End-point focus manipulations to determine what information is used during observational learning

Acta Psychologica 126 (2007) 120–137 www.elsevier.com/locate/actpsy

End-point focus manipulations to determine what information is used during observational learning Spencer J. Hayes a

a,*

, Nicola J. Hodges b, Raoul Huys c, A. Mark Williams a

Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L3 2ET, UK b School of Human Kinetics, University of British Columbia, Canada c Faculte´ des Sciences du Sport, CNRS and Universite´ de la Me´diterrane´e, France Received 21 December 2005; received in revised form 13 November 2006; accepted 16 November 2006 Available online 3 January 2007

Abstract We required two groups of participants to observe an end-point model (ENDPT) while another two groups viewed a full-body, point-light model (FULL) to determine the role of relative motion information in acquisition of a multi-limb, whole-body action. One ENDPT and one FULL group also bowled a ball. Following retention, all groups observed the FULL model. The participants’ movements were compared to the model and outcome attainment was quantified. There was no difference in shoulder–elbow coordination between groups in acquisition or retention. The FULL groups replicated hip–knee coordination more accurately than did ENDPT groups in early acquisition only, with no significant differences in late acquisition or retention. Both bowling groups became more accurate at the task across acquisition, but the ENDPT group was more accurate and consistent in retention. Providing intra-limb relative motion in re-acquisition did not improve coordination for the ENDPT groups, but it did facilitate movement control (peak wrist velocity) and outcome attainment (target accuracy). The acquisition of coordination during observational learning is not only a result of copying relative motion information, but also involves copying of end-point trajectory information from the primary effector.  2006 Elsevier B.V. All rights reserved. Keywords: Motor learning; Pre-practice information; Imitation; Modelling

*

Corresponding author. Tel.: +44 151 231 4313; fax: +44 151 231 4353. E-mail address: [email protected] (S.J. Hayes).

0001-6918/$ - see front matter  2006 Elsevier B.V. All rights reserved. doi:10.1016/j.actpsy.2006.11.003

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

121

1. Introduction In early skill acquisition the learner is challenged with the task of reducing the degrees of freedom into a configuration that satisfies a desired movement pattern and/or an external goal (see Bernstein, 1967). The provision of pre-practice information specifying the to-belearned movement is a common technique for facilitating skill acquisition. A demonstration may be used to convey this information and through observational learning a cognitive representation of the action is formed and used for action reproduction and learning (Bandura, 1986). Although Bandura did not specify which features of the model help to form this representation, several researchers have subsequently attempted to identify the nature of the information conveyed within a demonstration (see Newell, 1985; Scully & Newell, 1985; Whiting, Bijlard, & Brinker, 1987). In particular, Scully and Newell (1985) proposed the ‘visual perception perspective’ to explain observational learning effects. The visual perception perspective (VPP) is based on perceptual psychology literature (e.g., Cutting & Proffitt, 1982; Johansson, 1973), where relative motion information (i.e., the motion of individual elements of a configuration relative to each other) has been identified as the invariant underlying the perception of an action. The VPP draws heavily on Newell’s (1985) framework of coordination, control, and skill (see also Kugler, Kelso, & Turvey, 1980; Kugler, Kelso, & Turvey, 1982). For the acquisition of a new movement (i.e., coordination), Newell (1985), following Bernstein (1967), suggested that the learner must coordinate the free variables of the motor system into a functional behavioural unit. He proposed that the relative motions of the to-be-learned action are significant in constraining the desired behavioural pattern via the combined effect of observation and physical practice (Newell, 1985; Scully & Newell, 1985). The importance of relative motion information for observational learning has typically been examined by comparing the learning effects apparent after observing point-light and video models, respectively. The proposal is that learning is facilitated when observing a point-light image of the action because relative motion information is made more salient than in a conventional film display and because all potentially non-essential (i.e., background) information is removed (e.g., Al-Abood, Davids, & Bennett, 2001; Horn, Williams, & Scott, 2002; Horn, Williams, Scott, & Hodges, 2005; Scully & Carnegie, 1998). However, these conclusions have been based on only indirect manipulations of relative motion information. Thus far, researchers have shown that the ability to pick-up the critical features underpinning the observational learning process is dependent on certain task constraints. In a soccer kicking experiment, where learners were instructed to imitate a model’s kicking action to propel a ball to a target, Horn et al. (2002) failed to observe differences in hip–knee coordination between the demonstration groups (i.e., point-light and video models) and a no-demonstration control group. The requirement to kick a ball, coupled with outcome feedback, influenced the learners’ coordination pattern more than the model’s action. In a follow-up experiment, Horn et al. (2005) removed outcome feedback of the ball’s trajectory and landing position and showed that the demonstration groups’ lowerbody intra-limb coordination patterns were more similar to the model than that of the no-demonstration group. They concluded that a full-body demonstration, and by inference relative motion, is a primary constraining source of information for acquiring intra-limb coordination when the only task goal is to learn a new movement pattern (see also Al-Abood et al., 2001).

122

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

In the aforementioned studies, the authors concluded that relative motion was imitated if learners’ relative motion patterns were more similar to a criterion model than those of control participants (e.g., Al-Abood et al., 2001; Horn et al., 2005; Scully & Carnegie, 1998). However, relative motion was not directly manipulated through, for example, the use of occlusion or perturbation methods. Therefore, it cannot be concluded that relative motion was used to constrain the learners’ movement pattern because another source of information may have been responsible for the observed effects. There is evidence from other studies involving the recording of point-of-gaze data to show that observers fixate on end-point features of a movement, such as the hand, when observing a model with the intention of imitating a whole arm movement (Mataric & Pomplun, 1998). Since there are many types of information available within a whole-body motion display (ranging from whole-body relative motion to absolute motion of a single joint), it is important to examine whether observers locate and use information around the end-point of an action, or a particular effector, to constrain their executed movement pattern. In a further experiment, Hodges, Hayes, Breslin, and Williams (2005) attempted to directly manipulate access to relative motion information during the replication of an unusual soccer kicking action. Movement reproduction was examined across two phases in the absence of any task constraints (i.e., imitating the model’s movement was the only goal). Three independent groups either observed a point-light model of the lower leg (i.e., intralimb relative motion), the foot (ankle and toe) or the toe (i.e., no relative motion). The toe group, who did not have access to relative motion information, reproduced an action that more closely resembled the criterion model’s intra-limb coordination than did the foot and leg groups. In a control condition, where observers viewed and imitated the criterion fullbody model, the resulting coordination profiles did not become more like the model indicating that end-point information was sufficient for constraining intra-limb coordination. Although these findings are contrary to Scully and Newell’s (1985) hypothesis, the main conclusions may still be interpreted from a visual perception perspective. For example, Mather, Radford, and West (1992) showed that the trajectory of an end-effector or joint is critical for differentiating various motor actions (as determined through methods of occlusion). It has therefore been suggested that during imitation and movement control, the trajectory of this feature ensures an accurate execution and is an important variable to attend to during imitation (see also Mataric & Pomplun, 1998; Morasso, 1981). To be able to infer whole-body actions based on only minimal information pertaining to the location of an end-point or end-effector requires a strong coupling between the consequences of an action and the action that brings about these effects. Based on the ideas of Bernstein (1967), see also Bernstein (1996); Latash (1993, 1996) has proposed that actions are planned and controlled in terms of their end-trajectories or what has been termed the ‘working point’. This could be the trajectory of the hand or pen in writing or the trajectory of a displaced object, such as a ball, in throwing. Moreover, anticipation of a distal action effect has been shown to facilitate subsequent initiation and execution of the action associated with this end-effect (see Hommel, Mu¨sseler, Aschersleben, & Prinz, 2001; Kunde, 2003; Kunde, Hoffman, & Zellmann, 2002). The findings reported by Hodges et al. (2005) have been partially replicated amongst observers learning to bowl a cricket ball (a specialized action where the arms move alternately in a vertical motion during the backward and forward swing). Although observation of the wrist trajectory was not sufficient to bring about an upper limb coordination pattern similar to the model, a full-body and an intra-limb group, who only viewed the

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

123

bowling arm, did not differ from each other in acquisition or retention on various parameters of coordination and control (see Breslin, Hodges, Williams, Curran, & Kremer, 2005, in press). The trajectory of the end-effector, rather than only the end-point of the action, was the primary constraining source of information. The study by Hodges et al. (2005) also included a third phase where an additional task constraint was added so that participants were required to kick a ball to land on a target area. In this phase, across groups, the observers’ knee–ankle intra-limb coordination became significantly more like the model across groups. The task constraints were more powerful in changing coordination than observation of relative motion information typically available in an unedited model display (see also Hayes, Hodges, Scott, Horn, & Williams, in press). The latter findings question the importance of demonstrations and in particular the importance of relative motion information for motor reproduction. The motor skill examined by Hodges et al. (2005) was a relatively simple kicking action, where the (single) endpoint trajectory of the kicking foot sufficiently constrained the accurate replication of the leg movement. However, Breslin, Hodges, Williams, Curran, and Kramer, in press found that the whole end-effector was necessary for replication of whole-body coordination, although in this task participants were additionally required to bowl a ball to hit a target. In the present paper we seek to distinguish the role of task constraints from demonstrations and therefore extend and validate the findings reported above. We examine the acquisition of a multi-limb, crown-green bowling action where both the nature of the information contained within a display is manipulated as well as the requirement to bowl a ball to achieve a target. Our aim is to directly compare action-reproduction with goaldirected action reproduction (see Bekkering, Wohlschla¨ger, & Gattis, 2000; Hodges et al., 2005; Horn et al., 2002). The effectiveness of two model types (i.e., end-point versus full-body) will be examined under two task conditions. In the first condition, participants will observe and imitate an end-point or a full-body model. No contextual cues or information will be given about the desired action. By comparing an end-point model that has intra-limb relative motion information removed, against a full-body relative motion model, it is possible to examine whether relative motion is important for acquiring intra-limb coordination. Scully and Newell (1985) proposed that relative motion information constrains the acquisition of coordination in early learning. If this is the case, the end-point groups should be at a disadvantage in the initial acquisition phase and therefore be less accurate at imitating the desired coordination pattern in comparison to full-body groups. If participants are not using relative motion information, there should be no difference between the full-body and end-point group’s intra-limb coordination patterns. In the second condition, we examine the effects of different model types under both goal- and non-goal directed task conditions. Therefore, half of the participants will also be required to bowl a ball to an external target. Under these goal constraints we might expect the model type to have less of an effect on the imitated intra-limb coordination pattern of the learners in comparison to their effects on participants who are only required to imitate the action. Under goal-directed conditions it has been shown that learners focus more on achieving the task goal and changing their movements based on feedback about outcome success than imitating the model’s movement (see Horn et al., 2002). In the second condition we will also quantify the participants’ bowling performance in order to examine whether target accuracy is facilitated through access to different model types. Although researchers have examined performance on outcome-based tasks (e.g., Breslin et al., 2005; Hodges et al., 2005) it is unclear whether outcome success is facil-

124

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

itated through access to different model types due to measurement limitations. In both these experiments only a discrete hit or miss measure was used to quantify performance. It is unclear whether a lack of difference across groups was a function of the model manipulations or the insensitivity of the measure. Therefore, in the present experiment we sought to examine bowling performance through measures of absolute error (accuracy) and variable error (consistency). In terms of our predictions, there is reason to suspect that making the movement end-point salient will facilitate outcome attainment. Hayes, Hodges, Scott, Horn, and Williams (2006) found that participants who were more accurate at hitting an external target demonstrated a similar wrist velocity profile to a criterion model. If the end-point display helps to focus the learner’s attention onto the dynamics of the movement, in comparison to a full-body display, we expect participants who observe an endpoint model to be more accurate than those who observe a full-body model. To extend our understanding of relative motion information during observational learning and across skill acquisition, a re-acquisition phase will be included. Following the retention phase all participants will undertake a further practice period. Irrespective of the earlier model groups, in this phase, all the participants will observe a full-body relative motion model. Although Scully and Newell (1985) proposed that relative motion is critical in early skill acquisition they suggested that it is not important in later practice (cf. Hayes et al., 2006). If this is the case, the addition of relative motion information in the reacquisition phase should have no effect on movement kinematics for any of the groups. 2. Method 2.1. Participants Thirty-two participants (M age = 22.1 yr; SD = 2.50 yr; range 18–30 yr) were randomly assigned to one of the four groups (of eight participants each). Participants either watched a full-body point-light model displaying a side-on-view of a crown-green bowling action (FULL) or a reduced point-light model displaying only the wrist marker on the right bowling arm and the left and right toe markers (ENDPT). These two groups were further subdivided such that they either did (BALL) or did not (No-BALL) bowl a ball to a target throughout testing. All participants were right handed and reported normal or corrected to normal vision. None of the participants had experience with a crown-green bowling action as ascertained before testing. The experiment was conducted in accordance with ethical guidelines of Liverpool John Moores University. Participants provided informed consent and were free to withdraw from the experiment at any time. 2.2. Apparatus Movement kinematics were collected using a VHS video camera (Panasonic M-40, Tokyo, Japan) and six infrared motion analysis cameras (Pro-Reflex; Qualisys, Gothenburg, Sweden) positioned on either side of the participant’s body (both sagittal planes) sampling at 50 and 240 Hz respectively. The demonstrations were front projected onto a 3.0 m · 3.5 m screen (Cinefold, USA) using a projector (Sharp XG-NV2E, Tokyo, Japan) and VCR (Panasonic NV-HS 820, Tokyo, Japan). For the model and BALL groups, a plastic ball (Regent, SOFFS: model 98200; circumference = 43 cm; mass = 0.15 kg) was bowled to a 6 m target line.

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

125

2.3. Task, design, and test-film construction Participants were required to observe and imitate a crown-green bowling action. This action which shows similarities to a ‘ten-pin bowling’ action was selected because it was considered to be a relatively novel, multi-limb action that has an associated outcome goal as well as being an action that can be acquired in a relatively short period of time under laboratory conditions (see Hayes et al., in press). A 26-year-old male acted as the model and was filmed from the sagittal plane while executing a crown-green bowling action. The filming took place after approximately 100 practice trials. The model was positioned at a start line and rolled a ball along a carpeted surface to a target line positioned 6 m from the start line. Once a consistent level of performance was achieved, a successful bowl (i.e., one where the ball stopped on the target line) was chosen to represent the kinematic profile adopted by the model to achieve task success. The spatio-temporal positions of 15 reflective markers placed on the model’s major joint centres formed a point-light display when viewed through a software-viewing program (QTM-Manager, Qualisys, Gothenburg, Sweden). A point-light display of the model’s bowling action was produced using the QTM software package. The point-light model was edited to create two demonstration tapes (from the same bowling action) where either all fifteen markers (FULL) or only three markers relating to the right wrist and the right and left toe (ENDPT) were presented. Participants viewed their respective demonstration from the sagittal plane. We presented the right and left toe within the demonstration so that the participant had access to the whole outline of the bowling action (i.e., left and right leg and the wrist), but did not have access to intra-limb relative motion pertaining to the three effectors. The corresponding data points were used as comparative data to judge how closely participants approximated the model. 2.4. Procedure Before experimental testing, reflective markers were placed on the right and left side of each participant’s distal head of the 5th metatarsal (toe), the lateral malleolus (ankle), the lateral condyle of the femur (knee), the greater trochanter (hip), the acromion process (shoulder), the lateral epicondyle (elbow), and the styloid process of radius (wrist). In order to familiarize participants with the point-light stimuli, observers viewed a point-light training video showing a model executing a number of everyday actions, not related to the bowling action, in both point-light and video format respectively. This process was expected to reduce any negative consequences associated with going from video to point-light format (see also Hayes et al., in press). Test sessions were conducted individually and lasted approximately 50 min. Before each trial, the participant stood behind a start line that was positioned to enable easy viewing of the demonstration and capture of movement kinematics. The task during acquisition1 was to observe a point-light model and reproduce (imitate) a whole-body action associated with the model’s action. The learners were not informed 1

It was not practical to collect pre-test data to initially quantify coordination because the experiment was designed to understand how the information contained in a demonstration impacts on the acquisition of coordination. It was reasoned that pre-test instructions directed at executing a ‘‘crown-green bowling action’’ would bias the observation phase of the experiment leading to potential confounds in the reproduction process (especially for the two non-bowling groups). We randomly allocated learners to the experimental groups to help control for any potentially confounding individual differences.

126

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

about the nature of the model’s action, such that we were more able to assess how the perceived information affected the imitated movement pattern. Participants received 20 acquisition trials where a demonstration was shown twice on trial one and then once before each of the remaining trials. The FULL groups observed the full-body model and ENDPT groups observed an end-point model displaying only three joint markers. The ENDPT groups were informed that the three markers corresponded to the model’s left and right toe and right wrist viewed from the side (i.e., sagittally). Participants were instructed to observe the model carefully and when instructed to imitate the model’s action accurately. The BALL groups were informed that the model’s action led to the ball stopping on the 6 m target line, whereas the No-BALL groups did not receive information regarding bowling performance or the target line. Before imitating the action only the BALL groups received a ball and were instructed to imitate the model’s action in order to stop the ball on the target line. They were not given any explicit instruction to ‘‘roll’’ or ‘‘bowl’’ the ball. The BALL groups had access to the ball’s trajectory and final position in relation to the target line throughout acquisition (and re-acquisition). All groups completed a 5-trial retention test 24 h later, where demonstrations were withheld. As with acquisition, the BALL groups received a ball and the same instruction to stop the ball on the target line. Following retention, participants conducted a 10-trial re-acquisition period where they observed the full-body, point-light model. The demonstration was viewed twice on the first trial and once on the remaining trials. The BALL groups were again instructed to stop the ball on the target line. 2.5. Dependent measures and statistical analysis 2.5.1. Kinematics In order to quantify the similarity of the learners’ imitated movement in comparison to the model’s movement, we calculated a measure of intralimb coordination called NoRMD (see Horn et al., 2005). This measure is a modified version of the normalized root mean squared error (NoRMS) proposed by Sidaway, Heise, and Schoenfelder-Zhodi (1995). A root mean square error score is calculated on the basis of the disparity of each trial from the model’s criterion trace (instead of the mean trace as used by Sidaway et al., 1995). This score is then normalized for the number of trials in the analysis (three trials in the present experiment) and its excursion. Excursion is normalized because a larger movement pattern may exhibit more absolute variability than does a similar, smaller pattern. For the calculation of NoRM-D, Horn et al. (2005) used a method recommended by Mullineaux, Bartlett, and Bennett (2001) in which excursion reflects the range of motion for angles in a coordination profile (e.g., shoulder–elbow coordination). This NoRM-D procedure provides an index of similarity to the model, with a lower NoRM-D value representing a closer approximation of the model’s movement (for further information regarding the validity of these values in inferring closeness of approximation to a model, see Hodges et al., 2005; Horn et al., 2005). Since the predominant aspect of the bowling movement (i.e., flexion extension of the bowling arm and right lower limb) occurred in a uni-planar direction on the right hand side of the body, we selected the learner’s right hip–knee and right shoulder–elbow joint angle configurations as kinematic parameters to compare relative motion. These configurations have been shown to be susceptible to modification following practice and demonstration manipulations in the past (Hayes et al., 2006, in press). Before quantification, the

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

127

start and end-points of the arm swing and right leg movement were standardized. This standardization allowed for comparisons across participants, trials, and with the model. The start and end-points were chosen as the initiation of shoulder extension, in preparation for the start of the arm swing phase of the action, and peak shoulder flexion in the follow-through element of the swing respectively. The resulting data were smoothed with a recursive 4th order Butterworth filter with a cut-off frequency of 7 Hz and re-sampled to 100 data points. During bowling, the projectile nature of the ball is governed primarily by the right arm (Dupuy, Mottet, & Ripoll, 2000; Feynman, Leighton, & Sands, 1965). We examined peak wrist velocity and calculated an absolute difference score in reference to the model. As with the NoRM-D analysis, a lower score would reflect a closer approximation to the model. For acquisition, all kinematic data were analyzed based on values computed from the first three (ACQ 1, t1–3), middle three (ACQ 2, t9–11), and last three (ACQ 3, t18–20) trials of acquisition. The resulting values were analyzed in a 2 Model (FULL; ENDPT) · 2 Task condition (BALL; No-BALL) · 3 Block (ACQ 1, 2, 3) mixed design ANOVA with repeated measures on the last factor. In retention, data from the first three trials were analyzed in a 2 Model (FULL; ENDPT) · 2 Task condition (BALL; No-BALL) factorial ANOVA. Finally, the re-acquisition data was analyzed in a 2 Model (FULL; ENDPT) · 2 Task condition (BALL; No-BALL) · 3 Block (ACQ3; RE-ACQ 1; RE-ACQ 2) mixed design ANOVA, where the last three trials of acquisition were compared to the first and last three trials of re-acquisition. 2.5.2. Outcome error To determine whether the amount of information provided within the two demonstrations affected outcome success, absolute (AE) and variable error (VE) were calculated for the two BALL groups. Outcome success was measured in terms of distance in centimetres from the target. These data were analyzed using a 2 Model (FULL, ENDPT) · 3 Block (ACQ 1, 2, 3) mixed design ANOVA with repeated measures on the last factor. In retention, the FULL and ENDPT groups were compared using an independent t-test. The reacquisition data was analyzed in a 2 Model (FULL; ENDPT) · 3 Block (ACQ3; RE-ACQ 1; RE-ACQ 2) mixed design ANOVA. For all analyses a Greenhouse–Geisser correction was applied when violations to sphericity were observed. Partial-eta squared ðg2p Þ values are reported for all significant effects (Cohen’s d for the t-test results). Comparisons of interest involving more than two means were examined using Tukey HSD procedure (significance was set at p < .05). 3. Results 3.1. Shoulder–elbow coordination In Fig. 1 the shoulder–elbow NoRM-D scores as a function of acquisition, retention, and re-acquisition test blocks for the No-BALL (A) and BALL (B) groups are presented. There was no significant difference between the ENDPT and FULL groups for shoulder– elbow coordination in acquisition, F(1, 28) = 2.65, p = .12, g2p ¼ :09. The FULL groups did not show a movement profile which more closely approximated the model than did the ENDPT groups. There was a tendency for the ENDPT groups to perform more like the model (M = 24.2) than the FULL groups (M = 28.2). The angle–angle plots for shoul-

128

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

35

Full Body ENDPT

NoRM-D Score

30

25

20

15 ACQ1

ACQ2

ACQ3

RET

RE-ACQ1

RE-ACQ2

Block 35 Full Body ENDPT

NoRM-D Score

30

25

20

15 ACQ1

ACQ2

ACQ3

RETR

E-ACQ1

RE-ACQ2

Block Fig. 1. Mean NoRM-D (standard error bars) scores for shoulder–elbow coordination across all test blocks (ACQ = acquisition, RET = retention and RE-ACQ = re-acquisition) as a function of display for the No-BALL (A) and BALL (B) groups.

der–elbow coordination as a function of acquisition, retention, and re-acquisition test blocks for the No-BALL (A) and BALL (B) groups are presented in Fig. 2. The main effect for task condition (i.e., bowling requirements), acquisition block, and any interaction concerning these factors were nonsignificant, all F’s < 1. In order to examine whether participants changed their behaviour early in acquisition as a result of watching the model, an additional analysis was conducted comparing only the first three trials of acquisition. A significant trial effect was observed, F(2, 56) = 46.08, p < .01, g2p ¼ :62. This effect did not interact with any of the group factors. After being shown the model, and irrespective of whether participants were required to bowl a ball or just copy the model,

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137 Shoulder

Shoulder Elbow

180

ACQ1

Elbow

90°

180°

Elbow Angle (deg)

Hip

Wrist 180

Shoulder Angle (deg)

ACQ2

180

170

170

170

160

160

160

150

150

150

140

140

140

130

130

130

120

120 10 20 30 40 50 60 70 80 90 100 110

10 20 30 40 50 60 70 80 90 100 110 180

RET

180

129

RE-ACQ1

ACQ3

120 10 20 30 40 50 60 70 80 90 100 110 180

RE-ACQ2

170

170

170

160

160

160

150

150

150

140

140

140

130

130

130

120 10 20 30 40 50 60 70 80 90 100 110

120 10 20 30 40 50 60 70 80 90 100 110

120 10 20 30 40 50 60 70 80 90 100 110

Shoulder Elbow Wrist 180 170

ACQ1

160 150 140 130 120 10 20 30 40 50 60 70 80 90 100 110 180

RET

180

Shoulder 180 °

Elbow 90 ° Elbow Angle (deg)

Hip

Shoulder Angle (deg)

ACQ2

180

170 160

170

150

150

140 130

140

120 10 20 30 40 50 60 70 80 90 100 110

120

180

180

160

130

RE-ACQ1

10 20 30 40 50 60 70 80 90 100 110

170

170

170

160

160

160

150

150

140

150 140

130

130

130

120 10 20 30 40 50 60 70 80 90 100 110

ACQ3

RE-ACQ2

140

120

120

10 20 30 40 50 60 70 80 90 100 110

10 20 30 40 50 60 70 80 90 100 110

Fig. 2. Shoulder–elbow angle–angle plots for (A) the two No-Ball groups and the model and (B) the two BALL groups and the model across all test blocks in acquisition (ACQ 1, 2 and 3), retention (RET) and re-acquisition (RE-ACQ 1 and 2). The FULL groups are designated by the light grey trace, the ENDPT groups by the dark grey trace and the model by the black trace. The open squares designate the start of the movement and filled squares the end of the movement.

the participants in both conditions adapted their movements to become more like the model; ENDPT (t1 = 30.40; t2 = 23.93; t3 = 20.63) and FULL (t1 = 34.15; t2 = 28.40; t3 = 25.27). No further differences were observed as a function of group in retention or re-acquisition.

130

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

3.2. Hip–knee coordination Fig. 3 shows the lower-body, hip–knee NoRM-D scores as a function of acquisition, retention, and re-acquisition for the No-BALL (A) and BALL (B) groups. The main effects for model, F(1, 28) = 3.65, p = .06, g2p ¼ :11, and task conditions, F(1, 28) = 3.80, p = .06, g2p ¼ :12, approached conventional levels of significance. Generally, the FULL groups performed more like the model than did the ENDPT groups and the BALL groups were more accurate than the No-BALL groups. The Model · Block interaction was signif-

60

Full Body ENDPT

55

NoRM-D Score

50 45 40 35 30 25 20 ACQ1

ACQ2

ACQ3

RET

RE-ACQ1

RE-ACQ2

Block 60 55

Full Body ENDPT

No RM-D Score

50 45 40 35 30 25 20 ACQ1

ACQ2

ACQ3

RET

RE-ACQ1 RE-ACQ2

Block Fig. 3. Mean NoRM-D (standard error bars) scores for hip–knee coordination across all test blocks (ACQ = acquisition, RET = retention and RE-ACQ = re-acquisition) as a function of display for the No-BALL (A) and BALL (B) groups.

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

131

icant, F(2, 56) = 3.39, p < .05, g2p ¼ :11. Participants who observed the FULL model were significantly more accurate at imitating the model’s hip–knee coordination profile during the first acquisition block only, p < .05. No other significant effects were observed. As with shoulder–elbow coordination, we examined any change in hip–knee coordination over the first three trials of acquisition. We observed the main effects for model, F(1, 28) = 10.08, p < .05, g2p ¼ :26, and task conditions, F(1, 28) = 4.63, p < .05, g2p ¼ :14. The FULL groups performed more like the model than did the ENDPT groups and the BALL groups were more accurate than the No-BALL groups across the first three trials of acquisition. The main effect of trial was significant, F(2, 56) = 3.88, p < .05, g2p ¼ :12, and the Trial · Model interaction approached a conventional level of significance, F(2, 56) = 2.81, p = .06, g2p ¼ :09. In contrast to that observed for the ENDPT group (t1 = 46.01; t2 = 42.93; t3 = 44.64), the FULL body group’s hip–knee pattern became more like the model as a function of acquistion trial (t1 = 36.26; t2 = 32.60; t3 = 25.61). In retention, the model and Model · Task condition interactions were not significant. Although there was a tendency for participants who bowled a ball to retain the model’s hip–knee coordination profile more accurately than those who did not bowl a ball, the main effect for task conditions was not significant, F(1, 28) = 3.32, p = .08, g2p ¼ :11. During re-acquisition, there was a significant effect of model, F(1, 28) = 4.74, p < .05, g2p ¼ :16, and task conditions, F(1, 28) = 7.99, p < .01, g2p ¼ :22. Participants who observed the FULL model during both acquisition and re-acquisition were significantly more accurate at imitating the model’s hip–knee coordination profile than the ENDPT groups. There was no evidence that the additional relative motion information was used to change the lower limb coordination pattern for the ENDPT groups. Participants in the two BALL groups, irrespective of model type, were significantly more accurate in terms of likeness to the model than the two groups who did not bowl a ball. There were no significant improvements in hip–knee coordination across re-acquisition as a function of block or any significant interactions. 3.3. Peak wrist velocity The absolute differences in wrist peak velocity relative to the model are displayed in Table 1. In acquisition, a significant main effect for task condition, F(1, 28) = 19.23, p < .01, g2p ¼ :41, and interactions concerning Model · Block, F(2, 56) = 3.48, p < .05, g2p ¼ :11, and Task condition · Block F(2, 56) = 3.17, p < .05, g2p ¼ :10 were observed. In general, participants who bowled a ball showed more similarity to the model than participants who did not bowl a ball. Post-hoc analysis of the interactions revealed that only participants in the FULL groups modified their wrist velocity to become more like the Table 1 Mean (SD) absolute difference in peak wrist velocity (m/s) relative to the model across all test blocks (ACQ = acquisition, RET = retention and RE-ACQ = re-acquisition) as a function of model type (FULL; ENDPT) and task condition (BALL; No-BALL) Model and task condition

ACQ 1

ACQ 2

ACQ 3

RET

RE-ACQ1

RE-ACQ2

FULL

.99 .84 1.03 .62

.82 .56 1.53 .39

.70 .33 1.37 .41

.87 .55 1.37 .38

.96 .41 .86 .43

.85 .55 1.00 .47

ENDPT

No-BALL BALL No-BALL BALL

(.75) (.46) (.61) (.26)

(.77) (.46) (1.04) (.33)

(.65) (.32) (.84) (.30)

(.73) (.37) (.86) (.26)

(.66) (.42) (.97) (.30)

(.64) (.46) (1.03) (.21)

132

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

Table 2 Mean (SD) absolute error (AE) and variable error (VE) scores (in cm) for both groups across acquisition (ACQ), retention (RET) and re-acquisition (RE-ACQ) blocks Model type and error measures AE FULL ENDPT VE FULL ENDPT

ACQ 1

ACQ 2

ACQ 3

RET

RE-ACQ 1

RE-ACQ 2

79.1 (47.1) 85.9 (51.2)

44.6 (27.0) 71.4 (38.3)

51.1 (22.0) 51.0 (25.5)

97.1 (19.1) 56.6 (23.8)

74.0 (32.3) 77.5 (47.4)

79.8 (32.4) 42.4 (15.7)

67.3 (42.9) 66.7 (40.7)

41.7 (34.0) 59.5 (49.9)

37.6 (20.7) 46.5 (29.6)

90.7 (19.9) 54.2 (22.2)

36.8 (31.6) 62.9 (50.7)

35.9 (29.2) 40.54 (18.2)

model from ACQ 1 to ACQ 2 and ACQ 1 to ACQ 3 in comparison to the ENDPT groups, both ps < .05. Similarly, only participants who bowled a ball modified their actions in line with the model across acquisition; ACQ 1 to ACQ 3 (p < .05) in comparison to the nonbowling groups. No other main effects or interactions were significant (all Fs < 1). In retention, a significant main effect was observed for task condition only, F(1, 28), 9.19, p < .01, g2p ¼ :25. Wrist velocity production was significantly influenced by the requirement to bowl a ball; the dynamics were more similar to the model when the learner was tasked with bowling a ball irrespective of model type. This effect remained in re-acquisition, F(1, 28), 6.78, p < .01, g2p ¼ :20. In re-acquisition there was also a significant Model · Block interaction, F(2, 56), 3.87, p < .05, g2p ¼ :12. Post-hoc analysis showed that although the FULL groups performed more like the model than the ENDPT groups on the final block of acquisition, p < .05, after seeing the full-body model in re-acquisition there were no longer any differences between the groups. 3.4. Outcome error The error (AE) and consistency (VE) scores for the ENDPT and FULL groups across the test blocks are displayed in Table 2. For acquisition, only a significant main effect for block was observed, F(2, 28) = 4.25, p < .05, g2p ¼ :23. Both groups reduced their target error (AE) from ACQ 1 to ACQ 3. No significant effects were observed for VE. A significant model main effect was observed for target accuracy (AE), t(14) = 3.75, p < .01, d = 1.9, and consistency (VE), t(14) = 3.47, p < .01, d = 1.7, in retention. The ENDPT group was significantly more accurate and consistent than the FULL group after a 24 h retention period. A significant main effect for block, F(2, 28) = 3.78, p < .05, g2p ¼ :21 and Model · Block interaction were observed, F(2, 28) = 3.37, p < .05, g2p ¼ :19, for AE in re-acquisition. The ENDPT group who now viewed a FULL model showed a reduction in error (AE) from the end of acquisition to re-acquisition block 2, p < .05 such that they performed more accurately than did the FULL group at the end of the re-acquisition trials. No decrease in error was observed for the FULL group. No significant effects were observed for VE. 4. Discussion The aim in this paper was to examine the importance of intra-limb relative motion information in the observational learning of a multi-limb action under different task con-

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

133

ditions. We directly manipulated intra-limb relative motion by removing joint markers from a point-light model. If relative motion is the primary constraining source of information for reproducing a multi-limb action (Scully & Newell, 1985), we predicted that participants who observed a full-body relative motion model would show a closer approximation to the model’s intra-limb coordination profile than those who observed an end-point model. Furthermore, relative motion was expected to have a greater influence under conditions that only required the learner to imitate the model’s movement compared to those where they had to bowl a ball to reach a target location (see Horn et al., 2002; Horn et al., 2005). We also examined when in the learning process this information would be most beneficial by incorporating a re-acquisition phase. Based on Scully and Newell (1985) visual perception perspective, it was predicted that this information would be more beneficial when presented early in the learning process, during the acquisition of movement form, rather than to help scale an already acquired action. There were no significant differences in shoulder–elbow coordination pattern in acquisition, retention, and re-acquisition between the FULL and ENDPT groups. The low NoRM-D values indicated that all groups approximated the model’s coordination pattern relatively accurately (similar NoRM-D values have been reported as evidence for a close approximation of a movement pattern, see Hodges et al., 2005; Horn et al., 2005). This pattern can also be seen from inspection of the angle–angle plots for shoulder–elbow coordination (see Fig. 2). Although the ENDPT groups viewed only motions of the wrist and feet, and the No-Ball group had no further contextual information beyond the model, the upper-body coordination patterns for these groups were similar to the model and were generally more accurate than the FULL groups. Supplementary trial-by-trial analyses confirmed that all groups modified their shoulder–elbow coordination to become more like the model from Trial 1 to Trial 3. In line with other research, it seems that learners only require a limited exposure to a model in order to adapt their intra-limb coordination profile to more closely approximate the model (see Hodges et al., 2005; Horn, Williams, Hayes, Hodges, & Scott, in press; Scully & Carnegie, 1998). It is important to note, however, that these early acquisition effects are likely to be dependent on other factors related to task difficulty as well as measurement of movement accuracy. For example, in the learning of bi-manual coordination skills requiring a complex spatial and temporal pattern of coordination between the limbs, the number of practice trials required to acquire the desired movement pattern (as measured through between limb relative phase) is significantly increased (see Hodges & Franks, 2002; Lee, Swinnen, & Verschueren, 1995). A different pattern of results was found for hip–knee coordination. The Model · Block interaction indicated that relative motion information was more effective in encouraging learners’ reproduction across the first acquisition block (ACQ 1). Examination of the first three trials of ACQ 1 showed that only the FULL body participants’ coordination pattern changed to become more like the model. The requirement to bowl a ball to an external target influenced the learners’ pattern of hip–knee coordination (p = .06) to more closely approximate the model. Hodges et al. (2005) reported similar findings when participants were required to kick a ball, rather than only copy a model, in terms of the accuracy of coordination in relation to the model. The acquisition effects for the hip–knee coordination remained after a 24 h retention period. Moreover, there was no improvement in the lower limb intra-limb coordination profile of the ENDPT groups (and the FULL body groups) following the observation

134

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

of the full-body model in re-acquisition. Newell (1985) and Scully and Newell (1985) have proposed that demonstrations, and in particular relative motion information, is most useful early in acquisition to help acquire the movement form. Newell (1985) proposed that coordination and control operate as an embedded hierarchy such that during learning the relative contribution of these components are weighted towards coordination in early learning, when the pattern of coordination is not assembled, and begins to shift towards scaling once the general coordination pattern is formed. For both model groups, and irrespective of the task demands, a full-body demonstration did not lead to any further improvements in the coordination supporting this interpretation. The analysis of wrist peak velocity showed that the dynamics of the movement were better replicated when the observers were able to bowl a ball, as opposed to only viewing a demonstration. This effect was observed throughout acquisition, retention, and re-acquisition. If observers are not required to match a movement with an associated outcome goal, the underlying control properties are not well produced even though they can be perceived (Runeson & Frykolm, 1983; Shim, Carlton, & Kim, 2004). Although the ENDPT groups viewed only the displacement of the wrist and hence one might expect the dynamicrelated properties of the movement to be more salient, this condition did not lead to a closer approximation of the model’s velocity profile. In fact, the absence of intra-limb coordination pertaining to the motions of the arm had a negative impact, at least in acquisition, on this control-related parameter, although it did not affect the observed shoulder–elbow coordination pattern. This conclusion was confirmed by the finding that following the presentation of the full-body model to all groups in re-acquisition a Model · Block interaction was observed for wrist velocity. The ENDPT groups demonstrated a velocity profile that was more similar to the model after seeing the full-body model. We also examined the outcome performance of the two bowling groups to determine whether there were any advantages associated with the ENDPT or FULL models. Both groups improved their accuracy (AE) across acquisition. However, in retention the ENDPT group was more accurate (AE) and consistent (VE) than the FULL group whose performance deteriorated. One explanation is that the FULL group’s acquisition performance was dependent on having access to the full-body model. Similar dependency effects have been shown in other motor and observational learning experiments where reducing the amount of augmented information in acquisition benefits motor retention (e.g., Badets & Blandin, 2004; Badets & Blandin, 2005; Hodges, Hayes, Eaves, Horn, & Williams, 2006; Salmoni, Schmidt, & Walter, 1984). It has been argued that a reduction in the amount of information provided during acquisition encourages the learner to engage in cognitive processes, such as hypothesis-testing and error detection, that facilitate learning and hence performance in retention. It is worth noting, however, that without a control group where no information about the desired movement is presented, it is not possible to make a general statement about the beneficial effects of this information for learning. An examination of outcome performance and wrist velocity dynamics across the acquisition phase seems to indicate that these variables might be linked. It is evident that as the BALL groups became more accurate at hitting the target across acquisition blocks their wrist velocity dynamics also became more similar to the criterion model (see also Hayes et al., 2006). However, although the ENDPT-Ball group was significantly more accurate and consistent in retention (i.e., AE and VE) than the FULL-Ball group, their velocity dynamics were not significantly different. This is surprising given that velocity and out-

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

135

come seemed to be linked in acquisition. Inspection of the velocity difference data in retention does however show a trend in the direction of the outcome data (ENDPT-Ball, M = .38, SD = .25; FULL-Ball, M = .55, SD = .38). The addition of a full-body model in re-acquisition for the ENDPT-Ball group had a positive effect on the outcome accuracy with performance being significantly more accurate than the FULL-Ball group at RE-ACQ 2. The advantage accrued from viewing the FULL body model was only achieved following an earlier practice with the impoverished end-point model. This finding might lead to the suggestion that initially withholding information facilitates the pick up and use of this information later in practice to facilitate performance, although this did not manifest itself in terms of a more accurate coordination pattern or peak wrist velocity profile. Research is underway to test this proposal using eye movement recording techniques. The current findings provide mixed support for Scully and Newell (1985) hypothesis that relative motion information is the critical constraining source of information for acquiring intra-limb coordination during observational learning. It seems that irrespective of the task conditions and contextual cues, the ENDPT learners accurately produced shoulder–elbow coordination (in terms of similarity to the model) even though access to intra-limb relative motion was withheld (see also Hodges et al., 2005). We propose that the trajectory of the end-point of the main effector is sufficient information for recognizing motor actions that are relatively unusual and novel and that observers track this feature to form a trajectory plan that is used to control movement execution (see Mataric & Pomplun, 1998; Mather et al., 1992; Morasso, 1981). In previous papers, where it has been concluded that relative motion information is extracted and used from a demonstration to inform the acquisition of coordination (e.g., Al-Abood et al., 2001; Horn et al., 2005), it could be the case that the observers used the effector’s end-point to constrain action. However, we are hesitant in concluding that end-point trajectory information will always be sufficient both in view of some disadvantages in lower-body coordination for the ENDPT groups and also because of previous findings. For example, Breslin et al. (2005, in press) showed that for a more complex arm trajectory motion, as demonstrated in cricket bowling where the bowling arm is swung vertically in a circular motion in coordination with the non-bowling arm, additional information beyond the motion of the wrist is needed. Moreover in this cricket task, the dynamics of the movement are less important than in crown-green bowling, where the ball is required to stop on a line rather than merely hit a target at any speed. In conclusion, an executed relative motion pattern that approximates a criterion model is not, by default, a consequence of the learner extracting and using relative motion. In addition to end-point dynamics that constrain coordination (Hodges et al., 2005), properties of the task itself are responsible in shaping the desired, or a task goal specific, pattern of intra-limb coordination, and movement control dynamics (see Newell, 1986). Although end-point dynamics can be used to constrain intra-limb coordination, there is evidence that relative motion aids action imitation when the body parts in question are more remote to the primary-effector (i.e., lower-body coordination in this case) or if the action is particularly complex. There is evidence that actions are planned and executed in terms of their anticipated distal effects (Kunde et al., 2002) and that for actions that require an object to be accurately displaced, such as in throwing or bowling, invariance and accuracy in the end-point trajectory of the end-effector is critical and thus is the point about which the performer is most concerned (see Gentile, 1998; Latash, 1996).

136

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

We have also presented some evidence that full-body demonstrations and arguably relative motion might be useful at the later stages of practice, at least in terms of facilitating outcome success (cf., Scully & Newell, 1985). Although we did not find concomitant effects for scaling variables in the re-acquisition phase, the finding that outcome performance and wrist velocity were linked in acquisition warrants further research designed to understand what information specifically aids performance at this later stage, perhaps through the examination of visual point-of-gaze or the use of spatial occlusion techniques where the amount of information available is manipulated in addition to the type of information. References Al-Abood, S. A., Davids, K., & Bennett, S. J. (2001). Specificity of task constraints and effects of visual demonstrations and verbal instructions in directing learner’s search during skill acquisition. Journal of Motor Behavior, 33, 295–305. Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ: Prentice-Hall. Badets, A., & Blandin, Y. (2004). The role of knowledge of results frequency in learning through observation. Journal of Motor Behavior, 36, 62–70. Badets, A., & Blandin, Y. (2005). Observational learning: effects of bandwidth knowledge of results. Journal of Motor Behavior, 37, 211–216. Bernstein, N. A. (1967). The coordination and regulation of movements. New York: Pergamon Press. Bernstein, N. A. (1996). On dexterity and its development. In M. L. Latash & M. T. Turvey (Eds.), Dexterity and its development (pp. 3–244). Mahwah, NJ: Erlbaum. Bekkering, H., Wohlschla¨ger, A., & Gattis, M. (2000). Imitation of gestures in children is goal-directed. Quarterly Journal of Experimental Psychology, 53A, 153–164. Breslin, G., Hodges, N. J., Williams, A. M., Curran, W., & Kremer, J. (2005). Modelling relative motion to facilitate intra-limb coordination. Human Movement Science, 24, 446–463. Breslin, G., Hodges, N. J., Williams, A. M., Curran, W., & Kramer, J. (in press). The role of intra and inter-limb relative motion information in modeling a novel motor skill. Human Movement Science. Cutting, J. E., & Proffitt, D. R. (1982). The minimum principle and the perception of absolute, common and relative motion. Cognitive Psychology, 14, 211–246. Dupuy, M. A., Mottet, D., & Ripoll, H. (2000). The regulation of release parameters in underarm precision throwing. Journal of Sport Sciences, 18, 375–382. Gentile, A. M. (1998). Implicit and explicit processes during acquistion of functional skills. Scandinavian Journal of Occupational Therapy, 5, 7–16. Feynman, R. P., Leighton, R. B., & Sands, M. (1965). The Feynman lectures on physics. Addison-Wesley. Hayes, S. J., Hodges, N. J., Scott, M. A., Horn, R. R., & Williams, A. M. (2006). Scaling a motor skill through observation and practice. Journal of Motor Behavior, 38, 357–366. Hayes, S. J., Hodges, N. J., Scott, M. A., Horn, R. R., & Williams, A. M. (in press). The efficacy of point light demonstrations in teaching children an unfamiliar movement: effects of perceptual training and task constraints. Journal of Sports Sciences. Hodges, N. J., & Franks, I. M. (2002). Learning as a function of coordination bias: building upon pre-practice behaviours. Human Movement Science, 21, 231–258. Hodges, N. J., Hayes, S. J., Breslin, G., & Williams, A. M. (2005). An evaluation of the minimal constraining information during movement observation and reproduction. Acta Psychologica, 119, 264–282. Hodges, N. J., Hayes, S. J., Eaves, D., Horn, R., & Williams, A. M. (2006). End-point trajectory matching as a method for teaching kicking skills. International Journal of Sport Psychology, 37, 230–247. Hommel, B., Mu¨sseler, J., Aschersleben, G., & Prinz, W. (2001). The theory of event coding (TEC): a framework for perception and action planning. Behavioural and Brain Sciences, 24, 849–878. Horn, R. R., Williams, A. M., & Scott, M. A. (2002). Learning from demonstration: the role of visual search from video and point-light displays. Journal of Sports Sciences, 20, 253–269. Horn, R. R., Williams, A. M., Scott, M. A., & Hodges, N. J. (2005). Visual search and coordination changes in response to video and point-light demonstrations without KR. Journal of Motor Behavior, 37, 265–274. Horn, R. R., Williams, A. M., Hayes, S. J., Hodges, N. J., & Scott, M. A. (in press). Demonstration as a rate enhancer to changes in coordination during early skill acquisition. Journal of Sports Sciences.

S.J. Hayes et al. / Acta Psychologica 126 (2007) 120–137

137

Johansson, G. (1973). Visual perception of biological motion and a model for its analysis. Perception & Psychophysics, 14, 201–211. Kugler, P. N., Kelso, J. A. S., & Turvey, M. T. (1980). On the concept of coordinative structures as dissipative structures: theoretical lines of convergence. In G. E. Stelmach & J. Requin (Eds.), Tutorials in motor behaviour (pp. 3–47). Amsterdam: North Holland. Kugler, P. N., Kelso, J. A. S., & Turvey, M. T. (1982). On the control and co-ordination of naturally developing systems. In J. A. S. Kelso & J. E. Clark (Eds.), The development of movement control and co-ordination. Chichester: Wiley. Kunde, W. (2003). Temporal response-effect compatibility. Psychological Research, 67, 153–159. Kunde, W., Hoffman, J., & Zellmann, P. (2002). The impact of anticipated action effects on action planning. Acta Psychologica, 109, 137–155. Latash, M. L. (1993). Control of human movement. Urbana, IL: Human Kinetics. Latash, M. L. (1996). The Bernstein problem: how does the central nervous system make its choices? In M. L. Latash & M. T. Turvey (Eds.), Dexterity and its development Mahwah. NJ: Erlbaum (pp. 277–304). Lee, T. D., Swinnen, S. P., & Verschueren, S. (1995). Relative phase alterations during bimanual skill acquisition. Journal of Motor Behavior, 27, 263–274. Mataric, M., & Pomplun, M. (1998). Fixation behavior in observation and imitation of human movement. Cognitive Brain Research, 7, 191–202. Mather, G., Radford, K., & West, S. (1992). Low-level visual processing in biological motion. Proceedings of the Royal Society of London, B, 273–279. Morasso, P. (1981). Spatial control of arm movements. Experimental Brain Research, 42, 223–227. Mullineaux, D. R., Bartlett, R. M., & Bennett, S. J. (2001). Research design and statistics in biomechanics and motor control. Journal of Sports Sciences, 19, 739–760. Newell, K. M. (1985). Coordination, control and skill. In D. Goodman, R. B. Wilberg, & I. M. Franks (Eds.), Differing perspectives in motor learning. Memory and control (pp. 295–317). Amsterdam: Elsevier. Newell, K. M. (1986). Constraints on the development of coordination. In M. G. Wade & H. T. A. Whiting (Eds.), Motor development in children: aspects of coordination and control (pp. 341–360). Boston: Martinus Nijhoff. Runeson, S., & Frykolm, G. (1983). Kinematic specification of dynamics as an informational basis for personand-action perception. Journal of Experimental Psychology: General, 112, 589–615. Salmoni, A. W., Schmidt, R. A., & Walter, C. B. (1984). Knowledge of results and motor learning: a review and critical reappraisal. Psychological Bulletin, 95, 353–386. Scully, D. M., & Newell, K. M. (1985). Observational learning and the acquisition of motor skills: toward a visual perception perspective. Journal of Human Movement Studies, 11, 169–186. Scully, D., & Carnegie, E. (1998). Observational learning in motor skill acquisition. The Irish Journal of Psychology, 19, 472–485. Shim, J., Carlton, L. G., & Kim, J. (2004). Estimation of lifted weight and produced effort through perception of point-light display. Perception, 33, 277–291. Sidaway, B., Heise, G., & Schoenfelder-Zhodi, B. (1995). Quantifying the variability of angle–angle plots. Journal of Human Movement Studies, 29, 181–197. Whiting, H. T. A., Bijlard, M. J., & Brinker, B. P. L. M. (1987). The effect of availability of a dynamic model on the acquisition of a cyclical action. Quarterly Journal of Experimental Psychology, 39A, 43–59.