Can we hasten expertise by video simulations? Considerations from an ecological psychology...

Running head: PERCEPTUAL LEARNING

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Running Head: Perceptual learning 1

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“Can we hasten expertise by video simulations?” Considerations from an ecological 4

psychology perspective 5

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Matt Dicks1, John van der Kamp2, 3

, Rob Withagen4, & Johan Koedijker

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1: Department of Sport and Exercise Science, University of Portsmouth, England 12

2: MOVE Research Institute Amsterdam, VU University, The Netherlands 13

3: Institute of Human Performance, University of Hong Kong, Hong Kong SAR 14

4: Center for Human Movement Sciences, University Medical Center Groningen, University 15

of Groningen 16

5: Institute of Sport Science, University of Bern, Switzerland 17

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Address correspondence to Matt Dicks, [email protected], Department of Sport and 22

Exercise Science, Spinnaker Building, University of Portsmouth, Cambridge Road, 23

Portsmouth PO1 2ER, United Kingdom. 24

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Abstract 2

In their 1994 publication, Starkes and Lindley considered whether perceptual skill 3

could be trained through the observation of video simulations of sport situations. We return to 4

this topic 20 years later and provide a critical review of the subsequent research on perceptual 5

learning in sport. We reflect on the implications from recent empirical evidence, which 6

indicates that perceptual expertise in sport is best captured using experimental methods that 7

allow participants to perceive and act (i.e., produce an interceptive action) against an 8

opponent in real-time. Despite the pertinent implications that these findings have for the 9

training of perceptual skill, until now, a review has not been forthcoming. Specifically, we 10

consider the implications of an ecological approach to perceptual learning for training 11

interventions in sport. We provide a critical review of current literature, before focussing on 12

an ecological theory of learning as a framework for our perspective. We then overview two 13

contemporary topics in ecological psychology - continuum of contact and between-participant 14

variability in perception-action - before considering the implications of our perspective for 15

future research. 16

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Key Words: ecological psychology, perception, action, perceptual learning, expertise 18

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Since its conception as a field of study, many researchers working in different sub-6

disciplines of sports science have set out to understand the mechanisms that underlie expertise 7

in sport. One particular sub-discipline, which is the focus of the present article, is the body of 8

research that has studied how elite sportspeople skillfully adapt to situations in fast-ball sports 9

(e.g., tennis: Huys, Smeeton, Hodges, Beek, & Williams, 2008; or cricket: Mann, Abernethy, 10

& Farrow, 2010). Experimental investigations have tended to focus on whether performers 11

with expertise in fast-ball sports pick-up advance information from an opponent‟s movement 12

at an earlier point in time than novices (cf. Jones & Miles, 1978). Over the past three decades, 13

findings have largely demonstrated an experimental advantage for experts across several 14

different sports. For example, in a notable in situ study, expert volleyball players were found 15

to be better than novices at predicting the direction of a serve following the observation of an 16

opponent‟s action occluded before the moment of hand/ball contact (Starkes, Edwards, 17

Dissanayake, & Dunn, 1995). 18

Evidence from research demonstrating that elite performers make more accurate 19

predictions than novices (e.g., Starkes et al., 1995) has often provided a starting point for 20

perceptual training studies (e.g., see Williams, Ford, Eccles, & Ward, 2011). An example is 21

the publication of Starkes and Lindley (1994) who considered “whether it is possible to use 22

video technology or simulations to advance athletes to higher levels of expertise” (p. 213). 23

After citing findings from video based prediction studies of perceptual skill (e.g., Helsen & 24

Pauwels, 1993), Starkes and Lindley postulated that video training may have many particular 25

advantages in facilitating perceptual skill as video technology allows players to practice when 26


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injured, during the off-season and also in conjunction with on-court training (cf. p 211). In 1

their article, Starkes and Lindley considered the implications of a study that had examined the 2

effect of video training on the decision-making of collegiate and high-school female 3

basketball players (Starkes & Lindley, 1991). Pre- and post-training, participants had their 4

perceptual skill tested via a series of video clips created from over-head footage of Canadian 5

university women‟s basketball games. The video was stopped just before the ball-handler 6

executed her decision, after which, participants were required to select whether the best 7

decision for the player in possession would be to shoot, dribble or pass the ball. Following the 8

pre-test, half of the participants undertook six training sessions, comprising 16 to 22 different 9

video clips that were watched every other day for 13 days. At the end of training, participants 10

completed a video post-test. Results indicated that accuracy of decision making for the 11

experimental group marginally improved in the post-test while there was a decrease in 12

performance for a control group. In addition, response times for decision-making decreased 13

for both groups in the post-test, with the most substantial decrease occurring for the 14

experimental group. 15

In addition to the video test, participants also completed a transfer test in which they 16

viewed real-time play sequences while seated in the spectator stands. Target players‟ on-court 17

performed patterned plays, and at predefined moments, tried to freeze their positions once a 18

desired play option emerged. Participants were required to provide their decision-making 19

responses as quickly as possible after the players stopped on-court. Unlike the video-based 20

test, there were no improvements in decision making for the experimental group following the 21

video intervention. Taken together, the results suggested that video training may improve 22

accuracy on video-based tests of perceptual skill although there was no indication of transfer 23

to on-court performance. Subsequently, Starkes and Lindley (1994) considered that while 24

video training was a viable tool that could be used by coaches and trainers, it was not known 25


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at the time of their publication whether any improvements in video-based performance 1

transferred to game situations. 2

In the current article, we return to the topic of Starkes and Lindley‟s (1994) paper and 3

critically consider the findings from research studies that have examined whether expertise 4

can be hastened by video simulations. We draw upon recent evidence (e.g., Mann et al., 2010) 5

which demonstrates that perceptual expertise is best studied under conditions that require 6

sportspeople to (inter)act relative to the movements of other players and ball-flight 7

information in real-time. In line with earlier perceptual skill articles, we adopt an ecological 8

psychology perspective (e.g., see Beek, Jacobs, Daffertshoffer, & Huys, 2003; Dicks, Davids, 9

& Araújo, 2008). Preceding works in the sport domain (e.g., Fajen, Riley, & Turvey, 2009) 10

have demonstrated that J.J. Gibson‟s ecological approach (1966, 1979) is of fundamental 11

importance for the study of perceptual expertise. Indeed, previously, researchers have drawn 12

complementary links between Gibson‟s view and that of Brunswik‟s (1956) representative 13

design (Dicks, Davids, & Button, 2009), Kelso‟s (1995) dynamical systems theory (Araújo, 14

Davids, & Hristovski, 2006), and Milner and Goodale‟s (1995) two visual systems model 15

(van der Kamp, Rivas, van Doorn, & Savelsbergh, 2008). In addition to these articles, we 16

consider the implications of the ecological approach to perceptual learning developed by the 17

Gibsons (see E.J. Gibson & Pick, 2000; J.J. Gibson & E.J. Gibson, 1955). We review findings 18

in the sports perceptual learning literature before providing a brief overview of an ecological 19

approach to perceptual learning. We then focus on two contemporary concepts in the 20

ecological psychology literature, namely continuum of contact (Withagen, 2004) and 21

between-subject variability in perception-action (Withagen & Chemero, 2009). Finally, we 22

consider a number of implications for future research on perceptual learning in sport. 23

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Current approaches to training perceptual skill 25


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At the time of their publication, Starkes and Lindley (1994) noted that most perceptual 1

learning studies in the sport domain had considered expertise from a “basic information-2

processing perspective”. Broadly speaking, basic processing accounts propose that human 3

perception functions across different computational stages in a manner akin to the digital 4

computer (see Whiting, 1969). During visual perception, it is proposed that information is 5

added to sensory stimuli via memorial representations that reside within the person. The 6

internal mechanisms attributed to representations are thought to help experts develop an 7

encoding for a situation, which precedes a separate stage that controls the performer‟s action 8

(Williams, et al., 2011). Significantly, within the basic processing approach, perception and 9

action are considered to function independently across a series of successive processing stages 10

(i.e., perception enslaves action). As exemplified by the approach adopted in many research 11

studies, a potential consequence of such theorizing is that improvements in perception are 12

considered possible when using video training methods that do not permit learners to perform 13

requisite actions (e.g., Abernethy, Schorer, Jackson, & Hagemann, 2012). 14

Information-processing explanations of visual perception have developed from the 15

basic theoretical perspective considered above (e.g., see Wolpert & Kawato, 1998). Despite 16

such advances, in the sport perceptual expertise literature, many of the methodological 17

approaches used in current research remain equivalent to the early studies that were motivated 18

by the basic information-processing approach. Namely, there is a retained focus on the use of 19

video and in situ methods, which measure expertise via predictive responses (i.e., no 20

interceptive action). In this regard, studies that have revealed expert-novice differences in 21

predictive judgments still aim to provide an empirical basis for perceptual training (e.g., 22

Abernethy et al., 2012; Williams, Ward, & Chapman, 2003). Therefore, rather than being 23

taught to use information in the control of their movements (e.g., action or interception), 24

interventions have tended to focus on improving a performer‟s ability to predict the outcome 25


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of an opponent‟s movement in the absence of any (inter)action (e.g., Williams, Ward, 1

Knowles, & Smeeton, 2002). 2

Reminiscent of the approach described in the work of Starkes and Lindley (1994), the 3

vast majority of perceptual training studies have presented video-clips to participants – often 4

alongside some form of instruction - with the aim of enhancing participant understanding on 5

the relationship between an opponent‟s kinematic movement (e.g., the orientation of the 6

service arm during a tennis serve) and an event outcome (e.g., tennis serve direction). Much 7

of the empirical efforts that have followed Starkes and Lindley‟s early work in this area have 8

focused on the content of the instructional protocols – for example, explicit instruction vs. 9

guided discovery vs. discovery learning – that describe the movement kinematics of the 10

opponent (for a review, see Jackson & Farrow, 2005). As such, researchers have considered 11

the different consequences these respective learning instructions may have on perceptual skill 12

when, for example, performing under pressure (Abernethy et al., 2012; Smeeton, Williams, 13

Hodges, & Ward, 2005). 14

The video interventions aimed at improving perceptual skills have focused on the idea 15

of training an a priori „optimal‟ decision or perceptual strategy (e.g., Williams et al., 2003). 16

For example, if one considers the research on gaze behaviors and perceptual skill in sport, it is 17

typical to average the gaze patterns of a sub-sample of experts resulting in a „one size fits all‟ 18

template strategy that learners are guided toward during video training (Hagemann, Strauss, & 19

Cañal-Bruland, 2006). Furthermore, the video clips presented to participants within the 20

training footage also denote „perfect‟ trials. For example, for the penalty throw in handball, 21

this approach entails video footage of shots executed to only the four respective corners of the 22

goal (Abernethy et al., 2012). As we will consider, not only do these described training 23

practices fail to account for any between-participant variations in perceptual skill (see Dicks, 24

Davids, & Button, 2010), but also, the gaze behaviors of experts are typically derived from 25

video prediction studies (Williams et al., 2002). Subsequently, if the question of transfer from 26


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video to in-game performance is considered relative to this method, recent research shows 1

that the gaze behaviors of performers recorded during video-based methods deviate 2

significantly from in situ interception strategies (for a review, see Travassos, Araújo, Davids, 3

O‟Hara, Leitão & Cortinhas, 2013). 4

Pertinent to such evidence, an important research issue highlighted by Starkes and 5

Lindley (1994) is whether video-training paradigms bring about performance improvements 6

outside of a laboratory based setting. Arguably, following their initial efforts, there have been 7

surprisingly few attempts to address this issue in fast-ball sports until recently (see Williams 8

et al., 2004). Perhaps most encouragingly, Hopwood and colleagues (Hopwood, Mann, 9

Farrow, & Nielsen, 2011) recently demonstrated that a 6-week video training intervention - 10

supplementary to regular fielding practice - improved the in situ fielding performance of 11

highly-skilled cricketers. Unfortunately, the study of Hopwood et al. aside, when performance 12

accuracy is considered, there is little evidence to support the benefits of video training. On the 13

whole, research largely demonstrates that novices who undertake video based training do not 14

improve their response accuracies in comparison with placebo groups. For example, Williams 15

and colleagues (2003) trained novice field hockey goalkeepers for the penalty shot situation 16

using video training before examining performance using a video and an in situ predictive 17

judgment test. The training group viewed video footage presented using a freeze-frame set-up 18

alongside perceptual training (explicit) instructions. A control group just completed the pre- 19

and post-tests whilst a placebo group viewed an instructional video, which provided 20

information on the technical requirements of field hockey goalkeeping. Results for the in situ 21

condition revealed that the training group initiated their responses significantly earlier in the 22

post-test in comparison with the placebo and control groups, although there were no 23

differences in performance accuracy between the groups. Thus, in line with the initial 24

observations of Starkes and Lindley (1994), evidence suggests that novices may produce 25


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earlier response times following video training, but these changes in timing occur in the 1

absence of improvements in performance accuracy. 2

When earlier response times have been considered a potential benefit to novice 3

performance following video training, it is important to note that changes in response times 4

have occurred in the absence of any requirement to perform an interceptive action. Indeed, 5

when an interceptive action has been required, moving too early has been shown to be 6

detrimental for sport performance (Dicks, Davids, et al., 2010). Recently, Triolet and 7

colleagues (Triolet, Benguigui, Le Runigo, & Williams, 2013) demonstrated that the timing of 8

world-class tennis players‟ movements occurred 160ms or later after opponent racket-ball 9

contact on 87% of all game situations. This finding indicates that elite performers in fast-ball 10

sports utilize a combination of situational, opponent and ball-flight information to guide their 11

movements. Ball-flight information is not possible within video training practices, while 12

situational information has typically not been sampled in perceptual skill studies (for an 13

exception, see Abernethy, Gill, Parks, & Packer, 2001). Therefore, as has been argued 14

elsewhere, the skill required in passively predicting a movement outcome is likely to be very 15

different to the perceptual-motor skill necessary during the control of interpersonal 16

interactions in sport contexts (see Dicks et al., 2008; van der Kamp et al., 2008). A point we 17

consider in further detail in the following section. 18

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The reciprocity of perception-action 20

The absence of in situ interception methods in the training and testing of perceptual 21

skill is at the heart of a most pertinent topic in the perceptual expertise literature. There is now 22

strong empirical evidence, which demonstrates significantly greater expert-novice effects for 23

in situ interception paradigms when compared to studies (video and in situ) that have 24

measured performance using predictive judgments (Travassos et al., 2013). For example, 25

Mann et al. (2010) reported significant increases in the performance of skilled cricket batsmen 26


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– but not novices – as the response mode required relative to a bowler‟s action and ball-flight 1

matched their performance expertise. That is, expertise effects were most clearly elicited 2

under an in situ interception response when compared with verbal, foot-movement and 3

simulated batting movements. The observed increases in response accuracy were predicated 4

on the availability of visual information from, not only the bowler‟s movements, but also ball-5

flight. Furthermore, in a gaze behavior study, Dicks, Button et al. (2010b) reported distinct 6

differences in the spatial and temporal distribution of goalkeepers‟ gaze patterns when facing 7

penalty kicks under different video and in situ experimental conditions. Following initial 8

fixation on the movement kinematics of the penalty taker during the run-up, goalkeepers 9

fixated the ball earlier and for a longer duration for an in situ interception response in 10

comparison with judgment-oriented response conditions (i.e., verbal and simplified body 11

movements). 12

The findings of greater expert-novice effects for in situ interception research 13

paradigms are in-line with the proposal of van der Kamp et al. (2008), who reaffirmed the 14

perspective of J.J. Gibson (1979) in ecological psychology by emphasizing the reciprocal 15

relationship between perception and action (see also, Chemero, 2009). J.J. Gibson (1966) 16

proposed that the pick-up of information is an active process, encompassing the mobile body. 17

That is, as J.J. Gibson (1979) put it, “We must perceive in order to move, but we must also 18

move in order to perceive” (p. 223). Moreover, he claimed that the most purposeful function 19

of perception is to guide movement. Central to this suggestion, it is proposed that an animal‟s 20

behavior is visually guided by perception of the opportunities for action that are offered by 21

objects and organisms in the environment. J.J. Gibson (1979) coined these opportunities 22

affordances (for recent reviews, see Chemero, 2009; Fajen et al., 2009). In line with such 23

theorizing, van der Kamp and colleagues proposed that perception and action are 24

complementary but entail the exploitation of different types of information across different 25

time scales. They argued that performance in fast-ball sports entails a reciprocal relation 26


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between perception of what action the situation affords (i.e., what action is most appropriate 1

in a given situation?), and the control of movement execution (i.e., how does one arrive at the 2

right place at right time to intercept a moving ball?). Therefore, experimental paradigms that 3

fail to study reciprocal perception-action (i.e., predictive judgment tasks) were proposed to 4

impede upon the complementary function of the visual systems and thus our understanding of 5

perceptual expertise (see Milner & Goodale, 1995; van der Kamp et al., 2008). 6

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An ecological theory of perceptual learning 8

Further to highlighting the importance of reciprocal perception-action, J.J. Gibson 9

(1979) argued on the importance of exploring a theory of perception, which proposes that 10

what animals perceive, is not an internally stored representation of the environment but the 11

environment itself. Consequently, in J.J. Gibson‟s framework, perception is conceptualized as 12

a direct epistemic relation between animal and environment. An individual is surrounded by 13

an array of stimulus information consisting of variants and invariants (cf. J.J. Gibson & E.J. 14

Gibson, 1955). In the control of action, individuals can learn to improve the accuracy of their 15

behavior if they detect the invariant information in the environment. Therefore, improving 16

one‟s epistemic relation entails a learning process whereby the performer begins to exploit 17

and couple their movements to the specifying information available in the environment (J.J. 18

Gibson & E.J. Gibson, 1955). From an ecological view, this process of perceptual learning is 19

referred to as the education of attention or attunement (E.J. Gibson & Pick, 2000; J.J. Gibson, 20

1966).1 Indeed, from this perspective, action supports the epistemic relation between the 21

performer and the environment as, for example, changes in a performer‟s physical or technical 22

capabilities can yield new affordances (Fajen et al., 2009). It follows that learning conditions 23

that restrict an athlete‟s actions within the immediate environment may impinge upon his or 24

1 Over the last decade, several ecological psychologists have argued that successful performance not only

requires the detection of invariant information but also an appropriate calibration (Jacobs & Michaels, 2007; van

Lier, van der Kamp, Savelsbergh 2011; Withagen & Michaels, 2005). That is, movements should be properly

scaled to the detected information. However, in this paper we limit ourselves to the process of attunement.


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her opportunities to develop a greater epistemic contact with the environment that they 1

perform within (Dicks et al., 2008). 2

Additional to the original perspective of the Gibsons, contemporary ecological 3

psychologists have made a distinction between specifying and non-specifying informational 4

variables (e.g., Jacobs, et al., 2001; Withagen & van der Kamp, 2010). Specifying variables 5

relate one-to-one to the to-be-perceived property of the environment and thus inform perfectly 6

about it. Non-specifying variables on the other hand correlate with the to-be-perceived 7

property but are not specific to it. Yet, some non-specifying variables will have a moderate or 8

high correlation with the property and thus have an adaptive value in the control of 9

movement. Other non-specifying variables may have a rather low correlation with the relevant 10

property, implying that it is highly unlikely that these variables will be useful in the guidance 11

of behavior. The fact that informational variables differ in their degree of usefulness means 12

that athletes can improve the accuracy of their perceptual-motor behavior by learning to 13

exploit the more useful information. These theoretical ideas hold important implications for 14

practitioners and scientists, to ensure that practice conditions are appropriately designed to 15

allow learners‟ to attune to information for the control of skilled movement, a point we will 16

return to in the discussion (see also Renshaw & Fairweather, 2000). 17

Over the last decade or so, several authors have developed this general ecological 18

theory of learning and tested it in different paradigms (for overviews see e.g., Fajen, 2005; 19

Jacobs & Michaels, 2007; Withagen & Chemero, 2009). For example, Withagen and 20

Michaels (2005) studied the process of attunement in the paradigm of length perception by 21

dynamic touch. In this paradigm, participants are required to perceive the length of hand-held, 22

unseen rods. The perceptual modality of dynamic touch is pivotal in numerous sports 23

including cricket, baseball, fencing, and all racket sports (Carello, Thuot, & Turvey, 2000). In 24

these sports, the primary function of the visual system is to control movement relative to an 25

opponent‟s movement and/or ball-flight. This implies that the length, orientation and/or 26


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sweet-spot of the bat, foil or racket is primarily perceived haptically. Withagen and Michaels 1

(2005) reported that in the pretest all but one participant relied on a non-specifying variable to 2

perceive the length of the rod. That is, one participant was capable of accurately identifying 3

the length of the unseen rods without any practice, while the other participants demonstrated a 4

range of performances, which were for the most part inaccurate. Following practice, some 5

participants learned to detect the variable that specifies (i.e., relates one-to-one to) rod length 6

after feedback. Interestingly, the one participant (Withagen & Michaels, 2005; Experiment 1, 7

Participant 5) who relied on the specifying variable in the pretest volunteered that she had 8

been a top national fencer and had vast experience of practicing with foils made of materials 9

that comprised variable densities. Consequently, the expert fencer was better at differentiating 10

the stimulus information in the environment than the novice participants (see also, Headrick, 11

Renshaw, Pinder, & Davids, 2012). Indeed, research demonstrates that perceptual expertise 12

can be partly explained in terms of the informational variables that are detected (for an 13

example in baseball see Gray, 2002; see also Jacobs et al., 2001; Huet, Jacobs, Camachon, 14

Missenard, Gray, & Montagne, 2011) 15

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The continuum of contact 17

To elucidate the between-participant variations in the accuracy of perception-action 18

and the changes therein during learning, Withagen (2004) developed the idea of a continuum 19

of epistemic contact. This idea was inspired by the concept of perception as “a keeping-in-20

touch with the world” (J.J. Gibson, 1979, p. 239; emphasis added). Withagen proposed that 21

keeping-in-touch with the world (i.e., maintaining an epistemic relation) can be best thought 22

of as a continuum of contact. During the control of movement, the degree of contact that an 23

animal has with the environment depends on the usefulness of the informational variable that 24

is exploited. The epistemic contact offered by a non-specifying variable is not as adaptive as 25

the contact offered to a performer who exploits a specifying variable, or a more useful non-26


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specifying variable. Importantly, the continuum perspective asserts that performers can still 1

adaptively perceive and act upon an environmental property after the exploitation of a non-2

specifying, but useful, variable (see also, Fajen, 2005). 3

Consider the penalty taker‟s kinematic information that a goalkeeper may attend to 4

during the penalty kick. If specifying information were available from the kinematics of a 5

penalty taker‟s action, it would implicate the 100% reliability of an informational variable that 6

specifies the penalty kick direction. Research (e.g., Diaz et al., 2012; Lees & Owens, 2011) 7

indicates that information from penalty taker start position and approach angle is largely 8

incongruent with kick direction and therefore provides a (comparatively) low level of 9

epistemic contact for a goalkeeper who exploits these sources of information. In contrast, 10

kinematic information offering a higher level of epistemic contact emerges following 11

initiation of the kicking action as a function of biomechanical constraints. Useful information 12

at specific body segments include placement of the non-kicking foot (~ 80% reliable), 13

orientation of the hips in the final portion of the kicking motion (83% reliable) and orientation 14

of the kicking foot at the moment of foot-ball contact (85% reliable) (see also Dicks, Button, 15

& Davids, 2010a for a further review). However, the informational variables that are most 16

useful, and thus allow the best epistemic contact, are distributed across the relative motion of 17

multiple kinematic locations (e.g., torso, arms, legs and feet), which are coordinated together 18

when performing a kicking action (Diaz et al., 2012; for a related finding in tennis, see Huys, 19

et al., 2008). 20

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Between-participant variability in perception-action 22

In his proposal of the continuum perspective, Withagen (2004) discussed the 23

plausibility that from an evolutionary perspective, performers may be expected to attend to 24

non-specifying variables even during instances that specifying variables are available for 25

exploitation. As there are numerous constraints on the evolutionary process (see e.g., 26


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Dawkins, 1982), Withagen proposed that it might be that particular specifying information is 1

not exploited because the perceptual system required for the detection of specifying 2

information is not available in the evolving population. Moreover, as argued by Withagen and 3

Chemero (2009), an evolutionary approach to perception also implies variation between the 4

members of the same species. Indeed, such variability is a prerequisite for the evolutionary 5

process. And although natural selection may reduce the amount of variation, it is unlikely to 6

eliminate all individual differences, especially for actions that are not crucial for survival and 7

reproduction. 8

There are two fundamental interrelated implications of the perspective of Withagen 9

and Chemero (2009) that we consider to be of relevance to the perceptual learning literature in 10

sport. First, variation by natural selection implies that people with equivalent levels of 11

experience are likely to vary in their perceptual capacities (e.g., Dicks, Davids, et al., 2010). 12

Second, during learning, the rate and capacity to improve perception-action accuracy will 13

vary between performers. Across all time-scales in learning, whether that be following a pre-14

test (e.g., Jacobs et al., 2001; Withagen & Michaels, 2005) or after extensive practice, one can 15

expect to observe divergences in the informational variables exploited by participants and 16

subsequent differences in performance accuracies (e.g., van der Kamp, Withagen, & de Wit, 17

2013; Withagen & van Wermeskerken, 2009). 18

Indirect support of the theoretical position of Withagen and Chemero (2009) in the 19

sport perceptual skill literature has revealed individual differences between skilled performers 20

(e.g., Singer et al., 1998). For example, it has been demonstrated that differences in the action 21

capabilities of experienced goalkeepers‟ underpin individual differences in perceptual skill 22

(Dicks, Davids, et al., 2010). Dicks and colleagues reported a significant correlation between 23

goalkeeper action capability (i.e., agility) and penalty kick movement time demonstrating that 24

the faster the goalkeeper, the later the goalkeeping action was likely to be initiated. Results 25

demonstrated that being able to move quickly and thus initiate a movement response later led 26


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to performance advantages in the penalty-kick situation. Note that for goalkeepers – as with 1

all competitors in fast-ball sports – successful performance is predicated on the pick-up of 2

information that supports the accurate timing of action, as well as the direction of action. 3

Slower goalkeepers moved earlier and therefore, the pick-up of information supporting the 4

direction of the diving action was based on less useful (potentially deceptive), early 5

information from the actions of the penalty taker (see also Navia, van der Kamp, & Ruiz, 6

2013). In sum, contemporary research findings conducted from the perspective of an 7

ecological approach have shown that participant‟s vary in the information they exploit for 8

perception and action (for an overview see Withagen & van der Kamp, 2010). In the 9

following section, we consider some of the implications of the described perspectives in 10

ecological psychology for future work in the sports perceptual learning literature. 11

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Future Directions 13

Learning to perceive and act 14

Following the theoretical perspective and supporting data presented above, we propose 15

the need to further consider the utilization of in situ interception practice conditions which 16

have the goal of training skillful adaptive behavior predicated on reciprocal perception and 17

action (Dicks, Button, et al., 2010b; van der Kamp et al., 2008). While advances in 18

methodological paradigms have enhanced understanding on perceptual expertise (e.g., Dicks, 19

Button, et al., 2010a; Mann et al., 2010), it remains that these experimental advances have not 20

yet been fully utilized to assess the suitability of perceptual training interventions. Although 21

attempts have been made to study the acquisition of perceptual skill using on-court conditions 22

that allow participants to practice under in situ interception conditions (e.g., Williams et al., 23

2004), such research has failed to measure the transfer of performance using in situ 24

interception pre, post, and retention tests. Therefore, in order to enhance understanding on 25

perceptual learning, it is of essence to further implement in situ training interventions. 26


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If in situ training paradigms are to be utilized to their full, research is needed to 1

ascertain what constitutes the most useful information for the control of movement during 2

sport tasks. Unfortunately, current understanding on the informational variables available for 3

performance have most typically been derived from video simulation studies (e.g., Smeeton et 4

al., 2005; Williams, Ward et al., 2002) or biomechanical analyses whereby players have 5

executed shots in the absence of an opponent (Diaz et al., 2012; Huys et al., 2008). In the case 6

of the latter, an important first-step for future research would be to examine whether the 7

movement kinematics of a sportsperson in the absence of an opponent equates to the 8

movements exhibited during interpersonal sport situations (e.g., Pinder, et al., 2011). In the 9

case of gaze behaviors, evidence indicates that the perceptual strategies exhibited by 10

sportspeople in the absence of an interceptive action do not equate to the locations of 11

information pick-up during in situ interception conditions (Dicks, Button et al., 2010b). 12

Therefore, an important research topic entails the need to further examine the patterns of gaze 13

utilized by experts during in situ interception conditions (e.g., Panchuk & Vickers, 2006). In 14

this respect, rather than continued over-reliance on predictive judgment paradigms, 15

technological advances – including portable gaze measurement systems – permit the 16

opportunity to make exciting progress in this area of investigation, whereby researchers can 17

study the mechanisms underlying expertise predicated on reciprocal perception and action. 18

One of the few perceptual learning studies to consider improvements in reciprocal 19

perception and action in sport is the basketball jump shooting study of Oudejans, Koedijker, 20

Bleijendaal and Bakker (2005). Oudejans and colleagues provided six junior national 21

basketball players eight weeks of perceptual training in which the practice environment was 22

constrained in such a way (shooting from behind a screen) that they only had vision during 23

the final ~350 ms before ball release. This manipulation forced the participants to detect and 24

use the most useful information in the very short time window until ball release, emphasizing 25

the use of the latest possible update of the relative target position (see Oudejans, van den 26


19

Langenberg, & Hutter, 2002). In contrast to four control participants from the same team, the 1

participants that undertook perceptual training improved their shooting performance in games. 2

This study shows that in situ perceptual training interventions directed at attunement to more 3

useful information can lead to in situ performance improvements. Indeed, recent in situ 4

studies have followed the lead of Oudejans et al. and further examined the acquisition of 5

visually controlled aiming (e.g., Causer, Holmes, & Williams, 2011; Wood & Wilson, 2011). 6

It will no doubt be most interesting when researchers aim to replicate these promising 7

methodological advances to the broader domain of perceptual skill topics in sport. 8

9

Between-participant variation in perception-action and practice 10

The theoretical position of Withagen and Chemero (2009) suggests that the current 11

research practice of training performers on the basis of purported optimal perceptual strategies 12

may be misguided (e.g., Hagemann et al., 2006). As considered during our discussion of the 13

continuum of contact (Withagen, 2004), the accuracy of visually controlled behavior is 14

inherently tied to the usefulness of the information exploited by a performer. Therefore, 15

performance can be improved if performers learn to exploit the more useful or invariant 16

information in the environment. However, attunement to this information may not be so 17

simple for all performers. For example, given that behavior is action-scaled (e.g., Dicks, 18

Davids et al., 2010), performers can be expected to exploit different information as 19

constrained by variation in their action capabilities. The interesting challenge therefore is to 20

consider how to structure practice when it is highly plausible that all performers will not: i) 21

attune to the same information at the start of training; and ii) learn to attune to the same 22

information during/following training. 23

A worthwhile step may be to consider contemporary perspectives in the movement 24

coordination literature. Historically, there has been much debate on the role of variability in 25

coordination, with particular consideration of whether variation is facilitative or debilitative to 26


20

performance (see Davids, Bennett, & Newell, 2006). In the case of perceptual skill, there is 1

increasing consensus that movement variability plays an essential role in sport expertise. For 2

example, Schorer and colleagues (Schorer, Fath, Baker, & Jaitner, 2007) reported that the 3

movement variability of handball players‟ penalty throwing actions increased across skill-4

levels. The importance of movement variability has been considered in the differential 5

learning perspective, which emphasizes the acquisition of functionally different coordination 6

patterns, rather than the acquisition of a priori defined optimal coordination patterns (see 7

Frank, Michelbrink, Beckmann, & Schöllhorn, 2008). The aim of differential learning is to 8

support a learner in finding his or her functionally successful individual coordination patterns. 9

To facilitate this process, learners practice within noisy performance environments that vary 10

from exercise-to-exercise (trial-to-trial). 11

There are analogues between the differential learning viewpoint and the earlier 12

ecological learning perspective of the Gibsons (1955). Specifically, recent advances in 13

ecologically motivated perceptual learning studies indicate that emphasizing variability in 14

practice conditions appears to be most effective in helping learners to detect the invariant 15

information and thus increase the accuracy of their perceptual skill (see e.g., Huet et al., 2011; 16

Jacobs et al., 2001). In line with this evidence, perceptual learning studies may benefit a great 17

deal from practice conditions that emphasize variability of the opponent‟s movement (and 18

ball-flight). Rather than the current common procedure in video training (e.g., Abernethy et 19

al., 2012) in which participants view a small number of expert players executing a small 20

number of perfect trials, we propose that it will be most interesting to examine whether 21

novices benefit from learning against a large number of different players – of different ability 22

levels – while they execute a number of different shots to different locations (see, Dicks, 23

Uehara, & Lima, 2011). During variable perceptual training, learners will be exposed to a 24

manifold of information that will vary greatly in its usefulness for accurate perception-action. 25

This increase in variation of the practice environment may expedite expertise by guiding 26


21

learners toward the detection of invariant information. Moreover, rather than placing 1

emphasis on an a priori perceptual strategy, performers will have the opportunity to learn to 2

exploit the information that is most useful for them in the control of their own action. 3

The advocated approach is in keeping with recent understanding on the relationship 4

between play, practice and the (nonlinear) development of expertise, with evidence indicating 5

that expert players will have learnt against a number of different players in varying 6

environmental contexts en route to achieving elite performance levels (Ford et al., 2009 7

Phillips, Davids, Renshaw, & Portus, 2010). While such research offers increased 8

understanding on the practice activities of performers who have attained elite performance 9

levels across long time-scales (i.e., years), comparatively little is known about the perceptual 10

learning trajectories of performers over short and intermediate time-scales (i.e., hours, days 11

and months). To this end, it is possible that relatively short durations of perceptual training 12

may be of most benefit to skilled players (Hopwood et al., 2011). Expertise levels aside, it 13

remains of essence to ascertain the time-frame required for these respective sub-groups to 14

improve the accuracy of their in situ interception performance within a particular fast-ball 15

sport setting in tandem with measurement of the underlying mechanisms of such changes 16

including gaze behaviors (e.g., Causer et al., 2011). 17

18

Summary and conclusion 19

In the current article, we have returned to a central question in Starkes and Lindley‟s 20

1994 publication and evaluated the research evidence on the topic of perceptual training via 21

video simulations. Despite 20 years of research in this area, a conclusive answer is still not 22

forthcoming. Perhaps most importantly, the question of whether and to what extent video-23

based perceptual training actually transfers to on-field performance still remains largely 24

unanswered. Recent evidence indicates that highly-skilled players may benefit from video-25

training when it is used to supplement normal coaching practices (Hopwood et al., 2011). In 26


22

order to build on such evidence and provide more of a conclusive answer, it remains that far 1

more research efforts are needed to assess the suitability of video training by measuring 2

performance using appropriate transfer tests that measure in situ interception. Although some 3

advances have been made in experimental paradigms aimed at studying perceptual skill 4

(Dicks, Button et al., 2010a; Mann et al., 2010), arguably, the same cannot be said for 5

research when evaluating the effectiveness of video-based training. 6

Further to a review of current evidence in the video training literature, we have 7

considered an ecological approach to perceptual learning alongside recent empirical evidence 8

which indicates that perceptual expertise is most pronounced in situations that allow 9

participants to perceive and act against an opponent in real-time (Travassos et al., 2013). 10

Reflection on such empirical evidence would suggest that one can at least suspect that video 11

simulations may not be the best way to train perceptual expertise. A central implication is that 12

training interventions should permit learners to produce requisite actions to improve their 13

perceptual skill. Moreover, following evidence demonstrating variability in what 14

informational variables are used for the control of movement, we have advocated the 15

importance of appreciating potential between-participant variation in perception-action 16

through the use of variable practice environments. While we believe that the theoretical 17

approach advocated here will be of benefit to researchers interested in this scientific domain, 18

much of the ideas discussed still await experimental support within the sports literature. In 19

this regard, we believe that research – either aimed at proving or arguing against our 20

framework – will greatly benefit current scientific understanding in this field of research. 21

With the current advancements in on the field measurement of gaze and performance we are 22

optimistic that it will not take another 20 years before we have a much clearer answer to the 23

question of whether we can hasten expertise by video simulations. 24

25


23

Acknowledgments 1

The contributions from the lead author were made while he was supported by a grant (number 2

446-10-028) from the Netherlands Organisation for Scientific Research (NWO) and the Marie 3

Curie Cofund Action. 4

5


24

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