The role of elite coaches’ expertise in identifying key constraints on long jump performance: how practice task designs can enhance athlete self-regulation in competition

TL;DR: In this paper, the experiential knowledge of six elite long jump coaches was investigated using a constructivist grounded theory approach, with the aim of furthering their understanding of the competitive behaviours of elite longjump athletes and how they adapt actions to the emotional and physical demands of performance environments.

Abstract: Understanding performance behaviours provides useful information for practitioners that can assist with the design of tasks to enhance the specificity of practice. In this study, the experiential knowledge of six elite long jump coaches was investigated using a constructivist grounded theory approach, with the aim of furthering our understanding of the competitive behaviours of elite long jump athletes and how they adapt actions to the emotional and physical demands of performance environments. Findings offer a coaches’ perspective on three performance contexts which shape athlete performance – perform, respond and manage – towards two common performance intentions (maximum jump and sub-maximal jump). We contend that these findings reflect how coaches perceive performance as a series of connected events (jumps), during which athlete intentionality facilitates self-regulatory strategies in the face of unique interactions between individual, task and environmental constraints across a competition. These findings highlight how individuals must continually co-adapt with constraints in performance environments supporting how athletes self-regulate using intentionality, emotions and cognitions. Practice task designs should, therefore, provide greater opportunities for athletes to learn to self-regulate in performance contexts, with opportunities to perform, respond and manage. Interpreting the coaches’ insights, we suggest that these major performance contexts of perform, respond and manage could, therefore, be strategically used to frame representative learning designs, providing a framework for better organisation of training tasks.

Summary

Introduction

• This document is the author deposited version.
• You are advised to consult the publisher's version if you wish to cite from it.
• The role of elite coaches’ expertise in identifying key constraints on long jump performance: how practice task designs can enhance athlete self-regulation in competition.

A constructivist grounded theory views methods and analysis ‘as flexible,

• Heuristic strategies rather than as formulaic procedures’ (Charmaz 2003, 251).
• In summary, regardless of what goal or strategy (maximal or sub-maximal jump) the coach wishes his athlete to execute, there are certain time points in the competition that present as an opportunity for the athlete to ‘perform’.
• The context in which a performance takes places dynamically changes in a competition setting and, therefore, an athlete must adapt intentions and actions to meet these demands.

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Full text

The role of elite coaches’ expertise in identifying key
constraints on long jump performance: how practice task
designs can enhance athlete self-regulation in competition
MCCOSKER, C, RENSHAW, I, RUSSELL, S, POLMAN, R and DAVIDS, Keith
<http://orcid.org/0000-0003-1398-6123>
Available from Sheffield Hallam University Research Archive (SHURA) at:
http://shura.shu.ac.uk/25570/
This document is the author deposited version. You are advised to consult the
publisher's version if you wish to cite from it.
Published version
MCCOSKER, C, RENSHAW, I, RUSSELL, S, POLMAN, R and DAVIDS, Keith
(2019). The role of elite coaches’ expertise in identifying key constraints on long
jump performance: how practice task designs can enhance athlete self-regulation in
competition. Qualitative Research in Sport, Exercise and Health, 1-17.
Copyright and re-use policy
See http://shura.shu.ac.uk/information.html
Sheffield Hallam University Research Archive
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Chris McCosker, Ian Renshaw, Scott Russell, Remco Polman & Keith Davids (2019) The role
of elite coaches’ expertise in identifying key constraints on long jump performance: how
practice task designs can enhance athlete self-regulation in competition, Qualitative
Research in Sport, Exercise and Health, DOI: 10.1080/2159676X.2019.1687582

Abstract
Understanding performance behaviours provides useful information for practitioners
that can assist with the design of tasks to enhance specificity of practice. In this
study, the experiential knowledge of six elite long jump coaches was investigated
using a constructivist grounded theory approach, with the aim of furthering our
understanding of the competitive behaviours of elite long jump athletes and how they
adapt actions to the emotional and physical demands of performance environments.
Findings offer a coaches’ perspective on three performance contexts which shape
athlete performance – perform, respond and manage– toward two common
performance intentions (maximum jump and sub-maximal jump). We contend that
these findings reflect how coaches perceive performance as a series of connected
events (jumps), during which athlete intentionality facilitates self-regulatory
strategies in the face of unique interactions between individual, task and
environmental constraints across a competition. These findings highlight how
individuals must continually co-adapt with constraints in performance environments
supporting how athletes self-regulate using intentionality, emotions and cognitions.
Practice task designs should, therefore, provide greater opportunities for athletes to
learn to self-regulate in performance contexts, with opportunities to perform, manage
and respond. Interpreting the coaches’ insights, we suggest that these major
performance contexts of perform, respond and manage could, therefore, be
strategically used to frame representative learning designs, providing a framework
for better organisation of training tasks.
Keywords: Experiential knowledge, elite coaches, long jump, representative learning
design, ecological dynamics, interacting constraints, grounded theory, affective
learning design

The role of elite coaches’ expertise in identifying key constraints on long jump
performance: How practice task designs can enhance athlete self-regulation in
competition
Understanding movement behaviours in sport is critical to improving
performance, due to effective and efficient use of practice time and reducing injury
risk. This understanding has largely been driven by the creation of deterministic
models: a paradigm that aims to provide a normative model of a putative 'idealised
performance behaviour' of the athlete (Chow and Knudson 2011). For example, in
long jump, deterministic models have revealed that distance jumped is the product of
height, speed and angle of take-off, as well as the influence of air resistance (Hay,
Miller, and Canterna 1986). Whilst this knowledge has played a prominent role in
shaping performance understanding (e.g., Hay, Miller, and Canterna 1986; Leigh et
al. 2008), underpinning coaches' practical applications through ‘passed-down craft
knowledge of sports techniques’ (Chow and Knudson 2011, p. 229), it fails to
provide understanding on individualised performance solutions in competition
environments (Glazier and Davids 2009). This is critical as recent investigations into
the competitive behaviours of elite long jumpers revealed that performance is shaped
by interactions between individuals (e.g., athlete intentionality), performance
environments (e.g., strength and direction of wind) and tasks (e.g., rules of the sport)
(McCosker et al. 2019). Importantly, this research highlighted that coaches need to
go beyond solely addressing technical performance and prepare athletes to self-
regulate during competition, adjusting to the specific constraints of a performance
environment.

Given these nuanced complexities needed in understanding sport
performance, an emerging body of work underpinned by the theoretical framework
of ecological dynamics (ED) has begun to examine the regulation of actions in
performance settings (Araújo, Davids, and Hristovski 2006; Vilar et al. 2012;
McCosker et al. 2019). An ED approach promotes movement as facilitating the
exploration and utilisation of affordances (opportunities for action available in a
performance environment), continuously shaped by the continuous interaction of
individual, environmental and task constraints acting on the (athlete-environment)
system (Araújo, Davids, and Hristovski 2006; Araújo, Davids, and Passos 2007;
Gibson 1979). This process of self-organisation underpins the emergence of
functional coordination patterns during goal directed behaviour (Newell 1986;
Davids, Button, and Bennett 2008). Adopting an ED approach allows practitioners to
move beyond the reductionist approach of seeking to describe which performance
parameters are important and provide a holistic approach to understanding how
movement co-ordination patterns emerge under competition settings. This supports a
more nuanced, contextualised understanding of movement performance behaviours
central to enhancing fidelity of practice conditions, where decisions and actions
should simulate those found in competition (Pinder et al. 2011).
In the study of long jumping, most empirical research has focussed on the
run-up, demonstrating that athletes regulate their step lengths using continuous
perception-action coupling (athlete perceptions and movements co-adapt
continuously). Run-up performance is shaped by the key constraints of athlete
intentionality (individual constraint), wind strength and direction (important
environmental constraints) and the rules of the sport (task constraint) (e.g.,
McCosker et al. 2019; Bradshaw and Sparrow 2000; de Mestre 1991; Lee, Lishman,

Frequently asked questions

Q1. What are the contributions mentioned in the paper "The role of elite coaches’ expertise in identifying key constraints on long jump performance: how practice task designs can enhance athlete self-regulation in competition" ?

In this study, the experiential knowledge of six elite long jump coaches was investigated using a constructivist grounded theory approach, with the aim of furthering their understanding of the competitive behaviours of elite long jump athletes and how they adapt actions to the emotional and physical demands of performance environments. The authors contend that these findings reflect how coaches perceive performance as a series of connected events ( jumps ), during which athlete intentionality facilitates self-regulatory strategies in the face of unique interactions between individual, task and environmental constraints across a competition. Interpreting the coaches ’ insights, the authors suggest that these major performance contexts of perform, respond and manage could, therefore, be strategically used to frame representative learning designs, providing a framework for better organisation of training tasks. 

Q2. What was the process of generating action codes?

The generation of action codes within this process supported the comparison of data with data, followed by data with codes allowing for the emergence of theoretical categories (Charmaz 2006), formed by the research participants and the lead researcher. 

Q3. How does Coach Five explain the influence of a foul on performance?

(Coach Five)Whilst Coach Five explicitly mentions fouls as provoking a change in performance, a combination of the competition structure and the number of opportunities left for the athlete to achieve their performance goals, interact to influence the athlete’s ability to manage the performance situation. 

Q4. How many years of coaching experience did the elite coaches have?

All elite coaches had a minimum of 10 years coaching experience (M = 31.16, R = 11 – 53) and had attained accreditation that enabled them to coach at a national level. 

Q5. What is the role of intentionality in the design of competition environments?

Given the identified role of intentionality and associated interactions with emotions and cognitions, it is important for coaches to enable athletes to attune and calibrate their actions under varying and interacting constraints whilst attempting to meet one of the identified performance intentions. 

Q6. What are the limitations of the traditional deterministic models?

Whilst traditional deterministic models provide understanding of the mechanical details of technical performance, limitations exist in their understanding of how athletes adapt actions to the emotional and physical demands of changing competition environments. 

Q7. What is the role of elite coaches in identifying key constraints on long jump performance?

of elite coaches’ expertise in identifying key constraints on long jump performance: how practice task designs can enhance athlete self-regulation in competition, Qualitative Research in Sport, Exercise and Health, DOI: 10.1080/2159676X.2019.1687582AbstractUnderstanding performance behaviours provides useful information for practitioners that can assist with the design of tasks to enhance specificity of practice. 

Q8. What are the implications of this study for coaches?

Their findings have important implications for coaches in the design ofpractice environments where movements and decisions of athletes should be more representative of those found in competition. 

Q9. What format was used to encourage unanticipated statements and stories to emerge?

Interviews followed a semistructured format (duration, M = 60 min, R = 30-87 min), utilising open-ended questions designed to encourage unanticipated statements and stories to emerge (Charmaz 2006). 

Q10. What is the meaning of the term performance intentions?

This conceptualisation of how performance intentions shape emergent behaviours across a competition provides further understanding of a conditioned coupling (in a series of connected jumps) in the performance environment and has important implications for the design of more representative training environments. 

Q11. How many of the coaches had worked with athletes who had medalled at these major championships?

four of the six coaches had worked with athletes who had medalled at these major championships at the time of the interviews. 

Q12. What were the three categories of athletes perceived to be performing in long jump?

Coaches perceived athletes achieving these goals in contexts which could be conceptually organised into three categories - perform, respond and manage. 

Q13. Why did the authors not conduct, transcribe and analyse each interview prior to the next?

Due to practical constraints on the scheduling of interviews in line with a major international track and field competition, the authors were not able to conduct, transcribe and analyse each interview prior to the next.