The role of augmented information prior to learning a bimanual visual-motor coordination task: do instructions of the movement pattern facilitate learning relative to discovery learning?
Although information as feedback during or after the performance of a motor act has received much attention, less consideration has been given to information or instruction prior to learning, even though it is commonly believed that providing instruction to beginners is necessary for learning to occur. From a theoretical perspective it has been proposed that information provided prior to the acquisition of a motor skill serves to facilitate the development of a reference of correctness (e.g. Carroll & Bandura, 1982; Gentile, 1972; Swinnen, 1996) that would act like a template with which to compare performance. However, contrary to expectation the benefit of instruction prior to learning has received little support, and in some situations has shown to be harmful to the acquisition of coordinative skills e.g. learning to control a ski-simulator (e.g. Wulf & Weigelt, 1997) or putt a golf ball under stressful conditions (Hardy, Mullen & Jones, 1996; Masters, 1992).
Task instructions have received considerable attention within cognitive psychology (e.g. Berry & Broadbent, 1984, 1988; Reber, 1967, 1989), where it has been shown that participants are able to control a computerized interactive system, or discriminate artificial grammars, without explicit awareness of the rules governing performance (so-called implicit learning). Indeed, explicit knowledge of these rules did not benefit decision performance in relation to groups who had this knowledge withheld (e.g. Berry & Broadbent, 1984).
A number of possible reasons have been given for the results observed in implicit learning studies and in learning contexts where instructions have been manipulated. One reason is that explicit instructions may lead to a narrow focus of attention on only specific aspects of the task and ultimately a limited application of strategies to solve the task. Another reason is that instructions may distract attention away from the processing of more important information sources, such as kinaesthetic or visual information that may be integral to task execution. In contrast, when instructions are withheld participants may demonstrate a more exploratory learning strategy, becoming more familiar with the dynamics of the task and variations in intrinsic information sources. This type of learning has been referred to as 'discovery learning'. Vereijken & Whiting (1989) have contrasted discovery environments with more prescriptive approaches in learning to perform slalom movements on a ski simulator. Discovery learning was found to be as effective, and in some situations more beneficial to learning, than situations where participants were directed towards certain critical performance variables prior to learning, or when given a dynamic model to copy. Although differences in performance measures have been observed across these learning groups, Vereijken & Whiting (1989) point out that it is unclear whether the discovery learning groups approach the task in similar ways to the instructed groups, a question that we address in the current experiment.
Green & Flowers (1991) also found that instructions concerning probability information in a computerized catching task were disruptive to learning. They suggested that providing learners with instructions or rules may lead to an increase in processing load and high attentional demands during acquisition which is subsequently harmful to learning. Learning is generally presumed to be highly cognitive, attention demanding, and effortful early in acquisition (Anderson, 1982; Fitts & Posner, 1967; Gentile, 1998; Schneider & Schiffrin, 1977), and therefore, overloading beginners with instruction may prove to be particularly harmful at this stage. However, Wulf & Weigelt (1997) found that regardless of when instructions were provided (either at the start or after 3 days of learning) they were equally ineffective and, in both cases, even degraded performance.
The question that is of concern to this study is the reason why instructions may be harmful to acquisition. Do they promote a limited application of strategies to solve a novel motor task, and/or do instructions serve to keep attention focused at a cognitively demanding level that may prove to be disruptive to learning especially under increased attention conditions? In order to answer this question a task was chosen that allowed examination of the process of learning in relation to knowledge of pre-existing behaviours and their relative stabilities within the framework of dynamical systems.
Within the skill acquisition literature there has been a trend to examine more complex, coordinative skills as they are believed to be more representative of real-world motor learning environments. Rather than rescaling a previously acquired skill, such as learning to hit a target within a specified movement time, acquiring new relationships between body segments presents a more novel, true-to-life learning situation with which to examine the influence of instructional manipulations. Therefore, the following study was conducted to address how instructions influence the learning process of a novel bimanual coordination skill. Knowledge of existing coordinative preferences have been detailed elsewhere (e.g. Kelso, 1995) that provide a framework with which to evaluate learning as a result of instructional manipulations.
One of the consequences of this approach to the study of motor behaviour has been the development of a task environment to study dual limb coordinative movements. Kelso (1984) identified two stable, preferred patterns of bimanual coordination: 0 [degree] relative phase (in-phase), which is characterized by simultaneous flexion and extension of homologous muscles; and 180 [degrees] relative phase (anti-phase), which is characterized by alternating flexion and extension of homologous muscle groups. Interestingly, when the speed of performing these coordination patterns is increased, there is a critical point whereby the anti-phase pattern destabilizes, and a transition to the more stable, in-phase pattern is observed (whereas the opposite does not occur). This transitional behaviour is preceded by an increase in the variability of timing between the limbs (the standard deviation in relative phase) which provides an important measure of pattern stability. These bistable coordination tendencies are similar for all individuals and are referred to as the intrinsic dynamics.
Knowledge of these existing coordination preferences provides a background to examine and compare the learning of novel patterns. One pattern that has received considerable attention is the learning of 90 [degrees] relative phase. This pattern lies half-way between the two stable intrinsic states (0 [degree] and 180 [degrees] relative phase), creating a competitive learning environment between the intrinsic dynamics and the to-be-learned pattern (a situation commonly observed in the learning of motor skills, whereby existing habits or behaviours interfere with the learning of new ones). It is the acquisition of this novel pattern that will be examined in the following study. Augmented feedback about this pattern can be displayed on a computer monitor by plotting the real time displacement of one limb on the ordinate against the displacement of the other limb on the abscissa. When performing in 90 [degrees] relative phase the plot (Lissajous figure) appears as a circle. This information can then be used to specify the task goal and be provided to participants as augmented feedback.
In light of the foregoing discussion it is predicted that initial instruction concerning how to make the circle pattern, i.e. coordinate the limbs 90 [degrees] out of phase, will not facilitate learning of this new behavioural pattern, and may even be detrimental to learning. Due to the competition between the required pattern and the intrinsic dynamics, discovery methods of learning may serve to facilitate more exploration of the task dynamics, encouraging the breaking away from these competing stable patterns. This greater exploration may be evidenced initially by increased variability in relative phase, which will decrease substantially on acquisition of the new pattern. In this particular task measures of performance stability are important indicators of the strength of learning and reflect the underlying competition within the system's dynamics.
Two instruction groups will be examined. One group will receive a step-by-step specific guide as to the positioning of the hands every quarter of a cycle, whereas a second group will receive general instructions specifying the starting positions of the hands and the general rule that one hand should always follow behind the other by a quarter of a cycle. The general instruction (GI) group was included to rule out the possibility that instructions did not facilitate learning because they were too detailed and confusing, as could possibly be the case for the specific instructions. Additionally, step-by-step sequential instructions as provided in the specific instruction (SI) group are frequently given to performers before learning a new motor skill, and therefore, we were interested as to whether this type of instruction was more effective than general instruction.
Two other groups will not receive instruction concerning how to make the new pattern, and in addition one of these groups will be required to perform a secondary, cognitively demanding task during practice, of counting backwards in threes into a tape recorder. This secondary task situation is similar to implicit learning manipulations that have been examined in previous motor learning studies, for example, Hardy et al. (1996) and Masters (1992). These authors showed that participants were able to acquire a golf-putting skill and, in contrast to explicit learning groups, showed a resistance to stress-inducing transfer conditions. Since we have a secondary task condition in transfer, requiring a group to practise the task under these same conditions during acquisition provides a control to compare transfer performance, as well as an opportunity to examine whether this coordination pattern can be acquired under conditions of divided attention.
The purpose of this transfer test was twofold. First, adding a cognitive load may serve to stress the system's dynamics and therefore provide a window into the stability of the newly acquired pattern (see Kelso, 1994). Second, attention-demanding tasks have typically been used to infer the type of resources that are allocated to the primary task, with the supposition being that if the resources of the primary and secondary task are dissimilar then the amount of interference between them will be minimal (e.g. Wickens, 1980). In contrast, if the resources are shared then there will be an increased cost leading to a reduction in performance on the primary task. In this case, a cognitive-verbal task would be expected to interfere more with individuals who are performing the task in a more explicit, instructional manner as compared to individuals who have acquired the task in the absence of instructions, or in an implicit manner. An additional transfer test of performing a new pattern (45 [degrees] relative phase) will also be given to explore the generalizability of learning as a result of these different instructional manipulations.
There were a total of 33 participants in this investigation, 10 males and 23 females. The participants were volunteer undergraduate and graduate students in kinesiology at McMaster University in Hamilton, Ontario, Canada. Their ages ranged from 18-26 years. Participants were randomly allocated to one of four groups where prior instruction was manipulated (specific or general instructions, no instruction and no instruction plus a secondary task) resulting in eight participants per group (nine in the general instruction group). All participants were right handed and naive to the purpose of the experiment and the task itself. All participants received $15 on completion of retention tests.
A bimanual linear slide apparatus was used. Participants were required to move two vertical wooden handles (12.5 cm in height, 3 cm diameter), which were attached to slides located directly in front of where the participant was seated and centred at the participant's mid-line. The slides moved horizontally across ball-bearings that were enclosed within metal casings. Movements could be made to the right or left from the participant's mid-line and visual markers on the apparatus dictated the amplitude of these movements (31 cm for a full in-out-in cycle for each limb). Linear potentiometers (Duncan Electronics, DEL Elec 612R12KL.08) were attached parallel to the linear slide to encode displacement. A microprocessor (80486) was used to sample the data at a frequency of 200 Hz. The LabWindows software program (National Instruments Corporation, version 2.2.1) was responsible for starting and ending each 15 second trial as well as recording peak amplitude and point estimates of relative phase. In addition, participants were required to move at a speed of 1 Hz to perform one complete cycle in time with an auditory metronome (Lafayette Instrument Co. 58025).
Terminal feedback was provided to the participants via a computer monitor (AMA VGA colour monitor, model SC-431VS), situated 45 [degrees] to the left of the participant, that displayed a Lissajous figure (a real-time summary of the displacement-displacement plots of the right limb against the left limb, see [ILLUSTRATION FOR FIGURE 1 OMITTED]).
Participants were tested individually over a 3-day period - 2 concurrent days of acquisition followed by retention and transfer tests on the third day. All participants were told that their task was to learn how to manipulate their hands in such a way as to produce a circle on the computer screen with as much overlap as possible (a computer printout of a good trial was shown to participants). Participants were allowed to practise moving the linear slide to familiarize themselves with the movement amplitude and temporal constraints only, but at no time prior to testing were participants shown the effects of their movements as related to the production of the circle pattern. Timing of the movements was prescribed by an auditory metronome and each trial lasted 15 seconds.
Further instructions were provided dependent on the group assignment. The general instruction (GI) group was given information specifying the starting positions of the left and right hands and that the left hand should mirror the right hand but should follow behind by a quarter of a cycle. The specific instruction (SI) group also received this information, as well as a schematic diagram detailing the exact position of each hand every quarter of a cycle and the direction of movement. This information was displayed in a series of four steps that would be necessary to produce one full movement cycle (i.e. one full extension/flexion excursion). After receiving the instructions participants were asked to repeat into a tape-recorder how they were going to make the circle pattern based on what they had just read. This procedure was used to encourage participants to process the instructions explicitly. These instructions were provided at the start of each day of acquisition and at the mid-point during practice trials conducted on each day. Although the two no-instruction groups were not given any information concerning how to produce the circle pattern, the secondary task learning (STL) group was told that they would be required to count backwards in threes while trying to make the 90 [degrees] pattern. They were given practice at this subtraction task and at the start of each acquisition trial they were given a new predetermined number from which to start counting backwards.
All verbalizations throughout testing for all groups were recorded. Participants performed all trials with vision of their limbs only and received computer-generated feedback at the end of each trial in the form of a Lissajous trace overlaying the criterion (circle) pattern. Additionally, after every fifth trial the computer provided terminal feedback of the just-performed trial replayed to the participant in real time.
There were 35 trials (7 blocks) of acquisition each day. On the retention and transfer day participants were required to reproduce the circle pattern under eight no-feedback trials. On half of these trials participants were additionally required to perform a secondary task of counting backwards in threes during the circle production. These trials were presented in a pseudo-random order, with the constraint that no more than two trials of the same condition could follow each other. This order of presentation was consistent across all participants. Finally, participants were asked to produce a novel bimanual timing pattern in which the limbs lagged by one eighth of a cycle (i.e. in 45 [degrees] relative phase). After the first attempt terminal feedback was provided in the form of a Lissajous trace (which, for 45 [degrees] relative phase, is an elliptical pattern). Participants underwent eight 45 [degrees] transfer trials altogether, four of which were performed concurrently with the secondary task. At the end of transfer testing participants were given a questionnaire that assessed their knowledge about the relative positions of the hands for both the 90 [degrees] and 45 [degrees] patterns. Only two questions pertaining to each pattern required answering, relating to both the correct positioning of the hands as well as the direction of movement. Specifically, a schematic diagram was presented to the participant that had the position and direction of movement of one of the hands marked on a diagram of the bimanual apparatus, and the participants were asked to mark on the correct position of the alternative hand, as well as the direction of movement. Therefore, a total score of 4 was possible for each pattern.
The relative phasing of the left hand in relation to the right hand (i.e. the difference between the limbs) was calculated for each positive (maximum flexion) and negative (maximum extension) peak within each trial, after the position and speed of the limbs had been rescaled to the interval (-1, 1) for each cycle. The phase angles were calculated using the methods described in Scholz & Kelso (1989)(1). The within-trial mean of these phase angles and the within trial standard deviation (SD) were calculated. The mean number of cycles participants had produced was also determined.
Absolute constant error ([absolute value of CE]) was obtained by subtracting the mean of relative phase from the task goal (either 90 [degrees] or 45 [degrees]), and taking the absolute of this value. All dependent measures in acquisition were submitted to a 4 (group) x 2 (day) x 7 (blocks) ANOVA with repeated measures on the last two factors. A 2-way ANOVA 4 (group) x 2 (condition: secondary task/no secondary task) was performed on the retention and transfer data for each pattern. The Tukey HSD method was used for all post hoc comparisons and statistical significance was set at p [less than] .05.
The results for |CE| are shown in Fig. 2. A significant effect for group was observed (F(3,29) = 4.87, p [less than] .01). Post hoc comparison between the means showed that this effect was due to the poor performance of the STL group who demonstrated significantly more error than the no-instruction (NI) and SI groups. Although all groups demonstrated improvements across blocks and over the 2 days of acquisition, the majority of learning occurred on the first day as evidenced by a day x block interaction (F(6,174) = 2.16, p [less than] .05). On the first day, block 1 was significantly different from all blocks, except block 2. However, on the second day the first block was only significantly different from blocks 5, 6 and 7.
On inspection of mean relative phase a main effect for group was found (F(3,29) = 6.94, p [less than] .01). The NI and STL groups were not significantly different from each other and had a tendency to produce in-phase movements early in acquisition. The two instruction groups were also not significantly different from each other and both groups produced mean values close to 180 [degrees] relative phase [ILLUSTRATION FOR FIGURE 3 OMITTED]. However, both the instruction groups were significantly different from the STL group. Group x day (F(3,29) = 3.62, p [less than] .05) and group x block (F(18,174) = 2.28, p [less than] .01) interactions were also observed, demonstrating that with increased practice all four groups approached the goal relative phase value of 90 [degrees].
On examination of within-trial SD of relative phase it was found that the NI and SI groups demonstrated the greatest variability especially on the first day of practice, although the effects were not significant (group x day interaction, F(3,29) = 2.32, p = .096, see [ILLUSTRATION FOR FIGURE 4 OMITTED]). When the average number of cycles per trial was examined, the main effect of group approached conventional levels of significance (F(3,29) = 2.83, p = .056). The SI group produced fewer cycles than the other three groups, suggesting that in order to use the instructions effectively a trade-off in speed may be necessary.
Retention and transfer
The circle and ellipse patterns were analysed separately due to the poor performance (and non-homogeneity) of all groups when transferred to the ellipse pattern. For this novel pattern there were no significant main effects or interactions for any of the measures. Therefore, the focus of the retention and transfer data was on the circle pattern. Any transfer data reported, both in the text and in the figures, refers only to the secondary task transfer test.
For the circle pattern, absolute constant error results showed main effects for group (F(3,29) = 2.99, p [less than] .05), secondary-task transfer condition (F(1,29) = 13.07, p [less than] .01), as well as a group x condition interaction (F(3,29) = 3.21, p [less than] .05). Again the STL group exhibited the greatest amount of error in retention and transfer, followed by the GI group. Both the SI and NI groups demonstrated the least error. However, the only significant difference when the main effect for group was submitted to a post hoc analysis was between the STL group and the NI group. The main effect for the secondary task transfer condition showed, unsurprisingly, that error increased when participants had to make the circle concurrently with the secondary task. What was of most interest, however, was that an analysis of the interaction between group and condition showed that only the SI group was significantly affected by this manipulation relative to performance pre-transfer [ILLUSTRATION FOR FIGURE 2 OMITTED]. There were no significant differences between the two groups with respect to their performance on the secondary task transfer condition in terms of number of correct verbalizations.
A group x condition interaction effect was also found for mean relative phase (F(3,29) = 8.88, p [less than] .001). On inspection of the means it could be seen that the reason for this performance decrement for the SI group was a regression back to a pre-existing attractor state (180 [degrees] relative phase, see [ILLUSTRATION FOR FIGURE 3 OMITTED]). One of the reasons for this regression may be the lack of stability in retention performance of this group. Although not significant, the SI group also exhibited the highest within-trial standard deviation values, both with and without the secondary task [ILLUSTRATION FOR FIGURE 4 OMITTED].
Given the nominal nature of the data collected from the questionnaires, no quantitative analyses were performed on the data, instead only a visual inspection of the means was conducted [ILLUSTRATION FOR FIGURE 5 OMITTED].
It can be seen from the graph that, as expected, the two instruction groups scored nearly perfect scores for the circle task, although their scores were very low for the ellipse pattern, for which none of the groups received prior instruction. The NI group, although not quite as explicitly knowledgeable as the instruction groups with regards to how to make the circle pattern, still scored highly, demonstrating that the knowledge they had acquired was verbalizable. The STL group scored the lowest on the questionnaire. Interestingly, although all groups performed poorly on the right-ellipse task knowledge, the NI group gave answers that indicated that they knew how to make the elliptical pattern, relative to the other three groups. The SI group scored the lowest when asked the correct positions of the hands for the right-ellipse pattern.
The purpose of this experiment was to examine the process of learning a complex bimanual coordination pattern in the presence or absence of prescriptive instructions specifying how to do so. Specifically, this particular task allowed an examination of the acquisition process in comparison to pre-existing behavioural tendencies. In general it was found that acquisition performance was independent of whether participants did or did not receive instruction detailing how the hands should be coordinated to make the circle pattern. The type of instruction did appear to mediate performance, that is, the general instruction (GI) group had more difficulty acquiring the task than the specific instruction (SI) group, although the difference between these groups was not significant. This trend for the SI group to perform better than the GI group suggests that it is not the amount of information provided prior to learning (i.e. too much) that is disruptive to performance, as was originally proposed. However, the SI group also moved the slowest during the trials (i.e. produced the fewest cycles) which may have helped them implement the instructions they had received. Indeed, Walter & Swinnen (1992) showed that slowing down the task, by reducing the required frequency, facilitated breaking away from intrinsic attractors.
The no-instruction (NI) and SI groups were the most accurate in acquisition and demonstrated similar performance. However, the process of acquisition was quite different for both groups. Mean relative phase values indicated that the SI participants showed an initial preference towards the anti-phase pattern, whereas the no-instruction groups showed a preference towards the in-phase pattern. It would seem that the instructions alerted participants to the fact that in-phase was definitely not the way to make the circle pattern, thus leading to the initial bias towards anti-phase. This knowledge, however, did not benefit the learning process (especially for the GI group), and may have even been disruptive to learning, possibly by hindering exploration of the task dynamics.
An alternative explanation is that the anti-phase pattern may have been a stronger attractor, than in-phase, for the to-be-learned 90 [degrees] relative phase pattern, such that acquisition of the new pattern may have been more difficult and the resulting pattern less stable (see Fontaine, Lee & Swinnen, 1997). We will return to this hypothesis below when we discuss the transfer findings.
The retention and transfer data yielded the most interesting findings. The superior performance of the SI and NI groups was maintained during retention. No differences in error between these two groups was found. However, the SI group was significantly affected by the secondary task transfer condition whereas the NI group did not show any detriment in performance on transfer to this condition. Specifically, participants in the SI group showed a regression back to the previously stable anti-phase attractor. This finding is particularly interesting, suggesting that these two groups, although demonstrating similar performance with regards to outcome measures, were actually performing the primary task in quite different ways. In terms of the multiple resource model referred to in the introduction, it would appear that whatever resources the NI group was using to perform the primary task, these were not interfered with by the secondary task. In contrast, the SI group did show interference. Given that the secondary task was highly cognitive and verbal, i.e. counting backwards aloud, this suggests that the SI group was also drawing on similar cognitive-verbal resources to produce the 90 [degrees] relative phase pattern. Although it is possible only to speculate as to what this group was actually attending to during production of the circle pattern, one possibility is that they were repeating key aspects of the instructions to themselves during execution, such that dividing attention with this secondary task may have been particularly disruptive to performance.
Additionally this decrement in performance under secondary task transfer conditions for the SI group may be related to the stability of the newly acquired pattern. Although not significantly different from the other groups, the SI group demonstrated the highest within-trial variability of relative phase, both in retention and transfer. This suggests that although the SI group had learned to produce the circle pattern equal to the NI group, with respect to mean performance, the stability of the learned pattern was not as strong. This lack of stability in the performing of the newly acquired pattern would make it more susceptible to the competitive influences of the intrinsic dynamics, such that the addition of a cognitive load would be sufficient to effect a transition to a more stable, anti-phase pattern, in this case (see Kelso, 1994). As previously alluded, the anti-phase attractor may have continued to exert a stronger influence on the production of the 90 [degrees] pattern that became noticeable only under these cognitive load conditions. Recently Zanone & Kelso (1997) examined learning of this 90 [degrees] pattern and found that, although there were differences between individuals as to attractor preference prior to practice, at the end of practice, when learning was assessed through scanning trials (whereby relative phasing was scaled in intervals from 0 [degrees] -360 [degrees]) participants showed greater attraction to the 90 [degrees] and 180 [degrees] pattern, as compared to 0 [degrees] .(2)
All of the groups had difficulty applying their knowledge to the new transfer pattern (45 [degrees] relative phase), although again the NI and SI groups demonstrated the lowest error for this new pattern, and the NI group scored highest on the post-test questionnaire that assessed the relative position of the two hands when making the ellipse. It seems that this pattern may have been too difficult to acquire within eight practice trials (four of which were performed concurrently with the secondary task).
The findings reviewed above are in agreement with previous studies that have examined the effects of instructions on motor skill learning (e.g. Vereijken & Whiting, 1989; Wulf & Weigelt, 1997) and lead to the conclusion that providing learners with knowledge of how to perform a specific motor skill does not optimize learning and may degrade transfer. Instructions may serve to distract attention away from other important information that needs to be attended to during movement execution. Indeed, the poor performance of the secondary task learning (STL) group suggests that it is important to direct attention to the primary task, possibly the processing of kinaesthetic feedback (or concentrating on breaking away from the intrinsic attractors; see Schmidt & Fitzpatrick, 1996) to acquire new coordination patterns. In light of the nature of this secondary task, it may be that cognitive-verbal resources need to be allocated to the task, at least at some stage during the acquisition process. However, participants in this group did show improvement in production of the circle pattern and maybe with a few more practice sessions would have demonstrated learning equal to the other groups. Perhaps focused attention to the task itself is not necessary for skill acquisition, yet it appears to be an important contributor to the learning process at least in terms of acquisition rate.
Rather than only emphasizing the negative effects of instruction, it is also important to reiterate the beneficial effects of the discovery learning situation. Discovery learning promotes an exploratory problem-solving process that 'forces the learner to explore the dynamics of the system in which he (or she) is working in an iterative way' (Vereijken & Whiting, 1989, p. 168). This greater experience of the dynamical layout may lead to greater stability in performance, especially in the presence of perturbations or increased cognitive loads. In contrast, explicit instructions force the learner to concentrate only on finding the correct solution and therefore repeating the same procedure again and again, possibly getting stuck at an intrinsic attractor (as seems to have been the case for the GI group).
In conclusion, providing learners with knowledge concerning how the limbs should be coordinated to achieve a certain task goal (in this case a circle pattern) is not necessary and indeed may be detrimental, especially in situations that present additional demands or probe the stability of the acquired behaviour. Instructions may hinder the learning process by preventing individuals from actively exploring the task dynamics, breaking free from preferred behaviours, and finding a solution that is stable and suited to the individual's preferences and capabilities. In many real-world motor learning environments, instructions concerning how to produce a specific movement pattern are commonly given before learning proceeds. Yet, given the current findings, it appears that this may not be an optimal, or even a desirable, way of teaching a coordinated activity, especially if the task requires breaking away from old habits or preferred coordination patterns. Further studies are needed to distinguish between the explanations for these results, possibly examining instructions that relate to the intrinsic dynamics, or that encourage active search and exploration so that discovery learning is promoted. The nature of the attentional resources that are demanded by a task of this type require further investigation, to examine what information is critical to learning and requires attention, and how instructions could serve to encourage attention at this task-relevant, functional level without proving harmful to the very goal it is trying to achieve.
This work was supported by a Natural Sciences and Engineering Research Council of Canada operating grant awarded to the second author. We would especially like to thank Ian M. Franks for his advice and critical review of earlier drafts.
1 [Phi] = [tan.sup.-1] ((d[X.sub.R]/dt)/[X.sub.R])- [tan.sup.-1] ((d[X.sub.L]/dt)/[X.sub.L]), where [Phi] = relative phase between the limbs, X is the position of the limb within a cycle rescaled to the interval (-1, 1), (dX/dt) refers to normalized instantaneous velocity, and R and L are the right and left limbs (adapted from Scholz & Kelso, 1989).
2 In an earlier study Zanone & Kelso (1992) found that for some participants the anti-phase attractor actually destabilized with learning; however, there has been little empirical support for the destabilization of this attractor since then (e.g. Fontaine et al., 1997; Swinnen, Lee, Verschueren & Serrien, 1997). The discrepancy in findings may be in part dependent on the method of testing, the dynamics of the individual prior to practice, as well as the amount of practice.
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|Author:||Hodges, Nicola J.; Lee, Timothy D.|
|Publication:||British Journal of Psychology|
|Date:||Aug 1, 1999|
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