1-s2.0-s0001691802000446-main

8/14/2019 1-s2.0-S0001691802000446-main

1/18

Learning and performance effects of accurateand erroneous knowledge of results on

time perception

Lawrence J. Ryan * , Troy B. Robey 1

Department of Psychology, 204 Moreland Hall, Oregon State University,Corvallis, OR 97330-5303, USA

Received 28 May 2001; received in revised form 4 December 2001; accepted 2 January 2002

Abstract

Performance feedback (also known as knowledge of results or KR) has both performance

and learning effects on many tasks. Earlier studies have demonstrated performance but notlearning effects on time perception tasks. In this experiment, we dissociate and identify thesetwo phenomena on two different time perception tasks. Participants were presented with eitheraccurate (100%) or erroneous (80% or 120% of actual performance) KR on either a reproduc-tion or a numerical estimation time perception task. Accurate (100%) KR reduced the groupvariability and increased the accuracy of response magnitude but left individual variability un-changed. Erroneous (80% or 120%) KR also reduced the group variability while leaving indi-vidual variation unchanged, but decreased the true accuracy of the response, with responsemagnitudes increasing for the 80% KR group and decreasing for the 120% group. Thus exter-nal KR that is in conict with internal time cues overrides these internal cues and dictates re-sponse magnitude on these two tasks. Thus KR provides guidance for these behaviors. KR did

not reduce the variability (dispersion) of participants responses, but centered each partici-pants responses closer to the targeted performance. This decreased group response variabilityreected a performance enhancing effect of KR because group response variability increasedafter KR was withdrawn. In contrast, response magnitudes remained changed for the durationof the post-KR period, indicating that KR also induced a learned response. Thus individualresponse variability, group response variability and response magnitude represent dissociablefeatures of performance on these time perception tasks. 2002 Elsevier Science B.V. Allrights reserved.

Acta Psychologica 111 (2002) 83100

www.elsevier.com/locate/actpsy

*Corresponding author. Tel.: +1-541-737-1371; fax: +1-541-737-3547.E-mail address: [email protected] (L.J. Ryan).

1 Present Address: Department of Educational Leadership and Counseling Psychology, WashingtonState University, Pullman, WA 99163, USA.

0001-6918/02/$ - see front matter 2002 Elsevier Science B.V. All rights reserved.PII: S0001-6 918(02 )00044- 6

8/14/2019 1-s2.0-S0001691802000446-main

2/18

PsycINFO classication: 2343; 2340Keywords: Learning; Knowledge of results; Feedback; Time perception

1. Introduction

External performance feedback (also known as knowledge of results or KR) hasbeen shown to improve performance on skilled motor tasks (Salmoni, Schmidt, &Walter, 1984). KR promotes better performance both while it is present and afterit is withdrawn. While KR is present, it provides motivation and guidance andincreases a participants interest and persistence. These performance enhancingeffects dissipate rapidly once KR is withdrawn. However, KR also promotes learningand improves performance even after KR is withdrawn. Indeed, learning has beendened and differentiated from direct performance enhancing effects by the transferof improvement from the KR to the post-KR condition (Salmoni et al., 1984).

When learning motor tasks, information as to performance outcome is valuablebecause it provides a means by which the nervous system can calibrate and modifythe strength and timing of muscle responses in order to achieve the desired goal. Itprovides information that may be otherwise unavailable to the motor system. Onmany motor tasks, information as to performance outcome is provided by the ex-teroceptors, that is, participants can see or hear or touch the outcome to determinehow well they just performed. Performance feedback, whether originating from theexteroceptors or as KR from an external source, provides task-specic meaning tointernal physiological feedback that is itself task-independent (such as from musclespindles or Golgi tendon organs) and that may be used for regulating vastly differentmotor behaviors (a leg muscle and its associated sensory receptors, for instance, maybe used for running, kicking, stiffening the body while throwing, swimming, riding ahorse, etc.). The performance feedback may also directly modify motor program-ming, especially for ballistic movements that are preprogrammed to operate withoutcorrection by internal or exteroceptive feedback. In many cases KR provided by a

coach or computer or other outside source may be redundant with the exteroceptorfeedback, but, in other cases, it may provide additional information, clearer informa-tion or corroborative information to that provided by the exteroceptors. Indeed, KRis often used in preference to other sources of feedback, as is clearly shown by mis-guided performance following erroneous KR (Buekers, Magill, & Hall, 1992, 1994;McNevin, Magill, & Buekers, 1994).

Thus, on many motor tasks, KR complements information provided by the ex-teroceptors. On some cognitive tasks, such as judgment of line lengths, KR alsolikely complements the information provided by exteroceptors. However, on othercognitive tasks the sources of either internal, task-independent feedback analogous

to proprioceptive feedback, or of external, task-dependent feedback analogous tothat provided by exteroceptors on a motor task, are unknown. It is unclear on thesecognitive tasks what feedback is normally available to provide information for accu-

84 L.J. Ryan, T.B. Robey / Acta Psychologica 111 (2002) 83100

8/14/2019 1-s2.0-S0001691802000446-main

3/18

rate task performance and, therefore, how this feedback compares to KR. On a timeestimation task, for instance, in which the duration of an unlled interval is observedand then reported with a numerical estimate, the source of internal feedback thatwould be analogous to the proprioceptive feedback is unknown. The source of out-come feedback that would be analogous to exteroceptor feedback and that wouldprovide information for the measurement and correction of the accuracy of the time judgment is also unknown. Some models of time perception propose an internalclock whose ticks are accumulated and counted (Gibbon & Church, 1990), othermodels propose that mental events and changes are counted (Block & Zakay,1997) and still others propose that the decay of memory traces of recent events ismeasured (Staddon & Higa, 1999). These three type of models imply very differentsources and representations of internal time information (Grondin, 2001). Further-more, estimation tasks, reproduction tasks and production tasks involve quite dif-ferent cognitive processes to report the outcome of the time perception process(Fraisse, 1984; Montare, 1985, 1988; Zakay, 1990).

Without knowing what information sources are normally used to guide timingperformance it is difficult to predict how KR might act to alter and improve perfor-mance on time perception tasks. It could affect basic timing processes, calibration orinterpretation of these processes, memory that either holds the current duration per-ception or that holds recalled intervals for comparison, or it could affect task specicfactors that differ among the estimation, reproduction and production tasks.

In this paper we begin an analysis of how KR affects time perception processes.KR has been shown to increase the accuracy and to decrease the variability of responses on time perception tasks using short (seconds) and ultrashort (less than1 s) intervals (Aiken, 1965; Buckolz & Guay, 1975; Crowder & Hohle, 1970; Hicks& Miller, 1976; Hoyer, Jones, White, & Maconachy, 1970; Kladopoulos, Brown,Hemmes, & Cabeza de Vaca, 1998; Montare, 1985, 1988). KR also improves tempo-ral discriminability (Allen & Clark, 1979). Unlike KR on motor learning tasks, theseeffects on time perception tasks have typically been shown to decay rapidly after KRis withdrawn (Aiken, 1965; Buckolz & Guay, 1975; Hicks & Miller, 1976; Kladopo-ulos et al., 1998).

This is surprising as it may indicate that KR does not promote learning on time

perception tasks, contrary to some claims (e.g., Montare, 1985, 1988). Of course, wemay not learn about time perception because this is already an acquired and over-learned skill. Most participants have had years of experience judging short intervalsof known length (TV commercials, microwave settings, etc.). Rather than inducingthe learning which recalibrates our sense of time, the learning that may result fromKR could be learning about the specic requirements of the task and may thereforenot be obvious because most tasks are simple and easily acquired.

We have three goals for this study. First, we test the hypothesis that KR does leadto learning on time perception tasks. Unlike earlier experiments, we attempt to dis-tinguish between performance and learning enhancing effects of KR on time percep-

tion tasks by using a transfer design that allows us to examine performance duringand following the presentation of KR (Salmoni et al., 1984). We also use a paradigmderived from the motor learning literature (Buekers et al., 1992, 1994; McNevin et al.,

L.J. Ryan, T.B. Robey / Acta Psychologica 111 (2002) 83100 85

8/14/2019 1-s2.0-S0001691802000446-main

4/18

1994) that allows us to dissociate the effects of KR on the magnitude and the vari-ability of performance. We provide some participants with erroneous KR that eitherunder-represents or over-represents their actual performance. Based on these motorlearning studies, we predict that KR that under-represents performance will lead toan increase in response magnitude, whereas KR that over-represents performancewill lead to a decrease in response magnitude. We further predict that this effect islearned and will persist following the removal of the KR.

The second goal is to test the hypothesis that KR provides guidance for perfor-mance on our tasks as it is known for motor learning tasks. On such tasks, KR isbelieved to have both motivational effects, such as increased attention, reinforce-ment, persistence, interest, etc., and guidance effects, such as highlighting the correctgoal, which improves performance when KR is present (Salmoni et al., 1984). Theseknown motivational and guidance actions may well account for the observedchanges in performance on time perception tasks when KR is provided. The useof erroneous KR provides a direct test of the guidance effect of KR on these partic-ipants by specifying different performance targets and thus different degrees and di-rections of performance errors relative to initial performance. If the guidancehypothesis is correct, the magnitude of response change should reect both initialperformance and the target specied by the erroneous KR whereas other perfor-mance enhancing effects, such as increasing attention or interest, should act indepen-dently of initial performance.

The third goal is to provide evidence as to whether the KR-induced learning is taskspecic or whether it affects more fundamental time perception processes. It has beenproposed that different methods of measuring time perception may tap different cog-nitive processes and may therefore respond differently to KR (Fraisse, 1984, Montare,1985, 1988; reviewed by Zakay, 1990). Thus, we conduct two parallel experimentsthat use the same temporal source stimulus but use two different methods of measur-ing perceptual accuracy: a reproduction task and a numerical estimation task.

2. Method

2.1. Participants

Sixty-one male and female under-graduate students enrolled in a psychologycourse volunteered to participate in these experiments and received extra class creditfor their participation. Conditions of participation were approved by the OSU Hu-man Participants Committee and met all current ethical guidelines for the use of hu-man participants.

2.2. Materials and procedure

The experiments were conducted using 2 DOS-based 486 computers. Each partic-ipant completed a single session comprising three phases with the entire session typ-ically lasting 25 min and always lasting less than 35 min. Participants received


8/14/2019 1-s2.0-S0001691802000446-main

5/18

instructions and an opportunity to practice during the introductory screens of thecomputer program. They then initiated a series of three self-paced experimentalphases. In the reproduction task ( n 31), participants initiated a computer displaythat consisted of a red 33 37 mm rectangle centered on the screen against a blackbackground. A white command line occupied the top 10 mm of the screen. ThisRED display remained on the screen for one of three xed durations: 3.7, 5.6 or8.5 s. Participants were asked, both at the initial verbal brieng and again on thewritten computerized instructions, to judge the duration that this sample display re-mained on the screen without mentally counting. No other attempt was made to pre-vent counting but participants were asked at debrieng about their performance of the task. No data were excluded because of self-reports of counting. Furthermore, noparticipants in the erroneous KR groups reported being aware of the systematicerror in the KR, which should have been obvious to them if participants had beencounting. After judging the duration of the sample interval, they were to reproducethis interval by initiating a new display, identical to the sample interval display ex-cept that it was brown, and to terminate the display with a second keystroke whenthey estimated the BROWN display had been on the screen for as long as the previ-ous RED sample display. Performance data were not recorded for the rst three tri-als (one of each duration). Eight randomly presented samples of each duration, 24trials in total, were then presented. During phase 2, participants initiated the sameRED samples and BROWN reproduction displays but after each trial receivedgraphical feedback (KR) about the accuracy of their performance. The KR consistedof a red (84 5 mm) rectangle whose length represented the duration of the REDsample interval. Below it was a brown 5 mm in height rectangle whose length repre-sented the length of the reproduced interval relative to the sample interval. The threegroups of participants differed in the accuracy of this KR display. For one group(100% KR, n 10) the brown rectangle accurately represented their performance.For another group (80% KR, n 10), the brown rectangle represented only 80%of their reproduced interval and for the third group (120% KR, n 11) the brownrectangle represented 120% of the duration of their reproduced interval. Phase 3 re-sembled phase 1 in that participants completed the same task but did not receive KR.

The numerical estimation task ( n 30, 10 participants per KR group) was iden-

tical to that in the reproduction task with two exceptions. First, the participants wereasked to make a numerical estimation of the duration of the RED sample intervalrather than reproduce the interval. Participants were asked to make estimates tothe nearest whole second in order to control for the strong whole number responsebias that has been identied in verbal estimation paradigms (Zakay, 1990). Second,the sample durations were slightly changed from the reproduction task, being cen-tered between whole numbers: 3.5, 5.5 and 8.5 s.

2.3. Statistical analysis

Both experiments used a 3 3 3 design with two measures, sample duration(three levels) and experimental phase (three levels: pre-, during and after KR) beingrepeated. The third variable represented independent groups (three KR groups: 80%,


8/14/2019 1-s2.0-S0001691802000446-main

6/18

100% or 120% feedback). In both experiments, the dependent variable was the meanof the ratio of the performance (either reproduced duration or the numerical esti-mate) to the sample duration on each trial, eight trials per cell. Post-hoc analysisof differences between cells were conducted using the NewmanKeuls test with dif-ference criteria specied at a 0:05.

Two measures of response variability were measured. Group variability was mea-sured by calculating the standard error of the mean for each cell (27) in the 3 3 3design. Statistical signicance of the change in group variability across adjacentphases (2 vs 1 and 3 vs 2) was calculated using the Wilcoxin signed ranks test. Indi-vidual variability was calculated as a coefficient of variation dened as the ratio of standard deviation of each participants performance ratio (the dependent variablefor response magnitude) on the 8 trials comprising each cell of the design dividedby the participants mean performance ratio for that cell. Mean coefficients of vari-ations were then calculated across participants for each cell. A 3 3 3 repeatedmeasures ANOVA was conducted on the coefficients of variation. Post-hoc analysisof differences between cells were conducted using the NewmanKeuls test with dif-ference criteria specied at a 0:05.

To test the guidance hypothesis, the perceived performance error for each partic-ipant was calculated by determining the difference between each participants aver-age performance during the pre-KR phase and the target performance specied bythe KR (participants receiving 80% KR would have to perform at 125% of the sam-ple duration to achieve an apparent performance of 100%, those receiving 120% KRwould need 83.3% of the sample to appear to be performing at 100%). Thus a par-ticipant in the 80% KR group who initially under-estimated by 5% would have alarger apparent target (a 30% change) during KR than a participant who initiallyover-estimated by 5% (a 20% change). In comparison, over- and under-estimatorswould have similar magnitudes of change but different directions of change indicatedby 100% KR. We examined the correlation between the change in participant perfor-mance induced by KR and their perceived error of performance.

3. Results

3.1. Pre-KR

Prior to KR, participants in each group of the reproduction task reliably repro-duced intervals that were slightly shorter than the sample intervals (Fig. 1A). In con-trast, the numerical estimates made during the pre-KR phase in the numericalestimation task varied around the sample durations (Fig. 1B).

3.2. Effects of KR on magnitude of response

The effect of KR on the magnitude of the response was pronounced and demon-strated in two ways. First, the effect of KR is demonstrated as a change in the mag-nitude of response from the pre-KR to KR phases (KR group Phase Interaction,


8/14/2019 1-s2.0-S0001691802000446-main

7/18

Fig. 1. KR changes the magnitude of participants reproduced or estimated durations. For the reproduc-tion task (A) and the numerical estimation task (B) the mean response magnitude is represented as themean of the ratio of the participants reproduced or estimated duration and the actual duration of thesample for each of the three sample durations tested. The mean ratios are indicated for the three phasesof the experiment (prior to KR, receiving KR and after KR is withdrawn) and for the three experimentalgroups, which received either accurate KR (100% KR) or erroneous KR (80% or 120% of the participantsactual performance). Eighty percent KR increased participants reproduced or estimated durationswhereas 120% KR decreased participants durations. These effects persisted after KR was withdrawn, in-dicating the occurrence of learning. * p < 0:05 (NewmanKeuls test): the 80% or 120% KR group differedfrom the 100% group during the phase, p < 0:05: the 80% and 120% KR groups differed from eachother.


8/14/2019 1-s2.0-S0001691802000446-main

8/18

8/14/2019 1-s2.0-S0001691802000446-main

9/18

increased the duration of their reproductions and slightly decreased their numericalestimations (Fig. 1 and left half of Fig. 2). In contrast, participants receiving errone-ous KR greatly altered their performance, more strongly with 80% than 120% feed-back on the reproduction task, and equally on the estimation task. Participantsreceiving 80% feedback markedly increased the duration of their responses on bothtasks. Participants receiving 120% feedback on the estimation task markedly de-creased their response magnitudes, whereas, on the reproduction task, the durationof their responses was little changed. These KR effects were present at all three du-rations (Figs. 1 and 2), but were smaller at the longer durations (ANOVA; Repro-duction: KR group Duration F 4; 56 4:164, p < 0:01; Estimation: Maineffect of Duration F 2; 54 6:057, p < 0:01; KR group Duration F 4; 54 1:053, p 0:369).

3.3. Effects of KR on group and individual variability of response

In both tasks, KR, regardless of whether it was accurate or erroneous, reduced thevariability of the responses of each group of participants (Fig. 3A and B). For boththe reproduction and estimation tasks, the SEM was smaller in all possible cases, i.e.,in 9 of 9 cases for each task (3 feedback groups 3 interval durations; Wilcoxinsigned ranks test: N 9, T 0, p < 0:01). In contrast, each participants variabil-ity, as indicated by the coefficient of variation was essentially unchanged acrossexperimental phase for the reproduction task (see Fig. 3C) (ANOVA: main effect

of Phase: F 2; 56 0:256, p 0:775; KR group Phase: F 4; 56 1:314, p 0:276; KR group Phase Duration: F 8; 112 0:813, p 0:593; no signi-cant NewmanKeuls comparisons). On the estimation task, similar results werefound ((see Fig. 3D) ANOVA: main effect of Phase: F 2; 56 6:685, p < 0:01;KR group Phase: F 4; 56 0:042, p 0:792; KR group Phase Duration: F 8; 112 0:998, p 0:442). Although a signicant main effect of Phase was ob-served on the estimation task, no signicant changes for matching cells betweenphases 2 and 1, phases 3 and 2, nor phases 3 and 1 were found with NewmanKeulsanalysis. Signicant differences, which may reect the signicant main effect, wereonly found for non-matching cells (e.g. Phase 2, 100% KR, 3.5 s duration vs. Phase3, 80% KR, 5.5 s duration).

For both the reproduction and estimation tasks, there was a small effect of dura-tion (main effect of Duration: Reproduction F 2; 56 8:705, p < 0:001; Estima-tion F 2; 56 5:152, p < 0:01) with slightly smaller coefficients of variation atlonger sample intervals (Fig. 3C and D).

3.4. Post-KR response magnitude

The effect of KR on response magnitude persists into the post-KR phase as indi-

cated by differences in the response magnitudes of the KR groups during the post-KR phase. The 80% and 120% KR groups continued to differ from each other onboth tasks and for all durations (signicant NewmanKeuls differences shown in


8/14/2019 1-s2.0-S0001691802000446-main

10/18

Fig. 1). The 80% and 120% KR groups also differed from the 100% KR group onboth tasks for some durations (signicant NewmanKeuls differences shown inFig. 1).

The absolute magnitude of responses did change slightly between the post-KRand KR phases. On both the reproduction and estimation tasks, participants showedsome signicantly lengthened response magnitudes post-KR relative to their esti-

Fig. 3. Group response variability (A and B), as indicated by the SEM for the ratio data shown in Fig. 1,was reduced by KR and increased after KR was withdrawn. The decline in SEM reects the increased tar-geting accuracy of each group. This increase in the post-KR phase indicates that the reduced group vari-ability in the presence of KR is caused by a performance-enhancing effect of KR rather than by learning.In contrast, individual participants response variability (C and D), as indicated by the coefficient of vari-ation, did not change across KR conditions. Thus the dispersion of a participants response was un-changed, but this dispersion was centered more accurately around the target performance.


8/14/2019 1-s2.0-S0001691802000446-main

11/18

mates during the KR phase (right half of Fig. 2). This effect occurred in all three KRgroups and on both tasks suggesting it is unrelated to the KR or task.

3.5. Post-KR response variability

After the termination of KR the group variability of both reproduced durations

and numerical estimates increased (Fig. 3A and B). The SEM increased for 9 of 9conditions for the reproduction task (Wilcoxin signed ranks test: N 9, T 0, p < 0:01) and for 7 of 9 conditions in the estimation task (Wilcoxin signed ranks test:

Fig. 3 ( continued )


8/14/2019 1-s2.0-S0001691802000446-main

12/18

N 9, T 4, p < 0:05). The coefficient of variation did not show any consistentchange between phases 2 and 3 (Fig. 3C and D).

3.6. Over- and under-estimators

On both the reproduction and estimation tasks, most participants under-esti-mated (by more than 4%) the sample durations in the pre-KR period (Reproduction,mean all durations: N UNDER 19, N OVER 2, N WITHIN 4% 10, 1-sample sign test: z 3:71, p < 0:01; Estimation: N UNDER 18, N OVER 3, N WITHIN 4% 9, 1-samplesign test: z 3:28, p < 0:01).

On both tasks, initial under-estimators increased the magnitude of their durationresponses when given accurate feedback whereas initial over-estimators decreased

the magnitude of their duration responses (Fig. 4). Under-estimators showed largereffects than over-estimators as a result of 80% feedback and showed smaller effectsas a result of 120% feedback (Fig. 4). The magnitude of the change in performancecaused by KR was a function of the difference between the participants initial per-formance prior to KR and the target magnitude indicated by the KR. Results of correlation analysis of the magnitude of the change indicated by the KR (the dif-ference between KR specied target and initial performance) and the magnitudeof the actual change in performance induced by KR (change in response magni-tudes between KR phase and initial performance in the pre-KR phase) are shownin Table 1. Positive correlations, ranging from 0.516 to 0.958, were seen for all

groups.

Fig. 4. Participants that initially under-estimated or that initially over-estimated the sample durations onboth the reproduction (left) and numerical estimation (right) tasks, shifted their performance towards thetarget durations indicated by the 80%, 100% or 120% KR. Thus the change in performance was guided bythe indicated targets and was not based on fundamental participant differences that accounted for theirinitial over- or under-estimations.


8/14/2019 1-s2.0-S0001691802000446-main

13/18

4. Discussion

These results conrm our hypothesis that KR can produce both learning and per-formance enhancing effects on time perception tasks. On both a time reproductiontask and a time estimation task, we measured three effects in the presence of KR:(1) a shift in the magnitude of the duration responses, (2) a decrease in the variabilityof the group magnitude responses, and (3) no systematic change in the variability of each participants individual response. Thus, KR enhances performance by more ac-curately centering each participants performance around a target without alteringthe dispersion of that participants response. The accuracy of the centering of perfor-mance around the target values specied by the KR declined in the absence of KR,suggesting that this action of KR is a performance-enhancing action. In contrast, therelative change in response magnitude persists following the withdrawal of KR, in-dicating that learning has occurred.

These effects are made particularly clear by the use of erroneous KR. The KR thatwas intentionally shorter than the persons actual performance reliably increasedthat persons time estimates and KR that was intentionally longer tended to decreasethat persons time estimates. Thus KR appears to provide guidance informationabout the target performance. These effects also were true regardless of whetherthe participants initially over-estimated or under-estimated the sample durationssuggesting that fundamental factors that might lead a person to over- or under-esti-

mate time intervals do not affect how KR is used.

4.1. Performance effects of KR

In the presence of KR, group response variability declined. Because this declinelargely disappeared after KR was terminated, it appears to be associated with theknown performance enhancing effects of KR (Salmoni et al., 1984). There are sev-eral ways that KR might enhance performance on these tasks. It is likely that KRincreases the interest of participants in the task. During debrieng many partici-pants reported being more interested and attentive during the feedback phase than

in the non-feedback phases. This effect seems unlikely to be a major effect, though,because increased interest should cause a decline in response variability, whereasindividual participants response variability did not change. Another possibility is

Table 1Correlations of the magnitude of the change indicated by the KR (the difference between KR specied tar-get and initial performance) and the actual change in performance induced by KR (change in responsemagnitudes between KR phase and initial performance in the pre-KR phase)

Reproduction Numerical Estimate

Short Middle Long Short Middle Long

80% KR 0.759 0.621 0.819 0.564 0.580 0.820100% KR 0.868 0.664 0.827 0.958 0.937 0.900120% KR 0.516 0.758 0.560 0.940 0.867 0.909

Note: For all r > 0:55, t 9> 1:83, p < 0:05.


8/14/2019 1-s2.0-S0001691802000446-main

14/18

that KR could focus or direct attention onto the events from which the partici-pants derived their perception of the passage of time. This seems unlikely, however,because in the erroneous KR groups, there is a conict between the internal rep-resentation of time passage and the KR. Focusing attention on these internal tim-ing processes should magnify the conict and, presumably, increase the variabilityof performance. KR clearly overrides the internal representation and perceptions.This strong effect of erroneous KR has previously been reported in the motorlearning literature (Buekers et al., 1992, 1994; McNevin et al., 1994). The attentioneffects may, in fact, direct attention towards the KR and away from the internalcues and may assist in raising the salience and apparently reliability of the KR(Buekers et al., 1994).

Another possibility is that the mental representation of a short interval is changedby KR. Although some have claimed that it is implausible that KR can alter timeperception per se (Kladopoulos et al., 1998), this claim is made without empirical ev-idence. Such an effect seems plausible if, for instance, KR interacts in working mem-ory with a representation of the immediately preceding interval. However, thismemory explanation also cannot account for the reduced variability in the erroneousfeedback groups. The current experiments, though, do not provide any direct evi-dence for or against an alteration of mental representations of time underlying theeffects of KR.

Another alternative is that KR alters neither the mental representation, nor fo-cuses attention on the judgment of interval duration, but rather KR alters the useof time information in the performance of the task itself. Hicks and Miller (1976) sug-gested, on the basis of KR on other, non-time related perceptual tasks, that KR alterswhat they called response-translation processes. Task variables which might be af-fected could include response criteria, motor preparation responses on the reproduc-tion task, proprioceptive feedback on the reproduction task, or numerical labeling onthe estimation task, to name a few response processes. These processes depend on themethod used to measure time perception (Zakay, 1990). That is, KR may enhanceperformance by focusing attention on meeting the task requirements. The controlledvariable may be the outcome and internal variables may be translated to t the cur-rent task requirements. This translation, could, for instance, be as simple as an 80%

or 120% linear transform of internal perceptions or representations. This idea is con-sistent with the hypothesis that KR provides guidance (Salmoni et al., 1984; Schmidt,Young, Swinnen, & Shapiro, 1989). The idea of guidance may seem strange outsideof motor tasks where physical guidance can provide proper movement information,but KR does provide guidance in the sense of specifying the target of the perfor-mance and specifying the error between the target and the performance. The speci-cation of error could reduce response variability. It is clear from our correlationalanalysis that the magnitude of the change in a participants performance is largelyaccounted for by the magnitude of the difference between the target specied bythe KR and the participants initial performance. Prior to KR, the error specication

must rely solely on other information sources, that is, the untranslated internal vari-ables. Following KR, error specication might rely on these internal variables andthe translation factor(s).


8/14/2019 1-s2.0-S0001691802000446-main

15/18

Some models of the cognitive processes underlying time perception (e.g. Gibbon& Church, 1990; Kladopoulos et al., 1998) are based on analysis of participants re-sponse variability. Our nding of no change in the coefficient of variation is conso-nant with these (and similar) models, in which participants response variabilitiesderives largely from variability in the clock timing and counting mechanisms andnot from the decision criteria. The increased accuracy of the centering of the groupresponses reected in the decreased group variability is also consistent with thesemodels. If this were the case, KR would act by altering the decision criteria. Our dataacross KR groups do not test directly these models, but are not inconsistent withthem. However, the small reduction in the coefficient of variation seen with longersample intervals on both tasks is not entirely consistent with scalar timing models.

4.2. Learning effects of KR

In the presence of KR, participants modied the magnitude of their duration re-sponses. These changes persisted after KR was withdrawn and therefore meet the cri-teria of learned responses (Salmoni et al., 1984). Changes in group variability did notpersist after KR was withdrawn and changes in a participants response variabilitydid not occur with KR. Thus changes in group response variability, participant re-sponse variability and magnitude estimations are dissociable phenomena.

The central question is, What do participants learn from the KR that mediatesthe persistence of the changes in response magnitude? Because these changes oc-curred in both reproduction and numerical estimation tasks, consideration shouldrst be given to those elements shared by the two tasks. Both tasks share the presen-tation and perception of the sample intervals but differ in the method of reportingthe time duration perception. Thus, it is possible that, because of the mismatch be-tween the duration information provided by KR and the internal feedback, KRmight alter the perception of the passage of time itself or the mental representationor memory of the sample interval. Such a recalibration of our sense of time would beunprecedented and seems discordant with evidence that time perception changes aswe age (e.g., Craik & Hay, 1999) since the recalibrating events, such as timing with awatch, watching 15 s television commercials, etc., are widely available and should

prevent age-related changes. Also, performance of the reproduction task requiresmatching the sample and reproduced intervals. It is hard to imagine how recalibra-tion would affect the perception of one but not both intervals or lead to strikinglydifferent perceptions of two equal intervals.

The response-translation hypothesis presented above suggests that rather thanour time perception being recalibrated, the unchanged perceptions may be used dif-ferently during and after KR than before. If KR provides guidance and a target forperformance, then the goal of performance is minimizing the difference between theperformance and the target, not minimizing the perceived differences between thesample duration and reproduced duration. In the estimation task, the goal becomes

minimizing the difference in verbal label of the sample duration and the KR, not of accurately representing the duration of the sample interval. A similar conclusion,that mental representations are not altered, but other decision processes are, has


8/14/2019 1-s2.0-S0001691802000446-main

16/18

been reached studying temporal generalization and bisection tasks (Ferrara, Lejeune,& Wearden, 1997).

4.3. Non-specic changes in time responses

There appears to be a lengthening of both reproduced intervals and time estimatesafter KR has been withdrawn. These effects appear to be non-specic because theyare unrelated to the KR group, all three groups showed similar lengthenings. Be-cause we did not include a group which did not receive KR but which performedthe same number of trials in the same number of phases we cannot determine if thisis an effect of the KR or a result of repeated performance of the task.

4.4. Initial over- versus under-estimators

In both our tasks, most participants initially under-estimated the short time inter-vals, though a few over-estimated them. Montare (1985, 1988), who observed a sim-ilar tendency on similar tasks, hypothesized that this difference reects differentinternal processes and that over- and under-estimators are fundamentally differentin some way. He attributed the reduction in the magnitude of duration estimatesby KR to initial over-estimators to an unspecied increase in excitatory processes and the increase in duration estimates in initial under-estimators to a decrease inexcitatory processes (italics in the original, Montare, 1988, p. 585). He inferred fromthis that the reduced magnitude responses during KR of initial over-estimators re-

ected a reduction of excitatory processes and that the increased magnitude of re-sponses of under-estimators reected increased excitatory processes. Our datasuggest otherwise. Erroneous feedback demonstrates that the direction of changein response magnitudes is a function of the target duration, not of a fundamental dif-ference in the participants themselves. The most parsimonious explanation is thatparticipants act to minimize the difference between the target performance and theirown performance.

This may also explain why 80% feedback produced larger effects than did 120%feedback. As most participants were initial under-estimators, the 120% target reectsa smaller error than does the 80% target. Thus the magnitude of response shift that weobserve reects the size of the error between performance and target performance.

Several studies, though, have shown that indicating the direction of the responseerror is as effective as providing information as to the magnitude of the error (Buc-kolz & Guay, 1975; Salmoni et al., 1984). This does not necessarily mean that mag-nitude information is lacking as directional correction over the course of successivetrials may provide the magnitude information. Indeed, we observed that the magni-tude of the difference between initial performance and the KR signaled target was apowerful predictor of the actual change in performance induced by KR.

4.5. Summary

KR can produce both learning and performance enhancing effects on time percep-tion tasks. On both a time reproduction task and an time estimation task, KR in-


8/14/2019 1-s2.0-S0001691802000446-main

17/18

duced three effects while it was presented: (1) a shift in the magnitude of the durationresponses, (2) a decrease in the variability of the group magnitude responses, and (3)no change in the variability of each participants individual responses. Thus, KRmore accurately centers each participants performance around a target without al-tering the dispersion of that participants responses. This effect was made particu-larly clear by using erroneous KR. The size of the change in response magnitudewas a function of the difference between a participants initial pre-KR performanceand the target specied by the KR. Thus KR provides targeting and guidance infor-mation. When KR is removed, the accuracy of the centering of performance aroundthe target values specied by the KR declined, suggesting that this action of KR is aperformance-enhancing action. In contrast, the change in response magnitude per-sisted following the withdrawal of KR, indicating that learning occurred. Since thetask-specic demands of the reproduction and estimation tasks are different, butthe performance and learning effects of KR appear to be very similar, KR might af-fect some shared, fundamental cognitive processes as well as task-specic processes.

Acknowledgements

This work was supported by the Department of Psychology at Oregon State Uni-versity. We specially thank the reviewers (anonymous reviewer A and Dr. M.J. Beu-kers) and the journal section editor (Dr. J. Wagemans) for helpful comments in

distinguishing participant and group variability.

References

Aiken, L. R. (1965). Learning and retention in the estimation of short time intervals a circuit and study.Perceptual and Motor Skills, 20 , 509517.

Allen, D. A., & Clark, C. A. (1979). Effect of information feedback on temporal discrimination inconcurrent and post-feedback measures. Perceptual and Motor Skills, 49 , 935939.

Block, R. A., & Zakay, D. (1997). Prospective and retrospective duration judgments: a meta-analyticreview. Psychonomic Bulletin and Review, 4 , 184197.

Buckolz, E., & Guay, M. (1975). Effects of feedback and procedures on human time estimation. Journal of Human Movement Studies, 1 , 132142.

Buekers, M. J., Magill, R. A., & Hall, K. G. (1992). The effect of erroneous knowledge of results on skillacquisition when augmented information is redundant. Quarterly Journal of Experimental Psychology.A, Human Experimental Psychology, 44 , 105117.

Buekers, M. J., Magill, R. A., & Sneyers, K. M. (1994). Resolving a conict between sensory feedback andknowledge of results, while learning a motor skill. Journal of Motor Behavior, 26 , 2735.

Craik, F. I. M., & Hay, J. F. (1999). Aging and judgments of duration: effects of task complexity andmethod of estimation. Perception and Psychophysics, 61 , 549560.

Crowder, A. M. H., & Hohle, R. H. (1970). Time estimation by young children with and withoutinformational feedback. Journal of Experimental Child Psychology, 10 , 295307.

Ferrara, A., Lejeune, H., & Wearden, J. H. (1997). Changing sensitivity to duration in human scalartiming: an experiment, a review, and some possible explanations. Quarterly Journal of Experimental Psychology. B, Comparative & Physiological Psychology, 50B , 217237.

Fraisse, P. (1984). Perception and estimation of time. Annual Review of Psychology, 35 , 136.


8/14/2019 1-s2.0-S0001691802000446-main

18/18

Gibbon, J., & Church, R. M. (1990). Representation of time. Cognition, 37 , 2354.Grondin, S. (2001). From physical time to the rst and second moments of psychological time.

Psychological Bulletin, 127 , 2244.Hicks, R. E., & Miller, G. W. (1976). Transfer of time judgments as a function of feedback. American

Journal of Psychology, 89 , 303310.Hoyer, W. J., Jones, E. C., White, R. S., & Maconachy, W. V. (1970). Effects of knowledge of the ITI on

time estimates. Perceptual and Motor Skills, 31 , 392394.Kladopoulos, C. N., Brown, B. L., Hemmes, N. S., & Cabeza de Vaca, S. (1998). The start-stop procedure:

estimation of temporal intervals by human participants. Perception and Psychophysics, 60 , 438450.McNevin, N., Magill, R. A., & Buekers, M. J. (1994). The effects of erroneous knowledge or results on

transfer of anticipation timing. Research Quarterly in Exercise and Sport, 65 , 324329.Montare, A. (1985). Learning effects of knowledge of results upon time estimation. Perceptual and Motor

Skills, 60 , 871877.Montare, A. (1988). Further learning effects of knowledge of results upon time estimation. Perceptual and

Motor Skills, 66 , 579588.

Salmoni, A. W., Schmidt, R. A., & Walter, C. B. (1984). Knowledge of results and motor learning: areview and critical reappraisal. Psychological Bulletin, 95 , 355386.Schmidt, R. A., Young, D., Swinnen, S., & Shapiro, D. C. (1989). Summary knowledge of results for skill

acquisition: support for the guidance hypothesis. Journal of Experimental Psychology: Learning,Memory and Cognition, 15 , 352359.

Staddon, J. E. R., & Higa, J. J. (1999). Time and memory: towards a pacemaker-free theory of intervaltiming. Journal of the Experimental Analysis of Behavior, 71 , 215251.

Zakay, D. (1990). The evasive art of subjective time measurement: some methodological dilemmas. In R.A. Block (Ed.), Cognitive Models of Psychological Time (pp. 5984). Hillsdale, NJ: Lawrence ErlbaumAssociates.


1-s2.0-s0001691802000446-main

Documents