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Knowing the good from the bad: Does being aware of KR content matter?
Human Movement Science 31 (2012) 1449–1458
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Human Movement Science journal homepage: www.elsevier.com/locate/humov
Knowing the good from the bad: Does being aware of KR content matter? Jae T. Patterson ⇑, Jana Azizieh Department of Kinesiology, Brock University, Canada
a r t i c l e
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Article history: Available online 8 June 2012 PsycINFO classification: 4.030 5.040 Keywords: Knowledge of results Motor learning Practice Motor skills
a b s t r a c t Previous researchers have suggested that providing KR based on only successful (i.e., good trials) trials enhances learning compared to providing KR on unsuccessful trials (i.e., poor trials). However, the learners were unaware the content of their KR display was based entirely on their successful or unsuccessful trials. Thus, the purpose of the present experiment was to determine whether learning after providing KR after relatively good trials would persist if participants were aware of their KR content. All participants propelled a slider with their non-dominant hand to a pre-determined distance on a linear slide. Participant’s vision was occluded before, during and after their motor action. Similar to previous research, all participants were provided KR on three trials in a series of 6 trial blocks regarding their three best (KR good) or three worst (KR poor) trials in the block, and were either aware (goodaware; poor-aware) or unaware (good-unaware, poor-unaware) of content in their KR display. The retention results showed the groups aware of their KR content demonstrated superior learning to the groups unaware of their KR content. These findings suggest that in addition to the motivational components of KR, awareness of the KR content directly impacted motor skill acquisition not whether KR was presented on good trials or poor trials. Ó 2012 Elsevier B.V. All rights reserved.
1. Introduction The practice factors facilitating the cognitive and motor processes requisite for motor learning are suggested to be modulated by the amount of practice completed by the performer as well as the ⇑ Corresponding author. Address: Department of Kinesiology, Brock University, St. Catharines, ON, Canada L2S 3A1. Tel.: +1 905 688 5550x3769; fax: +1 905 688 8364. E-mail address: [email protected] (J.T. Patterson). 0167-9457/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.humov.2012.04.004
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characteristics of the augmented feedback schedule (i.e., knowledge of results). Augmented feedback, or knowledge of results (KR) for our purposes, is identified as one practice variable in particular that has received nearly a century of investigation (e.g., Arps, 1920; Thorndike, 1927), and is often considered one of the most powerful practice variables impacting motor learning (see Salmoni, Schmidt, & Walter, 1984; Wulf & Shea, 2004 for respective reviews). Knowledge of results (KR) is defined as information provided to a learner upon completion of a motor response informing them of the success in achieving the motor task goal (Salmoni et al., 1984; Schmidt & Lee, 2011). Inquiries into understanding the impact of various KR schedules on motor learning have been theoretically guided by the guidance hypothesis, originally proposed by Salmoni et al. (1984). The guidance hypothesis emphasized the positive informational role of KR in guiding the performer to the goal response. Recent attention to the learning advantages associated with performers controlling their receipt of KR during skill acquisition has reinforced the important informational role of KR during motor skill learning (Chiviacowsky & Wulf, 2005; Patterson & Carter, 2010). The results from the self-controlled KR research have unequivocally supported this practice context as a beneficial practice factor facilitating motor skill acquisition. In fact, participants in a self-controlled KR context have demonstrated superior learning compared to those participants replicating the KR schedule of a self-controlled counterpart, but without the choice (i.e., yoked condition) (Chiviacowsky & Wulf, 2002, 2005; Patterson & Carter, 2010). The learning advantages of a self-controlled KR context have recently been extended to contexts of multi-task learning (Patterson & Carter, 2010). Collectively, the findings from the self-controlled KR research have also highlighted an important motivational role of KR in facilitating skill acquisition (see Wulf, 2007 for review), not previously emphasized in KR contexts controlled by the researcher (see Salmoni et al., 1984; Wulf & Shea, 2004 for reviews). That is, performers in a self-controlled KR condition have reported a preference for requesting KR after they perceived a good (e.g., successful) rather than a poor (e.g., unsuccessful) motor trial during the acquisition period (Chiviacowsky & Wulf, 2002, 2005). Preference for KR after perceived good (e.g., successful) rather than poor (e.g., unsuccessful) responses is believed to highlight the performer’s awareness of their motor performance (Chiviacowsky & Wulf, 2002; also see Wulf, 2007 for review) and their subsequent motivation to engage in the processes required to repeat a successful motor response rather than those processes required to correct an unsuccessful motor response (Chiviacowsky & Wulf, 2002; Wulf, 2007). This reported finding is rather curious since historically, the perceived role of KR was to provide the learner the necessary information required to resolve the difference (e.g., movement error) between the intended movement and the actual movement outcome (i.e., strengthen the recognition schema based on Schmidt, 1975). In a follow-up experiment, Chiviacowsky and Wulf (2007) directly examined whether providing KR to performers after relatively good compared to poor trials would in fact prove advantageous for motor skill learning. The results of this study did in fact confirm and add support to the notion of providing the learner KR after relatively good compared to relatively poor trials during a defined acquisition period. These learning advantages have recently been extended to the older adult learner (Chiviacowsky, Wulf, Wally, & Borges, 2009). To account for these findings, providing KR based on relatively good trials has been speculated to increase the motivation of the participant to learn the task, that as a result, reinforces the cognitive processes required to reproduce the correct motor response on upcoming trials and subsequent learning (Badami, VaezMousavi, Wulf, & Namazizadeh, 2011; Chiviacowsky & Wulf, 2007; Lewthwaite & Wulf, 2010). In fact, the cognitive demands required to reproduce a correct response have proven to be less demanding and perhaps more desirable for the learner compared to the cognitive demands associated with correcting an error (Chiviacowsky & Wulf, 2002, 2005; Kohen, Dickinson, & Goodman, 2008). Although presenting KR after good trials compared to poor trials has generated a renewed interest in understanding the informational and motivational role of KR during motor skill acquisition (Lewthwaite & Wulf, 2010; also see Wulf, Shea, & Lewthwaite, 2010 for review), there is a caveat. Specifically, learners in these previous investigations were unaware the KR information they were receiving was in fact based on a pre-determined criteria set by the experimenter (i.e., receiving KR after only good or poor trials). Thus, it remains unclear whether being aware versus being unaware of the information in the KR display (e.g., good versus poor trials) would have differentially impacted motor skill acquisition. The purpose of the present experiment was to determine if being aware of the information in a KR display (i.e., KR exclusively based on good or poor trials) would differently impact learning
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compared to being unaware of the KR information. Based on the existing research, we predicted if the information contained in the KR display (i.e., KR presented on only good or poor trials) was the most influential factor facilitating skill acquisition, independent of awareness, those receiving KR on relatively good trials would demonstrate superior learning compared to those provided KR on poor trials (Badami et al., 2011; Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). However, if learning was a function of participant awareness of the information in their KR display (i.e., good or poor trials), we predicted the groups aware of their KR content would perform superior to those groups unaware of their KR content in the retention period. 2. Methods 2.1. Participants Fifty-six younger adults (28 female and 28 male, M age = 22, SD = 1.15) participated in the experiment. All participants provided informed consent before participation, were naïve to the purposes of the experiment and received course credit upon completion of the experiment. 2.2. Apparatus and task All participants were informed the goal of the motor task was to push and release a low-friction slider along a horizontal rail to a pre-determined goal distance of 133 cm. For this task, participants were in a seated position and were required to grasp the slider handle (knob shaped) with a transverse palmar grip with their non-dominant hand. The slider was 12.1 cm (length) by 17.1 cm (height), weighed 455 g and had a large knob for the participants to grasp. Propelling the slider along the rail required the participant to slowly flex then quickly extend their elbow requiring minimal shoulder flexion. Participants completed a total of 72 trials during the acquisition period, and 12 no-KR trials in an immediate (15 - minute) and delayed (one day later) retention test, respectively. For all acquisition and retention trials, participant’s vision of the goal distance (133 cm) and the outcome of their motor response were occluded by a physical barrier. During all acquisition and retention trials, participants were also required to wear industrial earmuffs to prevent the receipt of auditory feedback regarding the movement of the slider along the rail. A customized software program collected the dependent variables of interest (|CE|, VE) and controlled the temporal components of the experiment as well as the presentation of the experimental stimuli. The software program operated on a desktop computer with a 19-inch liquid crystal display monitor with a refresh rate of 60 Hz. The total length of the horizontal rail was 261.6 cm. The first 50 cm of the rail was defined as the pre-response area where participants were required to push and release the slider. A wooden barrier (78.7 cm 45.7 cm) was located at the 50 cm mark of the rail with the purpose of occluding the participant’s vision of the target position and subsequent results of their motor response. The wooden barrier contained an opening, slightly larger than the slider, to allow unobstructed travel along the rail, yet occluding the participant’s vision of the movement of the slider. The apparatus was secured to a customized table that was 243.8 cm (length) by 50.2 cm (width) by 60.3 cm (height). The total length of the linear side was 261.6 cm with the linear slide located 30.5 cm above the table surface. Upon completion of every motor action, the end location of the slider was detected by the Vernier Motion Detector 2, horizontally mounted to the end of the horizontal rail, operating at an ultrasound frequency of 50 kHz with an accuracy of ±2 mm within a range of 0.5 to 6 m. The Vernier Motion Detector was connected to a Vernier LabProÒ that collected the position data of the slider. All experimental stimuli (i.e., instructions, KR) were presented on a 19-inch liquid crystal monitor located 50 cm to the participant’s right side. 2.3. Procedure All participants were randomly assigned to one of the four following experimental conditions: Good trials – Aware (G-A), Poor trials-Aware (P-A), Good trials – Unaware (G-U) or
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Poor trials-Unaware (P-U). Similar to the experimental procedure of Chiviacowsky and Wulf (2007) and Chiviacowsky et al. (2009), participants received KR based on three of every six trials completed during the acquisition period. Participants completed a total of 72 acquisition trials resulting in KR being presented on a total of 36 trials during the acquisition period. The information contained in the three-trial KR display was either based on participants three best (good trials: G-A, G-U) or three worst (poor: P-A, P-U) trials within the just completed six trial block resulting in a relative KR frequency of 50%. The information content displayed to participants as a function of experimental condition was determined by the customized software program. To examine whether being aware or unaware of the information contained within the KR display would differentially modulate motor skill acquisition, a group of participants in the present experiment were explicitly informed their KR presented would be based on either their three best or three worst trials of the six trial block. For example, participants in the G-A (Good-Aware) condition would view the following message on the computer screen upon completion of every 6 trial acquisition block without KR: the task goal: 133 cm, and the following statement ‘your three best trials were 125 cm, 130 cm and 129 cm. Conversely, participants in the G-U (Good-Unaware) condition were informed they would receive KR on three of the six trials completed in the block. The KR display consisted of the task goal, and a summary of their three best trials of the six trial block. However participants were unaware the KR they were receiving was in fact based on their three best trials of the six trial block. The procedures for the unaware conditions in the present experiment were consistent with the procedure for the unaware participants in previous research (Chiviacowsky & Wulf, 2007). Finally, the procedure for the G-A was similar for the P-A condition, as was the procedure for the G-U and P-U, other than the content of the KR display was based on the three worst rather than the three best trials of the six trial block. The acquisition period began with participants reading through a series of instruction screens outlining the goal of the motor task and their respective KR condition. Upon completion of the instruction screens, participants then completed two familiarization trials of the motor task. All questions were answered at that time. A typical experimental trial began the same way for all experimental conditions with the word ‘Ready?’ in the center of the computer screen for a total of 3 s. Following this screen, participants viewed the word ‘Go’ in the centre of the computer screen in black, Arial, 72 pt font, signaling the participants to complete their motor response within 5 s. Upon completion of the trial, participants were prompted by a ‘Trial Complete’ message for 3 s, followed by the ‘Ready?’ screen for 3 s. Upon the completion of six acquisition trials, participants received KR, based on their respective experimental condition for three of their just completed six trials for 5 s. Participants completed a total of 72 acquisition trials resulting in participants receiving KR a total of 12 times during the acquisition period. To control for participants ease in associating their task-related intrinsic feedback to the associated KR trials completed later (e.g., trials 6) versus earlier in the block (e.g., trial 1), the trial numbers for the presented KR trials were not included in the KR display. Upon completion of the acquisition period, participants in the aware and unaware conditions were asked to complete a paper and pencil questionnaire requiring them to report whether they were motivated to learn the motor task as a function of the feedback they received throughout the acquisition period. Recent research suggests the information contained in a KR display does differentially impact motivation of participants and subsequent motor skill acquisition (see Lewthwaite & Wulf, 2009). Participants in the present experiment were also asked that if they had a choice, when would they have preferred to receive KR (e.g., good trials, poor trials, randomly, etc.). Previous research has shown that when queried, learners report a preference for KR after perceived good compared to poor trials (Chiviacowsky & Wulf, 2002, 2005). For participants in the unaware conditions, we were interested in determining whether these participants were in fact unaware of the content within their KR display. Thus, participants in the unaware KR conditions were asked to self-report the information they perceived was being presented in their KR display (e.g., good trials, poor trials, good and poor trials equally, randomly, etc.). Completion of the questionnaire was approximately 15 minutes. To assess the relatively permanent changes in performance as a function of participants KR condition, all participants completed 12 no-KR trials in an immediate (15 min after completion of the last acquisition trial) and delayed (24 hrs after the last acquisition trial) retention test, respectively. No KR was presented during the immediate or delayed retention test.
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2.4. Data analyses The dependent measures of interest for the acquisition and retention periods of the experiment were absolute constant error (|CE|) and variable error (VE). |CE| was used as a measure of performance accuracy while VE was used as an index of performance consistency (Schmidt & Lee, 2011). For the acquisition phase, the means for |CE| and VE were grouped separately into 12 blocks of six trials, respectively. For acquisition, |CE| and VE were analyzed separately in a 2 (Feedback Type: good, poor) 2 (Awareness: aware, unaware) 12 (Blocks) ANOVA with repeated measures on the last factor. For the retention tests, |CE| and VE were collapsed into one block of 12 trials for each retention test (immediate and delayed) and subjected to a 2 (Feedback Type: good, poor) 2 (Awareness: aware, unaware) 2 (Blocks: immediate, delayed retention test) ANOVA with repeated measures on the last factor. A significance level of p < .05 was used for all statistical analyses and statistically significant interactions involving more than two means were analyzed using the Tukey’s HSD post hoc analysis. Effect sizes were reported as partial eta squared (g2p ) where appropriate. 3. Results 3.1. Acquisition 3.1.1. Absolute constant error (|CE|) |CE| scores in the acquisition period for the experimental conditions are displayed on the left side of Fig. 1 for the experimental conditions. The analysis of |CE| showed a main effect for block, F(11, 572) = 48.97, p < .05, g2p = .49. The results of the post hoc analysis showed that block 1 and 2 demonstrated greater |CE| than blocks 3–12, and block 3 demonstrated greater |CE| than blocks 1, 2, 7, 10, 11 and 12. All other main effects and interactions were not statistically significant, p > .05. 3.1.2. Variable error (VE) VE for the experimental conditions are located on the left side of Fig. 2. The analysis of VE also revealed a main effect for block, F(11, 572) = 3.88, p < .05, g2p = .07. The post hoc analysis indicated block 1 demonstrated greater VE compared to blocks 3–12. All other main effects and interactions were not statistically significant, p > .05.
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Fig. 1. Absolute constant error (|CE|) for the experimental conditions for the acquisition and retention portion of the experiment.
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30 Good - Aware Good - Unaware
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Fig. 2. Variable error (VE) for the experimental conditions for the acquisition and retention portion of the experiment.
3.2. Retention 3.2.1. Absolute constant error (|CE|) The |CE| measures for the retention period are presented on the right side of Fig. 1 for the experimental conditions. The analysis of |CE| showed a main effect for awareness, F(1, 52) = 5.94, p < .05, g2p = .10, and retention test, F(1, 52) = 10.91, p < .05, g2p = 0.17. Participants aware of their KR content, independent of the type of content (M = 16.9, SE = 1.5) demonstrated less |CE| compared to those participants unaware of their KR content type (M = 22.2, SE = 1.5). Further, participants performed with less |CE| in the immediate (M = 17.5, SE = 0.9) compared to the delayed retention test (M = 21.7, SE = 1.5). 3.2.2. Variable error (VE) The VE measures for the retention period are presented on the right side of Fig. 2 for the experimental conditions. Analysis of VE in the retention period showed a main effect for awareness, F(1, 52) = 14.38, p < .05, g2p = 0.22. Participants aware of their KR content demonstrated less VE (M = 14.0, SE = .90) compared to those participants not aware (M = 18.8, SE = 0.9). All other main effects and interactions were not statistically significant at p < .05. 3.2.3. Self-reported measures of KR content awareness Our primary interest in the present experiment was to determine if being aware of the KR content would differentially impact learning compared to not being aware. Thus, to determine if being aware was a factor in facilitating motor skill acquisition, we needed to confirm that all participants in the unaware conditions (G-U and P-U) were in fact unaware of their KR content during the acquisition period. When asked to self-report their perception of the KR content during the acquisition period (e.g., good trials, poor trials, randomly, etc.), none of the participants in the GU and PU KR conditions reported receiving KR on trials that were in fact consistent with their experimental condition (e.g., only good or poor trials, respectfully). In fact, 57% (8/12) of participants in the GU condition and 64% (9/12) participants in the PU perceived that KR was being provided ‘randomly’ (see Table 1). We were also interested in determining whether the KR presented to participants during the acquisition period facilitated their motivation to learning the motor task. All participants (14/14) in the G-A, 79% (11/14) in the P-A, and 93% (13/14) in the P-U and G-U conditions, respectively, reported the KR they received during the acquisition period facilitated their motivation to learn the task. Finally, all participants were asked to self-report, that if they had the choice, when they would have preferred to receive KR. Only 36% (5/14) of participants in the G-A and G-U would have preferred to receive KR after good trials. For the P-A condition, only 14% (2/14) and 7% (1/14) in the P-U would have preferred to request KR on poor trials, similar to their experimental condition. Finally, 71% (10/14)
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Table 1 Introspective reports of participants as a function of feedback type (good/poor trials) and awareness of feedback type (aware/ unaware) regarding feedback scheduling. Group Good-aware
Poor-aware
Good-unaware
Poor-unaware
Did the feedback presented to you facilitate your motivation to learn the motor task? Number of responses Yes 14 11 13 13 No – 3 1 1 If you had the choice, when would you have preferred to receive feedback? Number of responses After only successful (e.g., good) trials 5 4 5 10 After only unsuccessful (e.g., poor) trials 2 2 4 1 Randomly 2 1 – – After good and poor trials equally 3 6 5 3 Other 2 1 – – During your practice of the motor task, you were presented feedback on certain trials. Did you perceive the feedback being presented to you was: Number of responses Good-Unaware conditions Poor-Unaware conditions After only successful (e.g., good) trials – 2 After only unsuccessful (e.g., poor) trials – – Randomly 8 9 After good and poor trials equally 4 3 other 2 –
of participants in the P-U condition and 29% (4/14) in the P-A condition preferred to receive KR after good trials (see Table 1). 4. Discussion Previous research examining the learning advantages of self-controlled KR schedules have reported a deliberate preference from participants in a self-controlled KR condition to prefer KR after perceived ‘good’ compared to ‘poor’ trials (Chiviacowsky & Wulf, 2002; Patterson & Carter, 2010). This finding has been extended in externally defined KR contexts whereby providing KR on relatively good rather than relatively poor trials has proven superior for motor skill learning (Badami et al., 2011; Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). Yet, in these previous studies, participants were not explicitly made aware of the KR they were receiving (i.e., good trials or poor trials). Further, it was only assumed that participants in their respective KR condition were in fact unaware of their KR content (e.g., good trials, poor trials). To address this limitation, the purpose of the present experiment was to extend this line of inquiry by examining whether or not participants awareness of their KR information, that is, based on relatively good or poor trials would differentially impact motor skill learning. Based on our theoretical understanding of KR during motor learning (Salmoni et al., 1984; Schmidt & Lee, 2011; Wulf & Shea, 2004) we suggested that if being aware of the KR content was the primary determinant facilitating motor skill learning, the groups awareness of their KR content would perform similarly in the retention period, yet superior to those groups unaware of their KR content. However, if the information within the KR display was the factor impacting motor skill learning, independent of awareness, we expected providing KR on relatively good compared to relatively poor trials would prove superior for learning, consistent with the existing research (Badami et al., 2011; Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). The results of the present experiment did not replicate and subsequently challenges the findings of previous research (i.e. Badami et al., 2011; Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). Our results suggest that participant’s awareness of their KR content was a factor modulating motor skill acquisition, not whether the KR was provided on good or poor trials. A discussion of these findings follows. The results from previous inquiry have suggested that providing KR after relatively good trials facilitates superior learning compared to providing KR after relatively poor trials (Badami et al., 2011;
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Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). Importantly, participants in these experiments were unaware of the content within their KR display. Contrary to this research, the results of the present experiment challenge earlier findings by showing that learning was superior when participants were aware compared to unaware of their KR content. We offer two possible reasons for these findings. First, the differences in learning between the aware and unaware conditions cannot be accounted for by the self-reported levels of motivation from participants required to learn the task. Our results do suggest that organizing KR information for the learner in a summary display according to a meaningful referent (i.e., only KR on good trials or poor trials) facilitated the efficiency of processing KR, to the advantage of learning. Presenting KR as a summary for a portion of the acquisition trials does share similarities to earlier research efforts examining the presentation of KR as summary (Guadagnoli, Dornier, & Tandy, 1996). In the summary KR literature, the learner is withheld KR for a pre-determined amount of no-KR trials (e.g., 5 trials), which is then followed by presenting KR for all the no-KR trials completed in the block in a summary format (e.g., 5 trials; 100% relative frequency). In a traditional summary KR display, the learner is assumed to utilize the KR in the summary display to dissociate the good from the poor motor responses as a method of facilitating the planning of upcoming motor actions. Based on the results of the present experiment, we suggest that modifying a summary KR display such that a meaningful referent is applied to the KR information (e.g., KR on good or poor trials) optimizes the efficiency and effectiveness of the learners processing of the KR, subsequently facilitating motor planning and as a consequence, learning. This notion is resonant with relatively recent theoretical understandings of the role of KR during skill acquisition that suggests KR should be presented in a manner that does not provide too much or too little challenge to the learner’s information processing (Guadagnoli & Lee, 2004). In summary, our results suggest that explicitly grouping the KR trials as a function of the participant’s performance (e.g., grouping the most accurate or least accurate trials) increased the informational value of the KR, independent of whether the KR was based on good or poor trials throughout the acquisition period, to the advantage of learning as evidenced by superior movement accuracy (|CE|) and movement stability (VE) in the retention period. Further research is required to determine the utility of organizing KR for the learner according to a pre-determined referent. These further inquires would determine whether meaningful referents utilized for organizing KR for the learner, such as ordering motor performance trials from good to poor, or vice versa, would further strengthen the informational and motivational role of KR during motor skill acquisition. Our second interpretation of the results is related to the presumed novelty of the motor task. We suggest the novelty of the present motor task, based on the fact participants were not expected to have any pre-existing knowledge or experience, compared to the caveat highlighted in the motor tasks utilized in previous research (e.g., Chiviacwosky & Chiviacowsky et al., 2009; Wulf, 2007), may have contributed to the present findings, and a failure to replicate past research. For example, the conclusions from previous research were based on a motor task that required participants to toss beanbags at a pre-defined target using their non-dominant hand (Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). Chiviacowsky and Wulf (2007) cautioned that although the task was performed with the non-dominant hand, pre-existing knowledge and experience with similar tasks may have compromised the novelty of the task and contributed to participants’ ability to accurately assess their movement outcome. Chiviacowsky and Wulf (2007) suggested that future research utilizing motor tasks where participants lacked previous experience was required to examine the generalizability of the findings. Thus, we suggest the novelty of the motor task utilized in the present experiment, compared to previous investigations (e.g., Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009) contributed to the failure of our unaware conditions to perform similarly to the unaware conditions in previous research. In fact, an earlier review by Wulf and Shea (2002) highlights the modulating effects of motor task characteristics on differentiating the subsequent effectiveness of a specific practice condition (e.g., feedback). Similar to Chiviacowsky and Wulf (2007), we recommend further inquiry into examining the interaction of awareness of the feedback content (e.g., KR based on most accurate compared to least accurate trials) and the characteristics of the motor task, such as type (e.g., continuous, serial tasks) and complexity. Our results are however commensurate with other lines of KR inquiry where learning was superior for participants aware compared to unaware of the basis for the information within their KR display. For example, in a bandwidth KR protocol, participants are aware that if their motor performance falls within a pre-defined error-tolerance (e.g., good trial), their augmented
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feedback is qualitative (e.g., good). However if their performance falls outside the error tolerance (e.g., bandwidth) (e.g., poor trial), the precision of the KR content is increased such that quantitative KR is provided to the leaner (e.g. amount and direction of error). Contrary to previous research, the results of the present study suggest that being aware of KR content has a greater impact on learner compared to whether the KR is based on good or poor trials. To conclude with certainty that awareness of the KR information, independent of the KR information itself, was the factor facilitating skill acquisition, participants in the good-unaware and poor-unaware conditions were asked to self-report their perception of when they thought they were being provided KR. Importantly, the results from this questionnaire showed that none of the participants in G-U condition reported receiving KR on only good trials, and none of the participants in the P-U condition reported receiving KR on poor trials only. Based on this data, we can conclude that none of the participants in the unaware conditions had the same explicit knowledge of their KR information as those participants in the aware conditions. In fact, a majority of participants in the good-unaware (57%) and poor-unaware (64%) conditions reported receiving KR on random trials throughout the acquisition period. In summary, the results of the questionnaire lend further support to the notion that being aware of the information within the KR display had a greater impact on motor skill acquisition compared to the type of information in the KR display alone, as suggested by previous research. We further examined the questionnaire data to determine whether participant’s motivation to learn the motor task was differentially modulated by the KR condition experienced during the acquisition. In fact, when participant motivation is enhanced as a function of KR, learners are predicted to practice with more seriousness resulting in an indirect impact on learning (Schmidt & Lee, 2011). Thus, the motivational role of KR during skill acquisition was previously believed to be a performance phenomenon whereby the effects were only present when KR was available (see Schmidt & Lee, 2011 for review). However, more recent evidence suggests that in fact the motivational role of KR during skill acquisition has a direct, rather than indirect, impact on learning (Lewthwaite & Wulf, 2009). Thus, to examine whether participants motivation to learn the task was differentially impacted by the KR condition experienced during the acquisition, all participants were asked to self-report via a paper and pencil questionnaire, if the feedback presented to them throughout the acquisition period motivated them to learn the motor task (e.g., circle yes or no). Overall, 91% of the participants (51/56) who participated in the experiment reported the KR they received during the acquisition period motivated them to learn the motor task. Upon closer inspection, 76% (11/14) of participants in the poor-aware condition reported their KR facilitated their motivation to learn the task compared to the good-aware (100%), poor-unaware and good-unaware conditions (both 93%, respectively). However, when collapsing across information type, the self-report measures from the aware and unaware participants, reported a similar amount of participants in the unaware (93% of participants) and aware condition (88% of participants) were motivated to learn the motor task as a function of their KR condition during the acquisition period. Although most participants in the aware and unaware condition were motivated to learn the motor task as a function of their KR condition, these findings do not account for the motor performance differences between aware and unaware conditions in the retention portion of the experiment. However, our findings do suggest that perceived motivation was not the singular factor dissociating the learning differences between the aware and unaware KR conditions. Further research is required to delineate the direct and indirect motivational role of KR during skill acquisition when providing KR on relatively good versus poor trials. The results from previous findings showed that when participants were unaware of the type of information in the KR display (i.e., good or poor trials), presenting KR on only good trials for 50% of the acquisition trials was more advantageous for learning compared to presenting KR on only poor trials (Badami et al., 2011; Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). The results of the present experiment challenge these findings by suggesting that awareness of the KR content has a greater impact on learning compared to receiving KR on either good or poor trials for 50% of the acquisition trials. However, further research is required to determine whether awareness is modulated by the relative frequency (e.g., providing KR on more than or less than 50% of the acquisition trials) of KR during motor skill acquisition.
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5. Conclusion In conclusion, the results from the present experiment suggest that being aware of the information in a summary KR display (good or poor trials), was more influential for motor skill learning compared to being unaware of the information in the KR display. Unlike previous research, our results were independent of the information within the KR display (e.g., KR based on good or poor trials). As a result, our findings challenge the findings from previous inquiry by suggesting that awareness of KR content had a greater impact on learning compared to receiving KR on either good or bad trials. Our results further suggest awareness facilitated a meaningful referent for the participants in facilitating their motor performance on subsequent motor trials (i.e. repeat a successful trial or correct an incorrect trial). Further research is recommended to examine the utility of awareness and organization of KR according to meaningful referents on the learners information processing and subsequent motor planning and learning. From a practical standpoint, our results suggest that a learner’s awareness of KR content could have a greater impact on learning compared to presenting KR on good or poor trials in various contexts such as vocational, recreational and rehabilitation settings. References Arps, G. F. (1920). Work with knowledge of results versus work without knowledge of results. Psychological Monographs, 28, 1–41. Badami, R., VaezMousavi, M., Wulf, G., & Namazizadeh, M. (2011). Feedback after good versus poor trials affects intrinsic motivation. Research Quarterly for Exercise and Sport, 82, 360–364. Chiviacowsky, S., & Wulf, G. (2002). Self-controlled feedback: Does it enhance learning because performers get feedback when they need it? Research Quarterly for Exercise and Sport, 73, 408–415. Chiviacowsky, S., & Wulf, G. (2005). Self-controlled feedback is effective if it is based on the learner’s performance. Research Quarterly for Exercise and Sport, 76, 42–48. Chiviacowsky, S., & Wulf, G. (2007). Feedback after good trials enhances learning. Research Quarterly for Exercise and Sport, 78, 40–47. Chiviacowsky, S., Wulf, G., Wally, R., & Borges, T. (2009). Knowledge of results after good trials enhances learning in older adults. Research Quarterly for Exercise and Sport, 80, 663–668. Guadagnoli, M. A., Dornier, L. A., & Tandy, R. D. (1996). Optimal length for summary knowledge of results: The influence of taskrelated experience and complexity. Research Quarterly for Exercise and Sport, 67, 239–248. Guadagnoli, M. A., & Lee, T. D. (2004). Challenge point: A framework for conceptualizing the effects of various practice conditions in motor learning. Journal of Motor Behaviour, 36, 212–224. Kohen, J. D., Dickinson, J., & Goodman, D. (2008). Cognitive demands of error processing. Psychological Reports, 102, 532–538. Lewthwaite, R., & Wulf, G. (2010). Social-comparative feedback affects motor skill learning. The Quarterly Journal of Experimental Psychology, 63, 738–749. Patterson, J. T., & Carter, M. J. (2010). Learner regulated knowledge of results during the acquisition of multiple timing goals. Human Movement Science, 29, 214–217. Salmoni, A. W., Schmidt, R. A., & Walter, C. B. (1984). Knowledge of results and motor learning: A review and critical reappraisal. Psychological Bulletin, 95, 355–386. Schmidt, R. A. (1975). A schema theory of discrete motor skill learning. Psychological Review, 82, 225–260. Schmidt, R. A., & Lee, T. D. (2011). Motor control and learning: A behavioral emphasis (5th ed.). Champaign, IL: Human Kinetics. Thorndike, D. L. (1927). The law of effect. American Journal of Psychology, 39, 212–222. Wulf, G., & Shea, C. H. (2004). Understanding the role of augmented feedback: The good, the bad, and the ugly. In A. M. Williams & N. J. Hodges (Eds.), Skill acquisition in sport: Research, theory and practice (pp. 121–144). London: Routledge. Wulf, G., & Shea, C. H. (2002). Principles derived from the study of simple skills do not generalize to complex skill learning. Psychonomic Bulletin & Review, 9, 185–211. Wulf, G. (2007). Self-controlled practice enhances motor learning: Implications for physiotherapy. Physiotherapy, 93, 96–101. Wulf, G., Shea, C., & Lewthwaite, R. (2010). Motor skill learning and performance: A review of influential factors. Medical Education, 44, 75–84.
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Human Movement Science journal homepage: www.elsevier.com/locate/humov
Knowing the good from the bad: Does being aware of KR content matter? Jae T. Patterson ⇑, Jana Azizieh Department of Kinesiology, Brock University, Canada
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Article history: Available online 8 June 2012 PsycINFO classification: 4.030 5.040 Keywords: Knowledge of results Motor learning Practice Motor skills
a b s t r a c t Previous researchers have suggested that providing KR based on only successful (i.e., good trials) trials enhances learning compared to providing KR on unsuccessful trials (i.e., poor trials). However, the learners were unaware the content of their KR display was based entirely on their successful or unsuccessful trials. Thus, the purpose of the present experiment was to determine whether learning after providing KR after relatively good trials would persist if participants were aware of their KR content. All participants propelled a slider with their non-dominant hand to a pre-determined distance on a linear slide. Participant’s vision was occluded before, during and after their motor action. Similar to previous research, all participants were provided KR on three trials in a series of 6 trial blocks regarding their three best (KR good) or three worst (KR poor) trials in the block, and were either aware (goodaware; poor-aware) or unaware (good-unaware, poor-unaware) of content in their KR display. The retention results showed the groups aware of their KR content demonstrated superior learning to the groups unaware of their KR content. These findings suggest that in addition to the motivational components of KR, awareness of the KR content directly impacted motor skill acquisition not whether KR was presented on good trials or poor trials. Ó 2012 Elsevier B.V. All rights reserved.
1. Introduction The practice factors facilitating the cognitive and motor processes requisite for motor learning are suggested to be modulated by the amount of practice completed by the performer as well as the ⇑ Corresponding author. Address: Department of Kinesiology, Brock University, St. Catharines, ON, Canada L2S 3A1. Tel.: +1 905 688 5550x3769; fax: +1 905 688 8364. E-mail address: [email protected] (J.T. Patterson). 0167-9457/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.humov.2012.04.004
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characteristics of the augmented feedback schedule (i.e., knowledge of results). Augmented feedback, or knowledge of results (KR) for our purposes, is identified as one practice variable in particular that has received nearly a century of investigation (e.g., Arps, 1920; Thorndike, 1927), and is often considered one of the most powerful practice variables impacting motor learning (see Salmoni, Schmidt, & Walter, 1984; Wulf & Shea, 2004 for respective reviews). Knowledge of results (KR) is defined as information provided to a learner upon completion of a motor response informing them of the success in achieving the motor task goal (Salmoni et al., 1984; Schmidt & Lee, 2011). Inquiries into understanding the impact of various KR schedules on motor learning have been theoretically guided by the guidance hypothesis, originally proposed by Salmoni et al. (1984). The guidance hypothesis emphasized the positive informational role of KR in guiding the performer to the goal response. Recent attention to the learning advantages associated with performers controlling their receipt of KR during skill acquisition has reinforced the important informational role of KR during motor skill learning (Chiviacowsky & Wulf, 2005; Patterson & Carter, 2010). The results from the self-controlled KR research have unequivocally supported this practice context as a beneficial practice factor facilitating motor skill acquisition. In fact, participants in a self-controlled KR context have demonstrated superior learning compared to those participants replicating the KR schedule of a self-controlled counterpart, but without the choice (i.e., yoked condition) (Chiviacowsky & Wulf, 2002, 2005; Patterson & Carter, 2010). The learning advantages of a self-controlled KR context have recently been extended to contexts of multi-task learning (Patterson & Carter, 2010). Collectively, the findings from the self-controlled KR research have also highlighted an important motivational role of KR in facilitating skill acquisition (see Wulf, 2007 for review), not previously emphasized in KR contexts controlled by the researcher (see Salmoni et al., 1984; Wulf & Shea, 2004 for reviews). That is, performers in a self-controlled KR condition have reported a preference for requesting KR after they perceived a good (e.g., successful) rather than a poor (e.g., unsuccessful) motor trial during the acquisition period (Chiviacowsky & Wulf, 2002, 2005). Preference for KR after perceived good (e.g., successful) rather than poor (e.g., unsuccessful) responses is believed to highlight the performer’s awareness of their motor performance (Chiviacowsky & Wulf, 2002; also see Wulf, 2007 for review) and their subsequent motivation to engage in the processes required to repeat a successful motor response rather than those processes required to correct an unsuccessful motor response (Chiviacowsky & Wulf, 2002; Wulf, 2007). This reported finding is rather curious since historically, the perceived role of KR was to provide the learner the necessary information required to resolve the difference (e.g., movement error) between the intended movement and the actual movement outcome (i.e., strengthen the recognition schema based on Schmidt, 1975). In a follow-up experiment, Chiviacowsky and Wulf (2007) directly examined whether providing KR to performers after relatively good compared to poor trials would in fact prove advantageous for motor skill learning. The results of this study did in fact confirm and add support to the notion of providing the learner KR after relatively good compared to relatively poor trials during a defined acquisition period. These learning advantages have recently been extended to the older adult learner (Chiviacowsky, Wulf, Wally, & Borges, 2009). To account for these findings, providing KR based on relatively good trials has been speculated to increase the motivation of the participant to learn the task, that as a result, reinforces the cognitive processes required to reproduce the correct motor response on upcoming trials and subsequent learning (Badami, VaezMousavi, Wulf, & Namazizadeh, 2011; Chiviacowsky & Wulf, 2007; Lewthwaite & Wulf, 2010). In fact, the cognitive demands required to reproduce a correct response have proven to be less demanding and perhaps more desirable for the learner compared to the cognitive demands associated with correcting an error (Chiviacowsky & Wulf, 2002, 2005; Kohen, Dickinson, & Goodman, 2008). Although presenting KR after good trials compared to poor trials has generated a renewed interest in understanding the informational and motivational role of KR during motor skill acquisition (Lewthwaite & Wulf, 2010; also see Wulf, Shea, & Lewthwaite, 2010 for review), there is a caveat. Specifically, learners in these previous investigations were unaware the KR information they were receiving was in fact based on a pre-determined criteria set by the experimenter (i.e., receiving KR after only good or poor trials). Thus, it remains unclear whether being aware versus being unaware of the information in the KR display (e.g., good versus poor trials) would have differentially impacted motor skill acquisition. The purpose of the present experiment was to determine if being aware of the information in a KR display (i.e., KR exclusively based on good or poor trials) would differently impact learning
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compared to being unaware of the KR information. Based on the existing research, we predicted if the information contained in the KR display (i.e., KR presented on only good or poor trials) was the most influential factor facilitating skill acquisition, independent of awareness, those receiving KR on relatively good trials would demonstrate superior learning compared to those provided KR on poor trials (Badami et al., 2011; Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). However, if learning was a function of participant awareness of the information in their KR display (i.e., good or poor trials), we predicted the groups aware of their KR content would perform superior to those groups unaware of their KR content in the retention period. 2. Methods 2.1. Participants Fifty-six younger adults (28 female and 28 male, M age = 22, SD = 1.15) participated in the experiment. All participants provided informed consent before participation, were naïve to the purposes of the experiment and received course credit upon completion of the experiment. 2.2. Apparatus and task All participants were informed the goal of the motor task was to push and release a low-friction slider along a horizontal rail to a pre-determined goal distance of 133 cm. For this task, participants were in a seated position and were required to grasp the slider handle (knob shaped) with a transverse palmar grip with their non-dominant hand. The slider was 12.1 cm (length) by 17.1 cm (height), weighed 455 g and had a large knob for the participants to grasp. Propelling the slider along the rail required the participant to slowly flex then quickly extend their elbow requiring minimal shoulder flexion. Participants completed a total of 72 trials during the acquisition period, and 12 no-KR trials in an immediate (15 - minute) and delayed (one day later) retention test, respectively. For all acquisition and retention trials, participant’s vision of the goal distance (133 cm) and the outcome of their motor response were occluded by a physical barrier. During all acquisition and retention trials, participants were also required to wear industrial earmuffs to prevent the receipt of auditory feedback regarding the movement of the slider along the rail. A customized software program collected the dependent variables of interest (|CE|, VE) and controlled the temporal components of the experiment as well as the presentation of the experimental stimuli. The software program operated on a desktop computer with a 19-inch liquid crystal display monitor with a refresh rate of 60 Hz. The total length of the horizontal rail was 261.6 cm. The first 50 cm of the rail was defined as the pre-response area where participants were required to push and release the slider. A wooden barrier (78.7 cm 45.7 cm) was located at the 50 cm mark of the rail with the purpose of occluding the participant’s vision of the target position and subsequent results of their motor response. The wooden barrier contained an opening, slightly larger than the slider, to allow unobstructed travel along the rail, yet occluding the participant’s vision of the movement of the slider. The apparatus was secured to a customized table that was 243.8 cm (length) by 50.2 cm (width) by 60.3 cm (height). The total length of the linear side was 261.6 cm with the linear slide located 30.5 cm above the table surface. Upon completion of every motor action, the end location of the slider was detected by the Vernier Motion Detector 2, horizontally mounted to the end of the horizontal rail, operating at an ultrasound frequency of 50 kHz with an accuracy of ±2 mm within a range of 0.5 to 6 m. The Vernier Motion Detector was connected to a Vernier LabProÒ that collected the position data of the slider. All experimental stimuli (i.e., instructions, KR) were presented on a 19-inch liquid crystal monitor located 50 cm to the participant’s right side. 2.3. Procedure All participants were randomly assigned to one of the four following experimental conditions: Good trials – Aware (G-A), Poor trials-Aware (P-A), Good trials – Unaware (G-U) or
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Poor trials-Unaware (P-U). Similar to the experimental procedure of Chiviacowsky and Wulf (2007) and Chiviacowsky et al. (2009), participants received KR based on three of every six trials completed during the acquisition period. Participants completed a total of 72 acquisition trials resulting in KR being presented on a total of 36 trials during the acquisition period. The information contained in the three-trial KR display was either based on participants three best (good trials: G-A, G-U) or three worst (poor: P-A, P-U) trials within the just completed six trial block resulting in a relative KR frequency of 50%. The information content displayed to participants as a function of experimental condition was determined by the customized software program. To examine whether being aware or unaware of the information contained within the KR display would differentially modulate motor skill acquisition, a group of participants in the present experiment were explicitly informed their KR presented would be based on either their three best or three worst trials of the six trial block. For example, participants in the G-A (Good-Aware) condition would view the following message on the computer screen upon completion of every 6 trial acquisition block without KR: the task goal: 133 cm, and the following statement ‘your three best trials were 125 cm, 130 cm and 129 cm. Conversely, participants in the G-U (Good-Unaware) condition were informed they would receive KR on three of the six trials completed in the block. The KR display consisted of the task goal, and a summary of their three best trials of the six trial block. However participants were unaware the KR they were receiving was in fact based on their three best trials of the six trial block. The procedures for the unaware conditions in the present experiment were consistent with the procedure for the unaware participants in previous research (Chiviacowsky & Wulf, 2007). Finally, the procedure for the G-A was similar for the P-A condition, as was the procedure for the G-U and P-U, other than the content of the KR display was based on the three worst rather than the three best trials of the six trial block. The acquisition period began with participants reading through a series of instruction screens outlining the goal of the motor task and their respective KR condition. Upon completion of the instruction screens, participants then completed two familiarization trials of the motor task. All questions were answered at that time. A typical experimental trial began the same way for all experimental conditions with the word ‘Ready?’ in the center of the computer screen for a total of 3 s. Following this screen, participants viewed the word ‘Go’ in the centre of the computer screen in black, Arial, 72 pt font, signaling the participants to complete their motor response within 5 s. Upon completion of the trial, participants were prompted by a ‘Trial Complete’ message for 3 s, followed by the ‘Ready?’ screen for 3 s. Upon the completion of six acquisition trials, participants received KR, based on their respective experimental condition for three of their just completed six trials for 5 s. Participants completed a total of 72 acquisition trials resulting in participants receiving KR a total of 12 times during the acquisition period. To control for participants ease in associating their task-related intrinsic feedback to the associated KR trials completed later (e.g., trials 6) versus earlier in the block (e.g., trial 1), the trial numbers for the presented KR trials were not included in the KR display. Upon completion of the acquisition period, participants in the aware and unaware conditions were asked to complete a paper and pencil questionnaire requiring them to report whether they were motivated to learn the motor task as a function of the feedback they received throughout the acquisition period. Recent research suggests the information contained in a KR display does differentially impact motivation of participants and subsequent motor skill acquisition (see Lewthwaite & Wulf, 2009). Participants in the present experiment were also asked that if they had a choice, when would they have preferred to receive KR (e.g., good trials, poor trials, randomly, etc.). Previous research has shown that when queried, learners report a preference for KR after perceived good compared to poor trials (Chiviacowsky & Wulf, 2002, 2005). For participants in the unaware conditions, we were interested in determining whether these participants were in fact unaware of the content within their KR display. Thus, participants in the unaware KR conditions were asked to self-report the information they perceived was being presented in their KR display (e.g., good trials, poor trials, good and poor trials equally, randomly, etc.). Completion of the questionnaire was approximately 15 minutes. To assess the relatively permanent changes in performance as a function of participants KR condition, all participants completed 12 no-KR trials in an immediate (15 min after completion of the last acquisition trial) and delayed (24 hrs after the last acquisition trial) retention test, respectively. No KR was presented during the immediate or delayed retention test.
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2.4. Data analyses The dependent measures of interest for the acquisition and retention periods of the experiment were absolute constant error (|CE|) and variable error (VE). |CE| was used as a measure of performance accuracy while VE was used as an index of performance consistency (Schmidt & Lee, 2011). For the acquisition phase, the means for |CE| and VE were grouped separately into 12 blocks of six trials, respectively. For acquisition, |CE| and VE were analyzed separately in a 2 (Feedback Type: good, poor) 2 (Awareness: aware, unaware) 12 (Blocks) ANOVA with repeated measures on the last factor. For the retention tests, |CE| and VE were collapsed into one block of 12 trials for each retention test (immediate and delayed) and subjected to a 2 (Feedback Type: good, poor) 2 (Awareness: aware, unaware) 2 (Blocks: immediate, delayed retention test) ANOVA with repeated measures on the last factor. A significance level of p < .05 was used for all statistical analyses and statistically significant interactions involving more than two means were analyzed using the Tukey’s HSD post hoc analysis. Effect sizes were reported as partial eta squared (g2p ) where appropriate. 3. Results 3.1. Acquisition 3.1.1. Absolute constant error (|CE|) |CE| scores in the acquisition period for the experimental conditions are displayed on the left side of Fig. 1 for the experimental conditions. The analysis of |CE| showed a main effect for block, F(11, 572) = 48.97, p < .05, g2p = .49. The results of the post hoc analysis showed that block 1 and 2 demonstrated greater |CE| than blocks 3–12, and block 3 demonstrated greater |CE| than blocks 1, 2, 7, 10, 11 and 12. All other main effects and interactions were not statistically significant, p > .05. 3.1.2. Variable error (VE) VE for the experimental conditions are located on the left side of Fig. 2. The analysis of VE also revealed a main effect for block, F(11, 572) = 3.88, p < .05, g2p = .07. The post hoc analysis indicated block 1 demonstrated greater VE compared to blocks 3–12. All other main effects and interactions were not statistically significant, p > .05.
60 Good - Aware Good - Unaware
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Fig. 1. Absolute constant error (|CE|) for the experimental conditions for the acquisition and retention portion of the experiment.
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30 Good - Aware Good - Unaware
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Fig. 2. Variable error (VE) for the experimental conditions for the acquisition and retention portion of the experiment.
3.2. Retention 3.2.1. Absolute constant error (|CE|) The |CE| measures for the retention period are presented on the right side of Fig. 1 for the experimental conditions. The analysis of |CE| showed a main effect for awareness, F(1, 52) = 5.94, p < .05, g2p = .10, and retention test, F(1, 52) = 10.91, p < .05, g2p = 0.17. Participants aware of their KR content, independent of the type of content (M = 16.9, SE = 1.5) demonstrated less |CE| compared to those participants unaware of their KR content type (M = 22.2, SE = 1.5). Further, participants performed with less |CE| in the immediate (M = 17.5, SE = 0.9) compared to the delayed retention test (M = 21.7, SE = 1.5). 3.2.2. Variable error (VE) The VE measures for the retention period are presented on the right side of Fig. 2 for the experimental conditions. Analysis of VE in the retention period showed a main effect for awareness, F(1, 52) = 14.38, p < .05, g2p = 0.22. Participants aware of their KR content demonstrated less VE (M = 14.0, SE = .90) compared to those participants not aware (M = 18.8, SE = 0.9). All other main effects and interactions were not statistically significant at p < .05. 3.2.3. Self-reported measures of KR content awareness Our primary interest in the present experiment was to determine if being aware of the KR content would differentially impact learning compared to not being aware. Thus, to determine if being aware was a factor in facilitating motor skill acquisition, we needed to confirm that all participants in the unaware conditions (G-U and P-U) were in fact unaware of their KR content during the acquisition period. When asked to self-report their perception of the KR content during the acquisition period (e.g., good trials, poor trials, randomly, etc.), none of the participants in the GU and PU KR conditions reported receiving KR on trials that were in fact consistent with their experimental condition (e.g., only good or poor trials, respectfully). In fact, 57% (8/12) of participants in the GU condition and 64% (9/12) participants in the PU perceived that KR was being provided ‘randomly’ (see Table 1). We were also interested in determining whether the KR presented to participants during the acquisition period facilitated their motivation to learning the motor task. All participants (14/14) in the G-A, 79% (11/14) in the P-A, and 93% (13/14) in the P-U and G-U conditions, respectively, reported the KR they received during the acquisition period facilitated their motivation to learn the task. Finally, all participants were asked to self-report, that if they had the choice, when they would have preferred to receive KR. Only 36% (5/14) of participants in the G-A and G-U would have preferred to receive KR after good trials. For the P-A condition, only 14% (2/14) and 7% (1/14) in the P-U would have preferred to request KR on poor trials, similar to their experimental condition. Finally, 71% (10/14)
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Table 1 Introspective reports of participants as a function of feedback type (good/poor trials) and awareness of feedback type (aware/ unaware) regarding feedback scheduling. Group Good-aware
Poor-aware
Good-unaware
Poor-unaware
Did the feedback presented to you facilitate your motivation to learn the motor task? Number of responses Yes 14 11 13 13 No – 3 1 1 If you had the choice, when would you have preferred to receive feedback? Number of responses After only successful (e.g., good) trials 5 4 5 10 After only unsuccessful (e.g., poor) trials 2 2 4 1 Randomly 2 1 – – After good and poor trials equally 3 6 5 3 Other 2 1 – – During your practice of the motor task, you were presented feedback on certain trials. Did you perceive the feedback being presented to you was: Number of responses Good-Unaware conditions Poor-Unaware conditions After only successful (e.g., good) trials – 2 After only unsuccessful (e.g., poor) trials – – Randomly 8 9 After good and poor trials equally 4 3 other 2 –
of participants in the P-U condition and 29% (4/14) in the P-A condition preferred to receive KR after good trials (see Table 1). 4. Discussion Previous research examining the learning advantages of self-controlled KR schedules have reported a deliberate preference from participants in a self-controlled KR condition to prefer KR after perceived ‘good’ compared to ‘poor’ trials (Chiviacowsky & Wulf, 2002; Patterson & Carter, 2010). This finding has been extended in externally defined KR contexts whereby providing KR on relatively good rather than relatively poor trials has proven superior for motor skill learning (Badami et al., 2011; Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). Yet, in these previous studies, participants were not explicitly made aware of the KR they were receiving (i.e., good trials or poor trials). Further, it was only assumed that participants in their respective KR condition were in fact unaware of their KR content (e.g., good trials, poor trials). To address this limitation, the purpose of the present experiment was to extend this line of inquiry by examining whether or not participants awareness of their KR information, that is, based on relatively good or poor trials would differentially impact motor skill learning. Based on our theoretical understanding of KR during motor learning (Salmoni et al., 1984; Schmidt & Lee, 2011; Wulf & Shea, 2004) we suggested that if being aware of the KR content was the primary determinant facilitating motor skill learning, the groups awareness of their KR content would perform similarly in the retention period, yet superior to those groups unaware of their KR content. However, if the information within the KR display was the factor impacting motor skill learning, independent of awareness, we expected providing KR on relatively good compared to relatively poor trials would prove superior for learning, consistent with the existing research (Badami et al., 2011; Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). The results of the present experiment did not replicate and subsequently challenges the findings of previous research (i.e. Badami et al., 2011; Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). Our results suggest that participant’s awareness of their KR content was a factor modulating motor skill acquisition, not whether the KR was provided on good or poor trials. A discussion of these findings follows. The results from previous inquiry have suggested that providing KR after relatively good trials facilitates superior learning compared to providing KR after relatively poor trials (Badami et al., 2011;
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Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). Importantly, participants in these experiments were unaware of the content within their KR display. Contrary to this research, the results of the present experiment challenge earlier findings by showing that learning was superior when participants were aware compared to unaware of their KR content. We offer two possible reasons for these findings. First, the differences in learning between the aware and unaware conditions cannot be accounted for by the self-reported levels of motivation from participants required to learn the task. Our results do suggest that organizing KR information for the learner in a summary display according to a meaningful referent (i.e., only KR on good trials or poor trials) facilitated the efficiency of processing KR, to the advantage of learning. Presenting KR as a summary for a portion of the acquisition trials does share similarities to earlier research efforts examining the presentation of KR as summary (Guadagnoli, Dornier, & Tandy, 1996). In the summary KR literature, the learner is withheld KR for a pre-determined amount of no-KR trials (e.g., 5 trials), which is then followed by presenting KR for all the no-KR trials completed in the block in a summary format (e.g., 5 trials; 100% relative frequency). In a traditional summary KR display, the learner is assumed to utilize the KR in the summary display to dissociate the good from the poor motor responses as a method of facilitating the planning of upcoming motor actions. Based on the results of the present experiment, we suggest that modifying a summary KR display such that a meaningful referent is applied to the KR information (e.g., KR on good or poor trials) optimizes the efficiency and effectiveness of the learners processing of the KR, subsequently facilitating motor planning and as a consequence, learning. This notion is resonant with relatively recent theoretical understandings of the role of KR during skill acquisition that suggests KR should be presented in a manner that does not provide too much or too little challenge to the learner’s information processing (Guadagnoli & Lee, 2004). In summary, our results suggest that explicitly grouping the KR trials as a function of the participant’s performance (e.g., grouping the most accurate or least accurate trials) increased the informational value of the KR, independent of whether the KR was based on good or poor trials throughout the acquisition period, to the advantage of learning as evidenced by superior movement accuracy (|CE|) and movement stability (VE) in the retention period. Further research is required to determine the utility of organizing KR for the learner according to a pre-determined referent. These further inquires would determine whether meaningful referents utilized for organizing KR for the learner, such as ordering motor performance trials from good to poor, or vice versa, would further strengthen the informational and motivational role of KR during motor skill acquisition. Our second interpretation of the results is related to the presumed novelty of the motor task. We suggest the novelty of the present motor task, based on the fact participants were not expected to have any pre-existing knowledge or experience, compared to the caveat highlighted in the motor tasks utilized in previous research (e.g., Chiviacwosky & Chiviacowsky et al., 2009; Wulf, 2007), may have contributed to the present findings, and a failure to replicate past research. For example, the conclusions from previous research were based on a motor task that required participants to toss beanbags at a pre-defined target using their non-dominant hand (Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). Chiviacowsky and Wulf (2007) cautioned that although the task was performed with the non-dominant hand, pre-existing knowledge and experience with similar tasks may have compromised the novelty of the task and contributed to participants’ ability to accurately assess their movement outcome. Chiviacowsky and Wulf (2007) suggested that future research utilizing motor tasks where participants lacked previous experience was required to examine the generalizability of the findings. Thus, we suggest the novelty of the motor task utilized in the present experiment, compared to previous investigations (e.g., Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009) contributed to the failure of our unaware conditions to perform similarly to the unaware conditions in previous research. In fact, an earlier review by Wulf and Shea (2002) highlights the modulating effects of motor task characteristics on differentiating the subsequent effectiveness of a specific practice condition (e.g., feedback). Similar to Chiviacowsky and Wulf (2007), we recommend further inquiry into examining the interaction of awareness of the feedback content (e.g., KR based on most accurate compared to least accurate trials) and the characteristics of the motor task, such as type (e.g., continuous, serial tasks) and complexity. Our results are however commensurate with other lines of KR inquiry where learning was superior for participants aware compared to unaware of the basis for the information within their KR display. For example, in a bandwidth KR protocol, participants are aware that if their motor performance falls within a pre-defined error-tolerance (e.g., good trial), their augmented
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feedback is qualitative (e.g., good). However if their performance falls outside the error tolerance (e.g., bandwidth) (e.g., poor trial), the precision of the KR content is increased such that quantitative KR is provided to the leaner (e.g. amount and direction of error). Contrary to previous research, the results of the present study suggest that being aware of KR content has a greater impact on learner compared to whether the KR is based on good or poor trials. To conclude with certainty that awareness of the KR information, independent of the KR information itself, was the factor facilitating skill acquisition, participants in the good-unaware and poor-unaware conditions were asked to self-report their perception of when they thought they were being provided KR. Importantly, the results from this questionnaire showed that none of the participants in G-U condition reported receiving KR on only good trials, and none of the participants in the P-U condition reported receiving KR on poor trials only. Based on this data, we can conclude that none of the participants in the unaware conditions had the same explicit knowledge of their KR information as those participants in the aware conditions. In fact, a majority of participants in the good-unaware (57%) and poor-unaware (64%) conditions reported receiving KR on random trials throughout the acquisition period. In summary, the results of the questionnaire lend further support to the notion that being aware of the information within the KR display had a greater impact on motor skill acquisition compared to the type of information in the KR display alone, as suggested by previous research. We further examined the questionnaire data to determine whether participant’s motivation to learn the motor task was differentially modulated by the KR condition experienced during the acquisition. In fact, when participant motivation is enhanced as a function of KR, learners are predicted to practice with more seriousness resulting in an indirect impact on learning (Schmidt & Lee, 2011). Thus, the motivational role of KR during skill acquisition was previously believed to be a performance phenomenon whereby the effects were only present when KR was available (see Schmidt & Lee, 2011 for review). However, more recent evidence suggests that in fact the motivational role of KR during skill acquisition has a direct, rather than indirect, impact on learning (Lewthwaite & Wulf, 2009). Thus, to examine whether participants motivation to learn the task was differentially impacted by the KR condition experienced during the acquisition, all participants were asked to self-report via a paper and pencil questionnaire, if the feedback presented to them throughout the acquisition period motivated them to learn the motor task (e.g., circle yes or no). Overall, 91% of the participants (51/56) who participated in the experiment reported the KR they received during the acquisition period motivated them to learn the motor task. Upon closer inspection, 76% (11/14) of participants in the poor-aware condition reported their KR facilitated their motivation to learn the task compared to the good-aware (100%), poor-unaware and good-unaware conditions (both 93%, respectively). However, when collapsing across information type, the self-report measures from the aware and unaware participants, reported a similar amount of participants in the unaware (93% of participants) and aware condition (88% of participants) were motivated to learn the motor task as a function of their KR condition during the acquisition period. Although most participants in the aware and unaware condition were motivated to learn the motor task as a function of their KR condition, these findings do not account for the motor performance differences between aware and unaware conditions in the retention portion of the experiment. However, our findings do suggest that perceived motivation was not the singular factor dissociating the learning differences between the aware and unaware KR conditions. Further research is required to delineate the direct and indirect motivational role of KR during skill acquisition when providing KR on relatively good versus poor trials. The results from previous findings showed that when participants were unaware of the type of information in the KR display (i.e., good or poor trials), presenting KR on only good trials for 50% of the acquisition trials was more advantageous for learning compared to presenting KR on only poor trials (Badami et al., 2011; Chiviacowsky & Wulf, 2007; Chiviacowsky et al., 2009). The results of the present experiment challenge these findings by suggesting that awareness of the KR content has a greater impact on learning compared to receiving KR on either good or poor trials for 50% of the acquisition trials. However, further research is required to determine whether awareness is modulated by the relative frequency (e.g., providing KR on more than or less than 50% of the acquisition trials) of KR during motor skill acquisition.
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5. Conclusion In conclusion, the results from the present experiment suggest that being aware of the information in a summary KR display (good or poor trials), was more influential for motor skill learning compared to being unaware of the information in the KR display. Unlike previous research, our results were independent of the information within the KR display (e.g., KR based on good or poor trials). As a result, our findings challenge the findings from previous inquiry by suggesting that awareness of KR content had a greater impact on learning compared to receiving KR on either good or bad trials. Our results further suggest awareness facilitated a meaningful referent for the participants in facilitating their motor performance on subsequent motor trials (i.e. repeat a successful trial or correct an incorrect trial). Further research is recommended to examine the utility of awareness and organization of KR according to meaningful referents on the learners information processing and subsequent motor planning and learning. From a practical standpoint, our results suggest that a learner’s awareness of KR content could have a greater impact on learning compared to presenting KR on good or poor trials in various contexts such as vocational, recreational and rehabilitation settings. References Arps, G. F. (1920). Work with knowledge of results versus work without knowledge of results. Psychological Monographs, 28, 1–41. Badami, R., VaezMousavi, M., Wulf, G., & Namazizadeh, M. (2011). Feedback after good versus poor trials affects intrinsic motivation. Research Quarterly for Exercise and Sport, 82, 360–364. Chiviacowsky, S., & Wulf, G. (2002). Self-controlled feedback: Does it enhance learning because performers get feedback when they need it? Research Quarterly for Exercise and Sport, 73, 408–415. Chiviacowsky, S., & Wulf, G. (2005). Self-controlled feedback is effective if it is based on the learner’s performance. Research Quarterly for Exercise and Sport, 76, 42–48. Chiviacowsky, S., & Wulf, G. (2007). Feedback after good trials enhances learning. Research Quarterly for Exercise and Sport, 78, 40–47. Chiviacowsky, S., Wulf, G., Wally, R., & Borges, T. (2009). Knowledge of results after good trials enhances learning in older adults. Research Quarterly for Exercise and Sport, 80, 663–668. Guadagnoli, M. A., Dornier, L. A., & Tandy, R. D. (1996). Optimal length for summary knowledge of results: The influence of taskrelated experience and complexity. Research Quarterly for Exercise and Sport, 67, 239–248. Guadagnoli, M. A., & Lee, T. D. (2004). Challenge point: A framework for conceptualizing the effects of various practice conditions in motor learning. Journal of Motor Behaviour, 36, 212–224. Kohen, J. D., Dickinson, J., & Goodman, D. (2008). Cognitive demands of error processing. Psychological Reports, 102, 532–538. Lewthwaite, R., & Wulf, G. (2010). Social-comparative feedback affects motor skill learning. The Quarterly Journal of Experimental Psychology, 63, 738–749. Patterson, J. T., & Carter, M. J. (2010). Learner regulated knowledge of results during the acquisition of multiple timing goals. Human Movement Science, 29, 214–217. Salmoni, A. W., Schmidt, R. A., & Walter, C. B. (1984). Knowledge of results and motor learning: A review and critical reappraisal. Psychological Bulletin, 95, 355–386. Schmidt, R. A. (1975). A schema theory of discrete motor skill learning. Psychological Review, 82, 225–260. Schmidt, R. A., & Lee, T. D. (2011). Motor control and learning: A behavioral emphasis (5th ed.). Champaign, IL: Human Kinetics. Thorndike, D. L. (1927). The law of effect. American Journal of Psychology, 39, 212–222. Wulf, G., & Shea, C. H. (2004). Understanding the role of augmented feedback: The good, the bad, and the ugly. In A. M. Williams & N. J. Hodges (Eds.), Skill acquisition in sport: Research, theory and practice (pp. 121–144). London: Routledge. Wulf, G., & Shea, C. H. (2002). Principles derived from the study of simple skills do not generalize to complex skill learning. Psychonomic Bulletin & Review, 9, 185–211. Wulf, G. (2007). Self-controlled practice enhances motor learning: Implications for physiotherapy. Physiotherapy, 93, 96–101. Wulf, G., Shea, C., & Lewthwaite, R. (2010). Motor skill learning and performance: A review of influential factors. Medical Education, 44, 75–84.