustrates the theoretical explanations offered from both cognitive and ecological dynamics perspectives when using the three learning tools that consequently underpin the contrasting implications.

Table 1. An illustration of the theoretical explanations (cognitive and ecological) offered for using three common teaching tools.

Learning Tool	Theoretical Perspective
	Cognitive	Ecological
Social Learning	Observation of the behavior → Interpret what is important → selection based on observation and interaction → consciously copy and replicate.	Observation of the behavior → stimulates the search for adaptive movement solution.
Demonstration	Communicating the relative movement of joints. Ideally, the demonstrator should be similar in size, shape, and skill level to the recipient, thereby maximizing relatenedness, understanding and transfer.	Early use to “shape” the search for solutions. Subsequently removed so that this search is not limited or overly directed toward a “perfect” technique.
Questioning	Plays an essential role through a directing process – strengthening the focus through building an understanding of what is (and isn’t) important. Uses closed and open questions to test understanding.	Applicable to encourage search processes within the affordance landscape. Questions do not seek to elicit definitive responses.

Social learning

According to social learning theory, the concept of modeling is used to explain observational learning, whereby people learn specific actions by observing those of others and the consequences (e.g., reward) of those behaviors socially. Observational learning processes include motivation, attention, reproduction, and retention (Locke, 1987). Motivation is required to improve one’s behavior by wanting to observe another’s behaviors. Attention is visually directed to identify and detect the behaviors to be learned when observing. Reproduction is the repetition of the observed behaviors. Retention refers to the observed behaviors being stored in the learner’s memory and retrieved later, which evidences that learning has taken place. In the early stages of learning, teachers can promote social learning processes by actively engaging children with experiences of positive behaviors, either by demonstrating themselves or directing attention toward other role models such as peers or siblings and evaluating those behaviors as beneficial (Taylor et al., 2018).

A large part of social learning comes from extrinsic motivation because of how certain behaviors are reinforced. In a PE setting, this could involve the teacher praising a child for performing a skill well and therefore making other children focus their attention on them to copy what they are doing. With practice, intrinsic motivation may increase as the level of competence improves (Deci & Ryan, 1985). Central to this learning process is the to-be-learned behavior being outside of the learner’s current capability and, therefore, providing an informationally rich visual stimulus. Unfortunately, studies incorporating these different mechanisms involved within social learning in a motor learning context are limited.

Social learning theory includes the notion that learning happens through the influence of social factors as a collective entity, with the learner, environment, and behavior interacting dynamically and reciprocally (Bandura, 1977). An example of this would be the model–learner relatedness, whereby if the model has some similar characteristics to that of the learner, such as gender or age, it will enhance their motivation to reproduce that behavior (Adriaanse & Crosswhite, 2008). Therefore, PE teachers should consider the make-up of smaller groups in classes to consider who can learn what from who.

Within the PE context there are few studies examining the direct impact of social learning on motor skill development, however the influence of social factors on motor learning can readily be inferred. Social learning (or co-operative learning as the authors phrased it) has been found to play a part in reducing the barriers to PE engagement for girls who are disengaged with PE when presented in its traditional form (Goodyear et al., 2014). Likewise, when learning motor skills, the role of modeling has a significant impact on physical activity in young children. Modeling (especially from parents/caregivers) has been found to play a significant part in promoting young childrens’ motivation and confidence to participate in physical activity as they grow older, which effectively improves preschool-aged childrens’ motor skills due to motor competence affecting long-term physical activity habits. This is likely due to parents/caregivers being the main influencers of physical activity in young children and being their role models, which leads to mutual reinforcement. Furthermore, social cognitive theory-based research shows that children can learn by watching their parents’ actions (Bandura, 1986). Overall, some of the mechanisms or features described in this section would appear to be redundant or neglected with a lack of empirical research available supporting social learning theory under both cognitive and ecological forms of learning.

Demonstration

Demonstration is a teaching strategy that uses visual information (e.g., live models, videos, posters) to convey a concept related to skill execution. Hamilton et al. (2020) argued that demonstration could streamline the process of developing and progressing learner’s procedural knowledge based on the set of observations and replications to ensure autonomy and adaptation of any particular technique. For proponents of this approach, an efficient demonstration should serve as the starting point for class discussion, promote/guide observation skills, spur thought, arouse interest, and reveal facets of intricate topics on a tangible level. It is frequently combined with verbal explanations and sometimes with tactile cues (e.g., physical manipulation). The terms demonstration and modeling are functionally identical for many learning purposes, with demonstration being the more common term and modeling being more derived from learning research.

Moreover, video feedback of the performance helps enhance skill learning because the information viewed can allow the performer to evaluate and adjust their movements in subsequent trials as it aids in their understanding of the skill. Examples of video feedback can be an expert video demonstration or feedback from the athlete performing the skill (Aiken et al., 2012). Furthermore, recent research has begun to empirically explore the mechanisms underpinning the optimum use of modeling in combination with other cognitive processes such as mental imagery. Interestingly, evidence shows that even in the absence of physical practice, motor learning can in fact occur through a combination of the mental imagery with observation of a model and that this leads to better improvements than having one of the techniques alone (see Binks et al., 2023 for a review). Accordingly, it would appear that most interest in this tool has originated from a cognitive perspective.

The concept of demonstration attracts considerable critical attention in PE, as a means whereby teachers/coaches can facilitate knowledge to the students by serving the role of explaining and reinforcing psychomotor skills, uplifting cognitive concepts, and socio-affective behaviors. From a cognitive point of view, a demonstration plays a vital role in learning. The teacher/coach asks the learner to look at a model doing a particular task or technique, and the learner picks up the relative movement of body parts and joints. Some demonstrations might result in better results depending on the similarity of some aspects between model and learner, such as size and/or technical ability. It falls in line with cognitive approaches to learning, as demonstrations allow for the teacher to give direct instructions on how to perform the skill to the learner.

Whether certain practical techniques may be exclusively explained by either ecological dynamics or information processing theories is a topic of continuous discussion in the motor learning literature (Gottwald et al., 2023). It is important to understand that practical tools can frequently be interpreted and explained by both views, albeit through distinct mechanisms, even though it may be claimed that some tools correspond more closely with one theoretical perspective than another (Gottwald et al., 2023). For instance, it is possible to see how demonstration, which is widely used in PE, can promote both ecological dynamics and cognitive viewpoints, albeit with different usage in the learning process. From an ecological dynamics perspective, observation, and observational learning aid in the exploration of the perceptual-motor landscape, intention education, and attention calibration. The use is then avoided however, so that the learner’s self-exploration is not “polluted” by the idea of a perfect model. The cognitive perspective, on the other hand, focuses on mechanisms for error detection and correction through observational learning (Gottwald et al., 2023). Demonstrations continue to be used to encourage associative links between skill elements toward an optimum model. Therefore, while considering practical tools, it is vital to recognize any potential overlap and shared explanatory power between theoretical viewpoints, but also any key differences in application. To fully comprehend the relationship between theoretical mechanisms and useful tools, the complexity of the motor learning process will be explored further by providing a practical framework intended to enhance the clarity of practical tools within the realm of the two perspectives.

Additionally, demonstration helps understand the practical differences between an ecological dynamics and a cognitive approach through the various mechanisms through which each perspective supports it. It might be stated that most PE teachers primarily rely on the cognitive approach, either consciously or accidentally, because of the popularity of demonstration in the field (Ryan et al., 2016). The intentionality in the selection of demonstration in PE has not, however, been the subject of empirical research that may draw a line between the ecological dynamics and cognitive viewpoints. The ability to distinguish between these perspectives in the context of PE is limited by this research gap. Further research is required to address this, providing insights into the alignment of demonstration in PE settings with either the ecological dynamics or cognitive perspective by examining the intentionality behind its use and its underlying mechanisms. The findings of such studies can help demystify the fact that some PE teachers are excellent in coaching, yet they lack deep theoretical insights regarding the ecological dynamics and cognitive perspectives.

Questioning

Questioning can be viewed as a microstructure in practice to help guide learners to motor task solutions. Previous research into coaching techniques found an over-emphasis on instruction, feedback and demonstrations and these methods were criticized for not enabling the athletes to develop problem-solving and decision-making skills (Williams & Hodges, 2005). These considerations led to more attention being paid to questioning as a tool for learning. It is seen as a useful characteristic in helping develop decision making and game understanding in novices. When coaches implement questioning in their training program, it will lead to better decision making and skill execution as it helps learners take responsibility for their own learning and be aware of changes in their ability (Light & Harvey, 2017). Additionally, it has also been found to create curiosity and persistence, which can ultimately boost the desire to learn as learners self-reflect and self-monitor their own learning progress (Harvey & Light, 2015). Questioning involves a teacher directing the learner’s attention toward specific actions and is carried out differently by the two approaches.

Under ecological dynamics approach, questions are used to focus attention to a source of information so the learner can adjust their behavior. As such, questions must be placed carefully as informational constraints and guide the learners toward an affordance-rich area (Chow et al., 2021). Questions are also not verbally responded to. For example, if a player in football keeps on missing the goal when shooting, the coach could ask “what can you do to have better control of the ball?” to make them search for the movement solution. Questions in this approach, are used to change the direction and define a path of exploration.

Contrasting this, in cognitively-grounded learning, questions are used by the learners to understand the task, and questioning by the coach gives a declarative solution (Correia et al., 2019). In support of this, a preliminary study conducted by Práxedes et al. (2016) found that when male football players were trained with questioning based on tactical understanding followed by discussion of the tactical concept to ensure understanding, the intervention group had better scores on passes and dribbling compared to a control group that involved no questioning. This study showed how using questioning to point out mistakes, leads to improved learning.

In summary, the ecological dynamics perspective utilizes questioning to guide attention and exploration, while the cognitive perspective uses questioning for learners to seek understanding and develop declarative solutions.

Making sense of the differences in perspectives

In view of the cognitive and ecological dynamics perspectives, it seems that neither can effectively capture the entirety of the PE experience to enable teachers to design optimal teaching and learning environments. Indeed, within a profession whereby teachers are required to critically reflect on their practice and make evidence-informed decisions, this dichotomous view of motor learning is not helpful when seeking to design and/or improve lesson plans. This is especially so when it is clear that both perspectives contain elements that are applicable. One way in which this conundrum may be reconciled is by recognizing and allowing for the “conditionality” of knowledge within specific contexts. What this means is that there could be scope for both mechanistic perspectives to be utilized at different times, but that this would depend on a number of factors to inform why the teacher should adopt one pedagogic approach and not another. This approach to employing evidence-informed teaching is important, because it shifts the current focus within motor learning literature from an “either/or” debate regarding how best to explain motor learning, to one that begins with the challenges faced within the PE context. Accordingly, exploring a different, more contemporary, theoretical perspective to those of cognitive and ecological dynamics is worthy of presentation.

The predictive processing perspective: A possible mechanistic solution

The predictive processing (PP) perspective has its roots within basic motor learning principles and uses a Bayesian concept to explain how the body utilizes internal and external information. A key concept of PP is that the brain generates a set of “most likely” expectations, or predictions, of an upcoming experience (e.g., a tennis rally or when bowling a ball) based on information available (Friston, 2010). Specifically, the expectations are generated by combining an individual’s internal representations of the world, which are developed through prior experience and understanding, with real-time contextual information. In doing so, a hierarchal model is created that prioritizes, or allocates a weighting to, specific factors of importance based on the information at that current time and the athlete’s intention. Performance is most likely to be successful when the performer has effectively modeled the demands of the task with their ability to act. Conversely, inappropriately anticipating the relevant factors, or their respective importance, may lead to a suboptimal action being taken to meet the task demands (Clark, 2013). As such, the PP approach is inclusive of the need to cognitively represent the situation and the ecological dynamics perspective that environmental information can inform motor strategies.

Consistent with this dual approach, hierarchical models do not always remain fixed within a performance. Following preparation to perform, the generated model does not require any revisions so long as the most likely expectation is met during the task; that is, no additional computational processing is required to complete the skill. However, when the performance expectations are incongruent with the external reality and performance is suboptimal, the model must reconfigure in order to create a new set of expectations that drives a change in the performer’s behavior (Wolpert et al., 2003). Indeed, such discrepancies may result from internal (e.g., fatigue) and/or external (e.g., change in competitor strategy) sources and require the acute perception of information to bring about a model’s change in the types of factors and/or their weighting of importance. In other words, when performance expectations are being met there is low demand on internal resources and the execution is more efficient, but when performance expectations need revising there is a high demand on internal resources and the execution is less efficient. In this way, direct perception processes might be more prevalent in the former and indirect perception processes might be more prevalent in the latter.

With this more dynamic view of perception and motor representation comes some important implications within the motor learning context. Firstly, in order to adapt performance expectations performers must be proficient in switching between more direct and indirect perceptual states (see Bortoli et al., 2012). This means that performers must be able to recognize that a prediction error has occurred through evaluation of goal-relevant contextual information. Secondly, performers must be able to reconstruct effective new strategies by combining environmental information with technical knowledge in a way that promotes subsequent success. This means that the performer should understand the fundamentals of technique if they are to avoid thinking about irrelevant and/or too many factors that slows down/negatively disrupts the adaptive process. Such learning involves a process of creating richer and more functionally adaptive models to predict task demands, applying knowledge both of and for the environment (Friston, 2010; Henderson, 2016).

Within sport there is evidence to show that performers rely on both sources of information to learn and regulate their movements. For example, Beilock and Carr (2001) found that expert golfers possessed a higher amount of generic technical knowledge in golf putting compared to novices, but relied much less so on it when compared to novices during the golf putt execution. When experts were given a novel “funny putter” they were found to increase their reliance on procedural knowledge than the novices or their expert counterparts with the normal golf putter. This shows that expert performers can focus on environmental stimuli without having to cognitively plan when they are performing a skill they know. However, when the task constraints change, experts rely on relevant cognitive sources of information, using previous experiences to more effectively update their predictive model. Therefore, depending on task demands, experts can differentially utilize environmental and/or movement-specific knowledge to regulate planning and execution processes.

Likewise, in a study comparing their ability to predict the direction and force of a squash stroke, the experts outperformed the novices showing that as skill level progresses, experts become more selective and accurate in picking up on the information-rich areas and place their attention accordingly (Abernethy et al., 2001). In a learning context, this would require novices to learn to decode a complex visual environment and learn where to focus their attention, interact their short-term with their long-term memory, and make their decision into a kinematic action with the ability to modify it in real-time, and only then can expertise be developed (Lola & Tzetzis, 2021). Further considering how the PE teacher might conceptualize these processes within the teaching and learning context may assist in removing any confusion arisen from a previously dichotomous view of motor learning and improve decision-making skill.

Professional judgement and decision making: A possible complimentary way forward

In acknowledging the need for a practical framework within PE, the Professional Judgement and Decision Making (PJDM) approach offers such from the sport psychology and coaching domains (Abraham & Collins, 2011; Martindale & Collins, 2012). Specifically, PJDM does not propose a dichotomous view of theoretical relevance (i.e., one perspective is more correct than another), but rather provides a nuanced and comprehensive framework that supports teachers using a variety of approaches through a specific emphasis on decision making (Mosston & Ashworth, 1990). Therefore, PJDM serves as a practical way forward by integrating different perspectives based on their appropriateness and promoting evidence-informed decision-making in motor skill acquisition (Collins et al., 2022).

Notably, in other domains such as sports coaching, the PJDM approach is receiving increasing academic attention as our understanding of performance, pathways, and their environments becomes more complex (see Collins et al., 2022). It can be defined as “the method that blends components to deliver a bespoke solution to the particular issues of the teaching setting, developed through a nested decision-making process” (Collins & Collins, 2016, p. 1231). According to research, making decisions and exercising judgment is critical for efficient performance in a variety of professions, and is intrinsically linked within the process of teaching (e.g., Vickers et al., 2004). As PP approaches have demonstrated, however, the style of motor control may vary for different learners and at different times, so a pragmatic approach is required when making decisions in practice, which is supported by employing the PJDM framework.

PJDM indicates the effective use and application of knowledge, skills, expertise, and experience in such a manner that the teacher is informed by the professional standards, knowledge, ethical standards, principles, and values for deciding on the approach which best fits the needs and aspirations of the learner (Martindale & Collins, 2005). However, it is worth considering the extent to which practitioners need to understand the theoretical mechanisms of skill learning to be effective. While a deep understanding of theoretical perspectives such as information-processing and ecological dynamics may not be essential for every PE teacher to deliver effective sessions (Gottwald et al., 2023), it is critical for practitioners to have a rationale underpinning their teaching decisions, such as practice structure, instructions, and feedback; in other words, reflecting ontological and epistemological compatibility. This rationale can be informed by both experiential knowledge and theoretical perspectives, such as those proposed by Mosston and Ashworth (1990) in their Spectrum of Teaching Styles. Notably, challenges occur when teachers cannot justify why they are using a particular approach or when the evidence is inconsistent. As one example, the idea of symbolic internal representations is supported by Bernstein (1967) but questioned and/or ignored by many ecological authors (e.g., Renshaw et al., 2016; Seifert et al., 2017). Therefore, PJDM provides a framework that supports practitioners in making evidence-informed decisions by integrating various viewpoints, including the practical implications from ecological dynamics and the cognitive perspectives, and considering the unique context of motor skill acquisition in PE.

In summary, while there has been discussion and dispute over the ecological dynamics and cognitive perspectives, PJDM provides a framework that is not theoretically aligned and, therefore, enables practitioners and researchers to generate better solutions for a variety of learner contexts, needs, and situational demands (Abraham & Collins, 2011). PJDM promotes evidence-informed decision-making and encourages professionals to consider the professional standards, knowledge, ethical standards, principles, and values pertinent to motor skill acquisition in PE by offering a method that combines components to deliver customized solutions within the teaching context (Martindale & Collins, 2005). By combining various viewpoints and giving practitioners a thorough decision-making framework, PJDM attempts to provide clarity and a workable path forward rather than fostering confusion through conflicting motor control explanations (Collins & Collins, 2016).

Next steps … so, what do we need in the PE literature?

Efficient practitioners rely on studies and theories as guidelines for optimal practices. These perspectives clearly offer differing and unclear advice to coaches and teachers. Furthermore, the use of learning tools receives different support and attention from theoretical perspectives. Consequently, there is a need for research to explore applications as an endpoint. Parsimonious models are simple models with great explanatory predictive power. According to the parsimony principle, scientists should pick the hypothesis that best fits the evidence out of those that also match it. So, choosing a hypothesis is influenced by more factors than just how well the facts fit the theory.

To be effective, PJDM needs theory-based research to consider the outcomes for learners as a primary goal. This as opposed to staying within the perhaps artificial boundaries imposed (indeed, often researcher imposed) by the theoretical stance. In a similar fashion to the Styles Spectrum by Mosston and Ashworth (1990), outcomes may be thought of as a continuum rather than either-or. Thus, for example and as suggested earlier, cognitive approaches may be more applicable for novices or younger learners whilst older/more experienced can benefit from an ecologically-based discovery processes. The only alternative is to demonstrate that one theory and/or tools and its implications are more effective than the other through fair comparison. Studies that claim to achieve this have often been either environmentally limited, such as through the use of lab-based tasks (e.g., Johnston & Morrison, 2016), by using closed skills (Williams et al., 2003) or imbalanced research. For instance, implicit and explicit learning from a cognitive perspective has been investigated in a very unbalanced and biased way to favor implicit learning (e.g., Bobrownicki et al., 2022).

More recently, some attempts have been made to compare and contrast the different approaches. For example, both Gray (2020) in baseball hitting and Orangi et al. (2021) examining creative action in soccer players, have demonstrated advantages of ecological dynamics-based learning approaches. These types of studies are essential, and our own work is designed to support this, although with a wider variety of skills and, more importantly for teachers, across age and stage. For the moment, however, it is worth stressing that in both these cases, the tool chosen (tested) was the one most suited to the job and would, therefore, reflect a good decision in practice. Baseball players acquired a better sense of when to hit (a perceptual challenge) whilst the soccer players were encouraged to be more creative by methods that encouraged a wider variety of responses. In short, we see these studies as further examples for PJDM (design learning to get what you want) rather than a demonstrated consistent superiority of one approach (ecological dynamics) over another (cognitive). For other tasks, with different purposes (as explained above), it may be more appropriate to adopt a cognitive perspective. Once again, the spectrum concept suggested by Mosston and Ashworth seems pertinent.

Additionally, the application of PP approaches in PE should be expanded in the literature. PP provides a mechanistic account of how the brain combines cognitive representations with real-time environmental information to generate predictions and guide motor behavior. Therefore, it offers a framework for practically integrating elements from both perspectives of motor skill learning (ecological dynamics and cognitive). There is a need to advance research on PP approaches to determine the specific practical ways in which they can help in enhancing motor skill acquisition but also in integrating cognitive and ecological perspectives. In summary, if motor learning researchers are to serve their purpose, better consideration for end users is needed.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.