Developing competency in sports coaching

B

Developing competency in sports coaching

35 Coaching expertise and the quantitative examination of developmental experiences

00

36 Psychosocial training interventions to prepare youth sport coaches

00

37 Developing high performance coaching craft through work and study

00

38 Mentoring for sport coaches

00

39 Innovative approaches in coach education pedagogy

00

m36_handbook of sports Coaching_C35.indd 436

9/26/2012 9:09:10 am

35 Coaching expertise and the quantitative examination of developmental experiences Bradley W. Young university of ottawa, canada

Introduction This chapter reviews research pertaining to the long-term development of skilled coaches in the elite context of competitive sport. In particular, it appraises emerging quantitative research that has examined the types of activities and experiences that aspiring coaches should accrue in order to progressively learn and become increasingly more competent. While pointing out the many merits of extant studies, the chapter also attempts to address limitations and to outline possibilities for improved rigour in future research. The chapter advances eight themes for consideration in future work, and finishes by considering how findings from quantitative coach development research might inform aspiring individuals as well as strategies for broader coach development schemes. Efforts to enumerate the developmental path towards coaching expertise have been inf luenced by the deliberate practice (DP) framework (Ericsson 2003) and social-ecological perspectives on human development (Bronfenbrenner 2005). DP is a metric for quantitatively understanding expert development, especially in fields that have strong cognitive underpinnings like coaching. Research has yet to specifically ask what constitutes DP for coaches, however, literature that identifies activities/venues in which rigorous opportunities for coach learning occur allow us to infer DP coaching opportunities (Trudel and Gilbert 2006). In a socio-ecological model, a coach’s development of knowledge, competencies, and behavioural tendencies is a product of the social domains where they invest their time and the network of coaches, mentors, communities of practice, and athletes within which they often function and have exchange opportunities (Côté 2006).

Coaching studies using the structured retrospective protocol The DP framework requires researchers to quantify coaches’ learning histories, and the socio-ecological perspective encourages enumerating the time that developing individuals spend in coaching domains interacting with others. Borrowing protocol for collecting data 437


9/26/2012 9:09:10 am

B.W. Young

relating to phenomena in athletes’ past, Gilbert et al. (2006) refined the structured retrospective interview method for research on coach development. The survey asks participants to report information about (1) demography, education, and accreditation; (2) engagement in various coaching contexts and roles; (3) coach learning opportunities; and (4) former athletic experiences. Data are analyzed for particular developmental periods, or cumulatively across a career, and are instrumental for deriving milestones when coaches begin certain activities. The procedure is reliable and valid when objective, quantifiable, potentially verifiable data involving simple units (e.g. discrete activities) are collected. Although work is needed to validate coach-reported data using external sources, test-retest analyses on various development measures (taken 16 months apart) showed strong reliability for the past ten years of recall, with intra-class coefficients (ICC) exceeding 0.79 (Brophy and Young 2009). Coaches reliably recalled time spent interacting with athletes in months (ICC = 0.81), and weekly hours in-season (0.69), on a year by year basis, as distant as 14 years ago. Coaches reliably recalled data from 10–19 years ago for number of collegiate coaching courses, and symposia attended, former athletes now coaching, and former assistant coaches (all ICCs >0.76). Young et al. (2009) reported reliable coefficients for career-long total years of coaching (0.99) and years as a primary coach (0.98), and accumulated hours working with athletes in each sport year (0.74). Initial work indicates that recall of total years in a secondary/ assistant coach role and total number of mentors across a career is challenging for coaches whose careers extend beyond ten years. At least five studies have employed the structured retrospective method to examine coaches who are engaged in an elite context of competitive sport, and who work with athletes in the investment years of athletic participation (see Côté et al. 2007 for defining criteria for this context). First, Gilbert et al. (2006) found that successful American collegiate football and volleyball coaches spent very little time in formal coach education activities. Before coaching, these coaches spent at least 13 years playing the game at a reasonably competent level but not necessarily as a designated team leader. They specialized in a few sports during their younger playing days. Investigators determined that coaching success was related to accumulations of total coaching activity, however, they could not answer how much non-formal (e.g. organized learning opportunities outside the education system, such as clinics and workshops) and informal (e.g. learning via activities of daily coaching, interaction with peer coaches, self-directed learning) activity was critically related to development. Second, Lynch and Mallett (2006) found that Australian highperformance coaches (n = 5) spent most of their time directly interacting with athletes in preparation for, or at competitions, averaging over 20,000 hours in active coaching across their careers in contrast to 900 hours invested in formal coach education. Additionally, they typically spent about 14,000 hours in administrative and planning duties. Of the four coaches who acknowledged having important mentors, they each reported at least two mentors across a career. All coaches reported formerly competing in athletics themselves, for an average of 11 years, and most coaches were modestly high-level performers, though not outstanding. Erickson et al. (2007) examined the past activities of Canadian university coaches in relation to 18 development experiences. Results demonstrated that several experiences were necessary at minimum to achieve university status: (1) having five (for individual sport coaches) or eight seasons (team sport coaches) of former experience playing the sport that one now coaches; (2) having one (for team sport coaches) or two mentors (individual sport coaches) when starting out as a coach between 24–29 years of age; (3) either coaching for 438


9/26/2012 9:09:10 am

Coaching expertise: Quantifying experiences

three seasons in the developmental context (i.e. school-based, less competitive) early in one’s career, or being an assistant coach for one season in the elite context before age 29. Furthermore, career development as a high-performance coach focused on a primary sport and not on the same variety of sports played when they had been athletes. Although necessary, time spent in formal coaching education activities was diminutive. Team sport coaches adopted leadership positions and had general experience in multiple team sports during their playing days. Investigators discounted having been an exceptionally elite athlete, and past coaching in the recreational context (i.e. participatory, novice instructional), as necessary for becoming a high-performance coach. Interestingly, due to wide variability on many developmental measures, investigators emphasized that minimal threshold experience (MTE) values could better inform coach development practices. MTEs were determined for those developmental activities for which more than 75 percent of high-performance coaches had reported values. On a within-participant basis, the additive scores for quantities reported in just these MTEs amounted to 64 percent of the total quantity of developmental experience that elite coaches reported overall across their career for all possible learning activities. The remaining time spent in developmental activities not accounted for by MTEs likely represented the highly diversified and individualized learning paths upon which elite coaches embark. Young et al. (2009) compared skilled Canadian athletics coaching groups (ranging from local up to national level) on 14 learning activity measures. Investigators used tests of significance in analyses of variance, post hoc tests, and effect sizes, to draw conclusions about group differences. The most-skilled group accumulated more years of coaching experience in either a head or assisting capacity, than less-skilled groups. More skilled groups invested more time interacting directly with athletes, and with assisting coaches, at any point in a career. National-level coaches took more post-secondary coaching courses than lesser-skilled counterparts. Former experience as a track and field athlete was necessary to coach beyond the local club level, however, no differences were found between senior club, provincial, and national-level coaches for former athletic prowess (i.e. all were moderately high-level performers), length of one’s former athletic career, number of years that they self-coached, or the number of personal coaches they had as athletes. Finally, Koh et al. (2011) discovered that national basketball coaches in Singapore had typically been above-average elite basketball players, had coached for at least ten years before reaching the elite level, with most of those years in the developmental context. These coaches averaged only 110 hours in formal coach accreditation sessions across their careers, which ranged in duration 3–23 years. Perhaps ref lecting cultural nuances, mentorship activities were absent and entry ages for various coaching experiences were delayed compared to prior works. In sum, a few common trends appear across these five quantitative studies. First, the studies highlight the diverse number of activities that can be measured and, on a withinvariable basis, data demonstrate substantial variance with standard deviations often exceeding group mean values. Second, skilled high-performance coaches report little time in formal coach education activities, amounting to less than 5 percent of coaching-affiliated time annually (Gilbert et al. 2006), or less than 3 percent of time spent relative to other coaching roles across a career (Lynch and Mallett 2006). Regardless, it is still notable that national coaches complete significantly more coaching workshops than all lesser-skilled groups at any point within a career (Young et al. 2009). Third, coaches accumulate vast amounts of coaching experience before becoming a head coach in the elite context. These amounts derive from head or assisting coaching experience in the elite context, and possibly 439


9/26/2012 9:09:10 am

B.W. Young

experiences in the developmental context, although experiences in the recreational context appear unimportant. Fourth, mentorship ‘received’ and ‘given’ both appear critical to becoming a highly skilled coach, with the former being most important before age 30. Fifth, former athletic experience is a prerequisite, and should have been in the elite context of the sport one now coaches, and at least at a moderately competent performance level for five years. Uniquely for team sport coaches, former playing experiences should have been in several team sports besides the one that they now coach, and included multiple leadership roles.

Appraisal of extant research: finding a path forward This section attempts to recognize the merits of recent studies as well as possible limitations in relation to eight identified themes. These themes are advanced for possible consideration with respect to future research. Where possible, specific recommendations and refined research questions are presented, which are informed by coaching science literature, but also by empirical works from broader literature on expertise.

1 Future research should focus on group discriminability rather than description Most studies have recruited a sample of successful coaches, numerically described their past experiences in various learning activities, and then compared these data to data for coach samples in other studies (which are often from different sports). If researchers wish to explain the activities that lend themselves to long-term development, then between-group analyses within the same sport and within the same study are instrumental. For example, pertinent research on long-term athlete development allows that quantities for developmental activities (i.e. DP) be submitted to inter-group analyses to explain differences in performance status – cumulative DP consistently distinguishes between elite and less-elite athletic groups on a within-study basis, with elite groups amassing the greatest practice overall (e.g. Ward et al. 2004) or more practice in critical activities (e.g. Young and Salmela 2010). Similar use of inferential statistics will allow coaching researchers to reliably judge the contribution of certain learning activities to development. When employing these analytic strategies, confidence in between-group findings is heightened when results show significant differences across multiple groups that represent incremental levels of coaching competency in the same sport (see Figure 35.1).

2 Researchers should employ similar metrics for quantifying coach learning to be able to compare results across studies In an effort to find consensus, this section catalogues learning ‘metrics’ that have been employed as measures in prior quantitative research, and which consistently are identified as critical learning opportunities driving development (Côté 2006; Erickson et al. 2007; Lynch and Mallett 2006; Mallett et al. 2009; Nelson et al. 2006; Werthner and Trudel 2006; Young et al. 2009). Future researchers might consider several possible metrics for quantifying activities, which fall into four broad categories of learning: (1) coach education activities; (2) mentoring; (3) experiential learning activities; and (4) former athletic experience (see Table 35.1).

440


9/26/2012 9:09:10 am

Coaching expertise: Quantifying experiences 15000

25.0

Career Total Hrs

Yrs Coaching

20.0

15.0

10.0

10000

5000

5.0 7.1 Local Club

10.0

15.4

Sr Club

Prov

23.1

0

Nat

2105

3875

9116

12736

Local Club

Sr Club

Prov

Nat

2.2

3.3

Prov

Nat

A

B

4.0

3.0

Coaching Courses

How many Mentors

4.0

2.0

1.0

3.0

2.0

1.0

1.5

1.0

Local Club

Sr Club

2.6

3.9

Prov

Nat

0.0

C

0.5

1.1

Local Club

Sr Club

D

Figure 35.1: Data for select learning activities across four incrementally skilled groups in Canadian athletics coaching – local club, senior club, provincial level, and national level. Between-group trends are displayed for total years of coaching (A), cumulative hours interacting with athletes across a career (B), total number of mentors (C), and number of post-secondary coaching courses (D), as a function of skill group (Young et al. 2007).

‘Coach education activities’ include college and university-level courses, accreditationbased sessions affiliated with a formal coach-education program, which all conform to ‘mediated’ (Werthner and Trudel 2006) learning opportunities. This category also includes other mediated but non-formal experiences such as clinics/symposia/workshops. ‘Mentoring’ comprises unmediated learning opportunities in that one watches other coaches and has somewhat informal interactions with a coaching peer. Apprenticeships with a coach mentor have been measured by the discrete number of relationships that a person reports in the past. Due to reciprocal learning benefits for both mentor and apprentice (Bloom et al. 1998), future work might continue to assess the discrete number of apprentices that coaches have in turn mentored. 441


9/26/2012 9:09:10 am

B.W. Young Table 35.1: Metrics for assessing relevant activities and experiences according to category of learning Category

Activity or Experience

Suggested Metrics

Coach education activities

• institutional-affiliated, postsecondary coaching courses

number

• coach accreditation-based courses, sessions • clinics, symposia, workshops attended Mentoring

• relationships as a coach apprentice

number

• relationships as a mentor, assisting coaches Experiential learning

• interaction with athletes in training for each calendar year: • months per year • hours per week, for an average week during the in-season • interaction with athletes in competition • investment in administration, planning, organization • ref lective investments

Former athletic experiences

• career duration in sport now coaching (at elite level)

number of seasons played

• performance indices in elite context

recall of verifiable statistics (times/ scores), performance bests, roster selections, starts in line-up

• coaches while an athlete (at elite level) in sport now coaching

number

• team sports played while an athlete (including sports besides one now coaching)*

number

• leadership positions on teams (all sports) as an athlete*

percentage of all seasons/years in which one was designated captain or assistant captain

* These transferable experiences should be assessed uniquely for team sport coaches.

Coaching involves constant behavioural interactions between training, competition, and organizational venues (Côté et al. 1995), thus, researchers should refrain from narrow conceptualizations of the informal/incidental learning that occurs through active coaching experience. For example, Young et al. (2009) assessed only coaching interactions in training 442


9/26/2012 9:09:10 am


and competitive venues. Assessing time invested in training, competitive, and organizational capacities using three separate metrics (e.g. Gilbert et al. 2006) is preferred. Finally, studies have yet to enumerate an integral process of daily experiential coach learning, which is coaches’ deliberate ref lection on their experiences (e.g. Irwin et al. 2004). Both ‘ref lection on action’ after games/practices, and ‘retrospective ref lection’ at season’s end, afford opportunities for coaches to refine/gain knowledge (Gilbert and Trudel 2001). In sum, future researchers might consider employing reliable and valid metrics for each of training interactions, competitive interactions, organizational investments, and ref lective investments, under a broad category entitled ‘experiential learning’. ‘Former athletic experiences’ in the sport one now coaches appear important for the assimilation of knowledge which one may later apply when reaching the coaching ranks (Côté 2006; Lynch and Mallett 2006), and because prior athletic experience is a major source of coaching efficacy (see Chase and Martin, Chapter 6 in this volume). However, the common practice of self-reporting former athletic ability is possibly fraught with difficulties due to memory distortion and self-presentation. Future researchers should verify the reliability of estimates using archived statistics for playing performance and roster selections in team sports, and former performance indices can be normalized across standardized events to give reliable performance estimates in individual sports like track and field (Young et al. 2009). Quantifying the portion of one’s athletic experiences in leadership roles (e.g. Erickson et al. 2007) will continue to be important with respect to coach development in team sports. Finally, it might be fruitful to survey the number of different coaches that they had as a former athlete in elite sport, because elite players who later progress to coaching may assimilate strategies from the very coaches for whom they played (Cushion et al. 2003; Salmela 1995). As informal coach learning opportunities, former athletic experiences are assessed for the sport one now coaches, but may also be considered with respect to alternative sports one may have ‘sampled’ previously from which critical learnings may have transferred to the sport one now coaches (Erickson et al. 2007).

3 Researchers should examine how transferable (non-specific) experiences are associated with skilled coaching status In particular, (1) former athletic experiences in sports besides the one now coaching, and (2) coach learning experiences in the developmental sport context may provide breadth which may become particularly formative in terms of coaching knowledge and leadership competencies later in the elite context (e.g. Erickson et al. 2007). At least among team sport coaches, Table 35.1 recommends assessing the number of team sports formerly played (besides the team sport one now coaches), and percentage of experiences in which one adopted leadership (assistant captain/captain) positions on teams from all sports. To measure accumulations of experiential learning in the developmental context, future survey instructions should have face validity to carefully direct participants about how to respond in relation to defining criteria for this context (see Côté et al. 2007). Moreover, researchers may submit these data to analyses that consider how non-specific activities (i.e. not related to one specific sport context) during an early developmental stage can inf luence requisite amounts of investment in specific activities at a later developmental stage on the road to skilled coaching in the elite context. In the domain of long-term athlete development, for example, Baker et al. (2003) performed such analyses to illustrate how non-specific activities (e.g. sampling and deliberate play) in the early playing years resulted in transferable skills that

443


9/26/2012 9:09:10 am

B.W. Young

subsequently reduced the number of hours that players later required in sport-specific activities before making elite national teams.

4 The linearity of stage models may be problematic and proper analyses are required to determine their suitability Quantitative research evolved from qualitative work with elite coaches, which was important for articulating stage-based models of development (e.g. Schinke et al. 1995). Recent quantitative studies have advanced similar models that are ‘linear’ in nature, meaning that individuals who aspire to be elite coaches should necessarily pass through one stage before progressing to the following stage, with certain developmental roles and activities being unique to some stages and less represented during others (Erickson et al. 2007; Koh et al. 2011). However, the linearity of the developmental path may be problematic (Trudel and Gilbert 2006) in that many individuals who reach elite coaching levels are able to bypass certain stages en route, and considering that possibly ‘no common pathways lead to national elite coaching positions’ (Schinke et al. 1995: 58). Assuming that the value of any developmental framework is judged by whether it captures the experience of nearly all aspiring competitive coaches, then linear models may be challenged to accommodate diverse experiences that accumulate with differential pacing across coaches. If one considers recent works underscoring the highly personalized preferences associated with coach learning activities (Erickson et al. 2008), and the idiosyncrasies of elite coaches’ developmental paths (Werthner and Trudel 2009), then the advancement of stage models is possibly premature. Still, if the articulation of stage models using quantitative data is preferred, then sufficiently large samples involving multiple coach skill groups should be recruited in order to conduct mixed-model analyses of variance (ANOVAs) or repeated measures ANOVAs. The interpretation of group (e.g. skilled versus less-skilled) by time interactions for various learning metrics would be helpful in determining which developmental activities are critical at different points (e.g. after one year of coaching, after three years, five years, etc.) in the progression. Results from such analyses would move researchers beyond the specification of role types (e.g. player in sport now coaching, assistant/head coach) and determination of milestone ages for each stage; instead, results would allow investigators to determine the critical amounts in accumulated learning metrics that significantly distinguish skilled and less-skilled coaching groups at designated points during career-long learning, irrespective of starting age. Although the recruitment of multiple skill groups for between-group analyses might necessarily be incremental (e.g. a ladder of skill groups), the path by which individuals accumulate learning activities and develop their coaching skills is not necessarily linear. In fact, future research that analyzes cumulative measures for various learning metrics across the longterm may instead determine that coach learning proceeds in a non-linear or quadratically accelerated pattern as is the case in other fields of expertise. According to the DP framework and trends observed for elite wrestlers (Hodges and Starkes 1996), team ball sport players (Baker et al. 2003), and musicians (Ericsson et al. 1993), a ‘monotonic benefits assumption’ establishes how aspiring individuals on the road to expertise accrue greater time in learning activities at each subsequently observed time point in the developmental path, and that the trend for accumulating practice activities inf lects upwards as time passes. This trend assumes continually increasing personal investment in learning activities (and concurrent benefits) over time, which may be a more f lexible perspective to the linear assumption that one ‘needs to do this, or have this experience, by this age, before passing to the next stage’. 444


9/26/2012 9:09:10 am


5 It is important to control for career length when comparing differently skilled coaching groups on accumulated learning metrics This could be accomplished by conducting group (i.e. those who become highly skilled coaches versus those who do not) by time analyses with all groups anchored at the same starting point and comparing measures after start age, after three years, after five years, and onwards. This approach challenges investigators to find sufficient sample sizes for lesserskilled comparison groups at progressive periods in a career, because their career length may not be sufficiently lengthy, or there may be problems with intermittent participation. Alternatively, one could conduct analyses of co-variance on cumulative career totals while controlling for ‘slow-moving’ career duration variables (e.g. years or seasons of coaching) for all participants (e.g. Young et al. 2009). This is important because the most successful coaches in the elite context commonly report earlier entry ages into coaching, and have more years of experience that will typically bias the cumulative measures in their favour. A pressing question is whether coaches who eventually become highly skilled invest more in certain developmental activities at any point within their career, which is determined after controlling for career length and possibly coach starting age. This would help determine whether the achievement of most-skilled coaching status results from relatively greater investments in coach learning opportunities, rather than being a by-product of a lengthy career.

6 It may be important to employ statistical approaches that use the full intra-individual variability of data for learning metrics and that acknowledge our limits in explaining variance in skilled coach development In studies of MTEs, investigators have condensed the repertoire of dependent measures based on whether all, or 75 percent, of elite coaches report pertinent experiences, and have converted the values of certain measures to become a percentage of the maximal value reported by an elite coach (e.g. Erickson et al. 2007). The former step reduces the number of developmental variables considered, and the second step reduces the range of variability in the distributions of developmental variables under examination, which may preclude researchers from observing interesting findings. Instead, researchers might consider examining data from all coaches including lower values in the distributions. To this end, if researchers were to adopt ANOVAs, then within-group variance would be fully considered when testing for group differences without unnecessary transformations or manipulations by the researchers. By the nature of these analyses, the likelihood of finding significant group differences between successful and less-successful coaches is greater if there are veridical differences in the mean levels between the groups, but also if the intact and unmanipulated variability around each group mean happens to be minimal. Future research should investigate how individual differences on various learning metrics predict skill group assignment, perhaps using a discriminant function analysis (e.g. Helsen and Starkes 1999). For example, results might tell us that 68 percent of membership in either a skilled or a less-skilled coaching group is explained by a host of independent variables representing coach learning metrics. Results might also compel us to admit that we cannot confidently explain 32 percent of variance in skill group assignment, thereby challenging us to improve the validity and reliability of our quantitative designs. Moreover, this approach could afford qualitative researchers a mandate for complementary or mixed-methods research that addresses the quantitatively ‘unexplained’, particularly researchers who are 445


9/26/2012 9:09:10 am

B.W. Young

interested in detailing coach learning biographies and describing personalized idiosyncrasies in the pursuit of learning.

7 Future research should explore affordances and ensure that all sampled coaches have similar aspirations Expert coaches likely seek out many resources in the form of people, organizations, funding, and programs to support their learning. However, experts may also be afforded resources in their environments to engage in critical learning opportunities. Affordances are inherently differential, meaning that they predispose certain individuals to benefit from their surroundings irrespective of personal decisions or actions, while others are disadvantaged or face barriers by not having similar affordances. For example, long-term athletic development is inf luenced by inequitable affordances related to where an athlete grew up and when they were born (Côté et al. 2006), and whether they had access to a master coach in the developing years (Kalinowski 1985). Inequities in coach development may similarly arise from a number of factors whereby some coaches benefit from ‘being in the right place at the right time’ (Schinke et al. 1995: 57), including the differential availability of coach education activities, mentor programs, vacancy of coaching jobs, and inequitable access due to geography (e.g. remote locales) amongst others, and which possibly interact with demographic factors such as gender and ethnicity. More research needs to establish the priority of affordances facilitating learning opportunities for many coaches, and commensurate in affordances which act as barriers to learning. One approach might involve surveys of barrier items with coaches being asked to report the frequency and limiting degree for each item with respect to the learning process. An understanding of affordances might encourage us to adopt non-linear functions for portraying the coach development path, by recognizing that the pace of individuals’ investment in learning activities might be somewhat inconstant and becomes instantly accelerated following a specific affordance (e.g. an opportunity such as the sudden posting of a graduate assistantship coaching position). It behoves researchers to determine exactly what these affordances are and how they might inf luence the pattern of aspiring coaches’ investments in learning metrics over time. Although coach development surveys appear to have implicitly assumed that all coaches are equally motivated to ascertain higher skill levels, motivational factors likely mediate the degree of coaches’ investment in developmental activities. For example, a senior club coach might be motivated to engage in developmental activities that they deem sufficient for the level at which they are presently, and do not aspire to more skilled roles which may demand greater investment. In future, therefore, researchers should ensure that coaches have similar motivational orientations towards coaching as a vocation requiring expertise, and similar perceptions towards the value of coach developmental activities, ensuring that these are inclusion criteria for the purposeful sampling of participants.

8 Future researchers should validate skill indices that distinguish between expert and less-expert coaches, and regress skill indices on data for developmental learning activities It is critical that coaching groups be discriminated based on outcome indices that validly ref lect gradients in competency. To date, studies have validated the most-skilled coaches using one or more criteria, including win-loss records, numbers of teams/athletes coached to championship finals, recognition from peers, an MTE related to five years of coaching, and 446


9/26/2012 9:09:10 am


accreditation levels (e.g. Gilbert et al. 2006; Lynch and Mallett 2006). Only Young et al. (2009) showed how incrementally higher skilled coaching groups also exhibited correspondingly higher values for these outcomes as well as for the quality of the athletes they had coached. Two important points can be made about these outcome indices: first, although potentially verifiable, their validity has never been confirmed using external archives of information; second, these were outcomes ref lecting coaching ‘success’ and not coaching skill. Indices of success and indices of skill are not necessarily related. For example, a highly skilled coach may fall short on success indices, and a less-skilled coach may have great success, because success outcomes depend highly on athletes’ performances in competition. Mallett and Côté (2006) cautioned that athletes’ performances are very unstable factors and accomplishment outcomes for athletes or teams are therefore indirect and unreliable measures of coaching effectiveness. Coaching effectiveness should instead be judged according to more stable indices, called ‘skills’, which underlie superior performance in the domain (see Ericsson 2003). Ford et al. (2009) advised coaching researchers who might use this approach to first identify representative tasks that capture the essence of expertise in coaching. If expert groups repeatedly perform better on these representative skill tasks than less-expert groups in a controlled empirical setting, results would enable investigators to identify the skill mechanisms that mediate expert coaches’ performance. Although this approach has yet to be popularly received in coaching, representative skill tests can be modified from pedagogy (Berliner 2001) and physical education (Dodds 1994) domains. Examples of pertinent tasks include: (1) procedural tests for coach-athlete exchanges (Erickson and Côté, Chapter 9 in this volume) and interactive decision-making ( Jones et al. 1997); (2) visual recognition tasks (Imwold and Hoffman 1983), think-aloud protocol (Rutt Leas and Chi 1993), or eye movement registrations (Petrakis 1987); (3) tests of pedagogical content knowledge (Block and Beckett 1990) (see also work by Schempp and colleagues, e.g. Schempp et al. 2004). Finally, an expertise approach dictates that researchers trace the amount of learning activity associated with the acquisition of these coaching skills, to identify when and how these skills were acquired (Ford et al. 2009). This brings us ‘full circle’, in a sense, as each of the existing quantitative studies (using the retrospective guide) has profiled practice histories and enumerated developmental activities (or metrics) that are likely associated with crucial coaching skills. Future researchers will need to integrate the quantitative data for the various learning metrics in which coaches have invested their time across their career with measures for stable coaching skills which validly discriminate experts and less-experts. Such analyses would tell us which coaching skills (deemed valid requisites for expertise) are amenable to change (learning) and which cumulative developmental activities are most critical in facilitating their acquisition.

Summary and implications for coaching practice In sum, the enumeration of learning activities and subsequent submission of these data to between-group analyses are necessary if researchers are to articulate the path to coaching expertise. It is important for researchers to focus less on chronological stages through which coaches might pass in their development, and instead focus on cumulative measures relating to the learning metrics that are accepted with consensus amongst researchers. Attempts to discriminate multiple skill groups should consider controlling for confounding variables relating to career length, levels of individual aspiration, and should consider moderating variables (i.e. affordances, barriers) that establish inequitable conditions for long-term development. 447


9/26/2012 9:09:10 am

B.W. Young

Quantitative coach development research cannot be a simple exercise in ‘bean counting’ – results must inform the long-term process of coaching skill acquisition. Emergent research possibly has implications for coach development schemes and coach education programs. Findings might determine which learning metrics best predict coaching expertise, and whether there needs to be a significant investment in each learning metric and particular sub-activities within each metric. For example, if experiential learning metrics are most important, coach education systems might afford more credit to coaches’ interactions in this domain, publish guidelines that dictate how much direct coaching is required, and introduce policies to effectively account for such experience before bestowing accreditation. If mentoring proves critical in discriminating skill groups, then steps can be taken to better entrench mentoring experiences in coach education schemes, and to tailor programs wherein mentors and apprentices are properly matched. If former athletic experiences are salient, strategies might be invoked to expose late-adolescent and early-adult elite athletes to coaching roles. Whereas early coaching recruitment might focus on playing ranks, later coach curricula might ask young coaches to ref lect on prior scenarios when they themselves had been players, getting them to draw lessons from their former coaches’ tactics. If transferable experiences are important, coach development systems may be able to sequence early coaching activities within the developmental sport context into graduated roles in the elite competitive coaching context. Using valid success outcome indices and/or representative skill tests, future quantitative research will be instrumental in determining how quantities in each learning metric contribute to expert versus less-expert group differences. The relative predictive weight for each metric could dictate the prescription for how much time and how many resources should be invested to support learning in the experiential, mentoring, former athletic, and formal coach education domains. Though any recommendations would depend on replicable results in future work, these prescriptions as well as information about critical affordances have implications for coach education programs deciding where to best allocate scarce organizational resources to support the development of a great number of coaches. Finally, prescriptions for where to invest time, energy and personal resources will be instrumental for aspiring individuals seeking a long-term developmental route to coaching expertise. Knowing the most important learning domains in which one should invest, when to invest during certain periods in the developmental progression, and knowing which specific environmental affordances to pursue – these are all aspects that developing coaches can take under advisement when charting their course.

References Baker, J., Côté, J. and Abernethy, B. (2003) ‘Sport-specific training, deliberate practice and the development of expertise in team ball sports’, Journal of Applied Sport Psychology, 15: 12–25. Berliner, D.C. (2001) ‘Learning about and learning from expert teachers’, International Journal of Educational Research, 35: 463–482. Block, K.K. and Beckett, K.D. (1990) ‘Verbal descriptions of skill by specialists and nonspecialists’, Journal of Teaching in Physical Education, 10: 21–37. Bloom, G., Durand-Bush, N., Schinke, R.J. and Salmela, J.H. (1998) ‘The importance of mentoring in the development of coaches and athletes’, International Journal of Sport Psychology, 29: 267–281. Bronfenbrenner, U. (2005) Making Human Beings Human: Bioecological Perspectives on Human Development, Thousand Oaks, CA: Sage. Brophy, K. and Young, B.W. (2009)‘Test-retest reliability of long-term retrospective recall methodologies’, presented at the Eastern Canadian Symposium for Sport and Exercise Psychology, Toronto, ON, March.

448


9/26/2012 9:09:10 am

Coaching expertise: Quantifying experiences Côté, J. (2006) ‘The development of coaching knowledge’, International Journal of Sports Science and Coaching, 1: 217–222. Côté, J., MacDonald, D., Baker, J. and Abernethy, B. (2006) ‘When “where” is more important than “when”: birthplace and birthdate effects on the achievement of sporting expertise’, Journal of Sport Sciences, 24: 1065–1073. Côté, J., Salmela, J.H., Trudel, P., Baria, A. and Russell, S. (1995) ‘The coaching model: A grounded assessment of expert gymnastic coaches’ knowledge’, Journal of Sport and Exercise Psychology, 17: 1–17. Côté, J., Young, B., North, J. and Duffy, P. (2007) ‘Towards a definition of excellence in sport coaching’, International Journal of Coaching Science, 1: 3–18. Cushion, C.J., Armour, K.M. and Jones, R.L. (2003) ‘Coach education and continuing professional development: Experience and learning to coach’, Quest, 55: 215–230. Dodds, P. (1994) ‘Cognitive and behavioral components of expertise in teaching physical Education’, Quest, 46: 153–163. Erickson, E., Bruner, M.W., MacDonald, D.J. and Côté, J. (2008) ‘Gaining insights into actual and preferred sources of coaching knowledge’, International Journal of Sports Science and Coaching, 3: 527–538. Erickson, K., Côté, J. and Fraser-Thomas, J. (2007) ‘Sport activities, milestones, and educational experiences associated with high-performance coaches’ development’, The Sport Psychologist, 21: 302–316. Ericsson, K.A. (2003) ‘Development of elite performance and deliberate practice: an update from the perspective of the expert performance approach’, in J.L. Starkes and K.A. Ericsson (eds) Expert Performance in Sport: Recent Advances in Research on Sport Expertise, Champaign, IL: Human Kinetics. Ericsson, K.A., Krampe, R.Th. and Tesch-Römer, C. (1993) ‘The role of deliberate practice in the acquisition of expert performance’, Psychological Review, 100: 363–406. Ford, P., Coughlan, E. and Williams, M. (2009) ‘The expert-performance approach as a framework for understanding and enhancing coaching performance, expertise and learning’, International Journal of Sports Science and Coaching, 4: 451–463. Gilbert, W.D. and Trudel, P. (2001) ‘Learning to coach through experience: Ref lection in model youth sport coaches’, Journal of Teaching in Physical Education, 21: 16–34. Gilbert, W.D., Côté, J. and Mallett, C. (2006) ‘Development paths and activities of successful sport coaches’, International Journal of Sports Science and Coaching, 1: 69–75. Helsen, W. and Starkes, J.L. (1999) ‘A multidimensional approach to skilled perception and performance in sport’, Applied Cognitive Psychology, 13: 1–27. Hodges, N.J. and Starkes, J.L. (1996) ‘Wrestling with the nature of expertise: A sport specific test of Ericsson, Krampe and Tesch-Römer’s theory of deliberate practice’, International Journal of Sport Psychology, 27: 400–424. Imwold, C.H. and Hoffman, S.J. (1983) ‘Visual recognition of a gymnastics skill by experienced and inexperienced instructors’, Research Quarterly for Exercise and Sport, 54: 149–155. Irwin, G., Hanton, S. and Kerwin, D.G. (2004) ‘Ref lective practice and the origins of the elite coaching knowledge’, Reflective Practice, 5: 425–442. Jones, D.F., Housner, L.D. and Kornspan, A.S. (1997) ‘Interactive decision making and behaviour of experienced and inexperienced basketball coaches during practice’, Journal of Teaching in Physical Education, 16: 454–468. Kalinowski, A.G. (1985) ‘The development of Olympic swimmers’, in B.S. Bloom (ed.) Developing Talent in Young People, New York: Ballantine. Koh, K.T., Mallett, C.J. and Wang, C.K.J. (2011) ‘Developmental pathways of Singapore’s high performance basketball coaches’, International Journal of Sport and Exercise Psychology, 9: 338–353. Lynch, M. and Mallett, C. (2006) ‘Becoming a successful high performance track and field coach’, Modern Athlete and Coach, 44: 15–20. Mallett, C. and Côté, J. (2006) ‘Beyond winning and losing: Guidelines for evaluating high performance coaches’, The Sport Psychologist, 20: 213–218. Mallett, C.J., Trudel, P., Lyle, J. and Rynne, S.B. (2009) ‘Formal vs informal coach education’, International Journal of Sports Science and Coaching, 4: 325–341. Nelson, L.J., Cushion, C.J. and Potrac, P. (2006) ‘Formal, nonformal and informal coach learning: A holistic conceptualisation’, International Journal of Sports Science and Coaching, 1: 247–259. Petrakis, E. (1987) ‘Analysis of visual search patterns of dance teachers’, Journal of Teaching in Physical Education, 6: 149–156.

449


9/26/2012 9:09:10 am

B.W. Young Rutt Leas, R. and Chi, M.T.H. (1993) ‘Analyzing diagnostic expertise of competitive swimming coaches’, in J.L. Starkes and F. Allard (eds) Cognitive Issues in Motor Expertise, Amsterdam: Elsevier. Salmela, J.H. (1995) ‘Learning from the development of expert coaches’, Coaching and Sport Science Journal, 1: 3–13. Schempp, P.G., McCullick, B., St. Pierre, P., Woorons, S., You, J. and Clark, B. (2004) ‘Expert golf instructors’ student-teacher interaction patterns’, Research Quarterly for Exercise and Sport, 75: 60–70. Schinke, R.J., Bloom, G. and Salmela, J.H. (1995) ‘The career stages of elite Canadian basketball coaches’, Avante, 1: 48–62. Trudel, P. and Gilbert, W. (2006) ‘Coaching and coach education’, in D. Kirk, D. Macdonald and M. O’Sullivan (eds) The Handbook of Physical Education, London: Sage. Ward, P., Hodges, N.J., Williams, A.M. and Starkes, J.L. (2004) ‘Deliberate practice and expert performance: defining the path to excellence’, in A.M. Williams and N.J. Hodges (eds) Skill Acquisition in Sport: Research, Theory and Practice, New York: Routledge. Werthner, P. and Trudel, P. (2006) ‘A new theoretical perspective for understanding how coaches learn to coach’, The Sport Psychologist, 20: 198–212. Werthner, P. and Trudel, P. (2009) ‘Investigating the idiosyncratic learning paths of elite Canadian coaches’, International Journal of Sports Science and Coaching, 4: 433–449. Young, B.W. and Salmela, J.H. (2010) ‘Examination of practice activities related to the acquisition of elite performance in Canadian middle distance running’, International Journal of Sport Psychology, 41: 73–90. Young, B.W., Jemczyk, K., Brophy, K. and Côté, J. (2009) ‘Discriminating skilled coaching groups: quantitative examination of developmental experiences and activities’, International Journal of Sports Science and Coaching, 4: 397–414. Young, B.W., Jemczyk, K. and Washington, M. (2007) ‘Quantifying the activities associated with the incremental development of coaches in Canadian track and field’, report presented to the Coaching Association of Canada and Athletics Canada, April.

450


9/26/2012 9:09:10 am