Impact of Feedback on Goal Setting and task performance

B. Krenn et al.: Testing the Feedback Intervention TheorySwissJ. Psychol. 72 (2) 2013 Verlag Hans Huber, Hogrefe AG, Bern

Original Communication

The Impact of Feedback on GoalSetting and Task Performance

Testing the Feedback Intervention Theory

Bjrn Krenn1, SabineWrth2, and Andreas Hergovich3

1Centre for Sports Sciences and University Sports, University of Vienna, Austria, 2Department of SportScience & Kinesiology, University of Salzburg, Austria, 3Department of Applied Psychology: Work,

Education and Economy, Faculty of Psychology, University of Vienna, Austria

Swiss Journal of Psychology, 72 (2), 2013, 7989

DOI 10.1024/1421-0185/a000101

Abstract. This research project was undertaken in response to Kluger and DeNisis (1996) call for more primary studies to investigatespecific propositions of the feedback intervention theory (FIT). To study the assumptions of FIT on the level of task-motivation processes,we analyzed the impact of combined positive and negative feedback. Participants (N = 413) performed a series of tasks in which theywere to indicate the number of athletes appearing in short video sequences of different sports. After each task performance the participantsreceived manipulated feedback and were to choose between predetermined options (e.g., raise the level of difficulty, maintain the levelof difficulty). We found that the participants most frequently raised the difficulty level after receiving positive feedback and maintainedthe level after receiving negative feedback. There were no significant differences in the performance of participants who raised and thosewho maintained the difficulty level after receiving positive or negative feedback. However, the performance of participants who raisedthe difficulty level after receiving positive feedback increased more than that of those who maintained the difficulty level after receivingnegative feedback. In addition, we observed an increase in participants avoidance behavior in response to repeated negative feedback.The results partially confirmed the assumptions of the FIT.

Keywords: feedback intervention theory, task choice, goal orientation, motivation, avoidance behavior

The influence of feedback on human behavior is extensive.Various studies have shown the impact of feedback on dif-ferent behavioral aspects, such as motivation (e.g., Butler& Nisan, 1986; Deci, Koestner, & Ryan, 1999; Jussim, Sof-fin, Brown, Ley, & Kohlhepp, 1992; Narciss, 2004), learn-ing (e.g., Black & Wiliam, 1998; Goodman & Wood, 2004;Narciss & Huth, 2004; Pashler, Cepeda, Wixted, & Rohrer,2005; Wulf, Shea, & Lewthwaite, 2010), and goal orienta-tion (e.g., Cron, Slocum, VandeWalle, & Fu, 2005; Phillips,Hollenbeck, & Ilgen, 1996; Senko & Harackiewicz, 2005;VandeWalle, Cron, & Slocum, 2001). Feedback allows oneto compare the actual state with the target state and discov-er a discrepancy between actual and desired achievement.Thus, it enables one to evaluate ones previous perfor-mance in relation to a specific goal or standard. The per-ception of a possible discrepancy influences subsequentperformance.

Feedback information can originate from external sourc-es (e.g., teacher) or internal sources (information derivedby task processing itself, e.g., proprioceptive perceptionsin a motor task) (Butler & Winne, 1995; Magill, 2001; Nar-ciss, 2008). In line with this notion, Narciss (2008) suggest-ed the existence of two feedback loops: one that involved

the comparison of internal feedback to an internal referencevalue derived from a subjective estimation of task demandsand another that involved the comparison of external feed-back to an external reference value mainly derived fromexternal information (i.e., instructional goals). Thus, exter-nal feedback loops may correspond or conflict with internalfeedback loops. Both processes interact and together deter-mine the impact of feedback. In particular, Butler andWinne (1995) called attention to the significant role of in-ternal feedback in enabling self-regulated learning, wherea high amount of self-regulation is tied to an effective andeconomic learning process. Such learners monitor them-selves and their process of engagement by creating and an-alyzing internal feedback (see also Hattie, 2002). Thus, ex-ternal feedback primarily assists the perception of discrep-ancies between the internally represented actual and targetstate. It represents additional information confirming ormoderating internal feedback and may help the learner tosuccessfully execute self-regulated learning (Butler &Winne, 1995; Ilgen & Davis, 2000; Narciss, 2008).

Numerous studies (see Bangert-Drowns, Kulik, Kulik,& Morgan, 1991; Hattie & Timperley, 2007; Kluger & De-Nisi, 1996; Mason & Bruning, 2001; Mory, 2004; Narciss,

Swiss J. Psychol. 72 (2) 2013 Verlag Hans Huber, Hogrefe AG, Bern

2008; Shute, 2008) have revealed conflicting findingswhere feedback could have a positive, negative, or even adebilitating effect on performance. For example, Shute(2008) pointed out that despite a large amount of feedbackresearch, many conflicting and minor findings continue toexist. So far, several theoretical frameworks have been pro-posed and adopted that specifically try to explain these con-troversial feedback effects (e.g., Bangert-Drowns et al.,1991; Butler & Winne, 1995; Hattie & Timperley, 2007;Mason & Bruning, 2001; Narciss, 2008). The feedback in-tervention theory (FIT), developed by Kluger and DeNisi(1996), is one of the most important of these theories. Theauthors called for more primary studies to investigate spe-cific propositions of their theory. This research paper is aresponse to this call. To study the assumptions of FIT withrespect to task-motivation processes, we examined the im-mediate influence of possible combinations of positive andnegative feedback (consistent and inconsistent) on task per-formance and goal-setting.

The Feedback Intervention Theory(FIT)

The FIT (Kluger & DeNisi, 1996) is based on the assump-tion that behavior is regulated by comparisons of feedbackto goals or standards that are organized hierarchically. Theauthors distinguished three hierarchical levels at which the

impact of feedback on performance differs: task-learningprocesses, task-motivation processes, and meta-task pro-cesses. Attention is usually directed to the intermediate lev-el of the hierarchy (task-motivation processes), whereasspecific feedback interventions can change the locus of at-tention. Therefore, the style of feedback plays a crucial rolein regulating human performance (Brunot, Huguet, &Monteil, 2000; Lipnevich & Smith, 2009; Podsakoff &Fahr, 1989; Shute, 2008; Venables & Fairclough, 2009).For example, feedback focused on the details of a task (e.g.,information about the position of ones fingers when one islearning to play the guitar) directs ones attention to thelevel of task-learning processes. Additional informationabout the appropriate handling of a specific task facilitatesthe learning process. Hence, the feedback recipient can usethis information to improve his or her performance (Butler& Winne, 1995). Numerous studies confirmed this assump-tion: Feedback has been found to have more influencewhen details about how to improve performance are pro-vided (Hattie, 2002; Hattie & Timperley, 2007; Lipnevich& Smith, 2009; Magill, 2001; Narciss & Huth, 2004).

On the level of task-motivation processes, feedback is atfirst compared to the individual task standard. If a positivefeedback-standard discrepancy is revealed, the person has theopportunity to pursue other goals. Depending on the occur-rence of such an opportunity, the person either raises thestandard and increases his/her effort or maintains the standardand reduces his/her effort (see Bandura, 1991, 1997; Erez,2005; Hattie, 2002; Ilies & Judge, 2005; Locke & Latham,

Figure 1. Summary of the basic assumptions of the feedback intervention theory (FIT).

80 B. Krenn et al.: Testing the Feedback Intervention Theory


1990; McCalley, de Vries, & Midden, 2011; Phillips et al.,1996). However, if the feedback-standard discrepancy is neg-ative, participants effort increases. If the subsequent out-come is attained by a reduction in discrepancy, the FIT furthersuggests that participants effort increases or is at least main-tained (see Cron et al., 2005; Hattie, 2002; Ilgen & Davis,2000). If no reduction in discrepancy can be achieved, atten-tion is either directed toward the level of task-learning pro-cesses or toward the level of meta-task processes, dependingon the individuals belief in success.

Feedback that is related to the self, such as explicitly pos-itive or explicitly negative feedback, directs ones attentionto the level of meta-task processes. Even feedback that con-tradicted participants performance history (e.g., positivefeedback for low achievers) was shown to enhance self-fo-cused attention (Brunot et al., 2000). On this level, negativefeedback motivates people to reduce the feedback-standarddiscrepancy. Therefore, one possibility is to redirect attentionto the task-motivation processes and to attempt to improveperformance. An easier alternative is to withdraw from thetask and engage in other activities (Hattie, 2002; Ilgen &Davis, 2000; Klein, 1997; Pulfrey, Buchs, & Butera, 2011;Venables & Fairclough, 2009). In this case, performance de-clines. The main aim at this level is to protect oneself fromrepeated negative feedback and to attain a positive self-im-age. Ilgen and Davies (2000) emphasized that repeated neg-ative feedback lowers expectations and therefore makesavoidance behavior more probable. Thus, decisions like quit-ting or choosing a higher task difficulty represent an oppor-tunity to protect ones self-image. Raising the level of diffi-culty diminishes the relevance of repeated negative feedbackdue to the knowledge of the increased difficulty of the task.Furthermore, the negative feedback is attributed more to thetask complexity than to ones own failure.

Kluger and DeNisi (1996) pointed out that their three-levelhierarchy is an abstraction. They assumed that the hierarchycould be more complex and contain more sublevels. More-over, it seemed possible that these levels interact with eachother, and attention is directed to each level to varying de-grees. Therefore, a specific feedback intervention could leadto more than one feedback-standard comparison. In addition,the possible discrepancies could be weighted and integratedinto an overall reaction to the feedback. Figure 1 summarizesthe basic assumptions of the FIT.

Previous Research on the Impact ofFeedback on the RelationshipBetween Goal Setting andPerformance

Feedback research has shown that feedback mostly in-creased performance (see Bangert-Drowns et al., 1991;Hattie & Timperley, 2007; Mason & Bruning, 2001; Mory,

2004; Narciss, 2008; Shute, 2008). However, Kluger andDeNisi (1996) revealed in their meta-analysis that at leastone third of the included studies reported decreasing effects(see also Ilgen & Davis, 2000). According to these results,not only the style of feedback, but also the specificity ofgoals (e.g., Erez, 2005; Hattie & Timperley, 2007; Ilies &Judge, 2005; McCalley et al., 2011; VandeWalle et al.,2001) and the characteristics of the task (e.g., DeShon &Alexander, 1996; Hattie & Timperley, 2007; Magill, 2001;Vancouver & Tischner, 2004) have been identified as im-portant factors that moderate feedback effects. The biggestinfluence on performance may be expected when perform-ing a low-difficulty task and goals are attainable, clear, andspecific (see DeShon & Alexander, 1996; Ilgen & Davis,2000; Kluger & DeNisi, 1996). Previously, Erez (1977)demonstrated that feedback had a significant impact ongoal-setting and pointed out its role in the relationship be-tween goal-setting and performance (Carver & Scheier,1981; Cron et al., 2005; Erez, 2005). Goals represent levelsof performance that are attained by individuals. Hence,they enable a person to evaluate his/her actions and efforts(Locke & Latham, 1990). Therefore, feedback is necessaryfor evaluating discrepancies between selected goals and ac-tual achievement by showing ones progress toward thegoal. It seems helpful to adjust effort, achievement, strate-gies, or tactics to meet the target, but also to set reasonablegoals. In this regard, it was shown that not only does goal-setting affect the impact of feedback but that feedback in-fluences subsequent goal-setting (Cron et al., 2005). Posi-tive feedback was found to enhance recipients decision toset more difficult goals, whereas negative feedback result-ed in a tendency for them to lower their goals (Donovan &Williams, 2003; Ilies & Judge, 2005; Phillips et al., 1996;Tolli & Schmidt, 2008; VandeWalle et al., 2001; Williams,Donovan, & Dodge, 2000; see also Ilies, Judge, & Wagner,2010). The setting of more difficult goals after receivingpositive feedback is tied to social cognitive theory (Ban-dura, 1997), according to which individuals create positivediscrepancies (set higher goals than in previous task per-formances) and try to succeed, as long as they assess themore difficult goals as attainable. Indeed, more difficultgoals go along with a lower probability of success but nev-ertheless greater stimulation by reaching this goal at a high-er level of performance (Bandura, 1997; Kluger & DeNisi,1996). On the other hand, creating less challenging goalsincreases the probability of success. Thus, the chance torebuild or maintain ones self-concept is augmented (Bau-meister, 1996; Hattie, 2002; Kluger & DeNisi, 1996; Van-couver & Tischner, 2004). In addition, Klein (1997) dem-onstrated that normative positive feedback as opposed tonormative negative feedback enhanced participants de-cision to persevere instead of switching to another task.However, these results have to be interpreted carefully con-sidering the individuals assessment of feedback: Podsa-koff and Fahr (1989) demonstrated that feedback credibil-ity mediated the relationship between feedback and goal-setting as well as performance.

B. Krenn et al.: Testing the Feedback Intervention Theory 81


Aims of the Current Study

This study examines the assumptions of the FIT on the levelof task-motivation processes. Kluger and DeNisi (1996)presumed that changes in achievement and goal-setting oc-cur as a result of both positive and negative feedback-stand-ard discrepancies. The following hypotheses were de-duced: H1: Following positive feedback, participants raise their

standard more often than following negative feedback. H2: Participants who raise their standard after receiving

positive feedback enhance their performance more thanparticipants who maintain their standard after receivingpositive feedback.

In contrast to positive feedback, raising the standard afterreceiving negative feedback offers the possibility of de-creasing the relevance of repeated negative feedback dueto awareness of the increased level of difficulty. Therefore,our next hypotheses were: H3: In the negative feedback condition, participants who

practice or maintain their standard enhance their perfor-mance more than those who raise their standard.

H4: Repeated negative feedback causes avoidance be-havior more often than a single reception of negativefeedback.

The FIT assumes an increase in performance when raisingthe standard after receiving positive feedback or maintain-ing the standard after receiving negative feedback. As an

additional approach and a possible expansion of FIT, wewere interested in a comparison of both scenarios. H5: Participants who raise their standard after receiving

positive feedback show an improvement in performanceequal to that of participants who maintain their standardafter receiving negative feedback.

Method

Participants

The study was conducted at the University of Vienna (Aus-tria) with 413 students (247 female, 166 male) participatingin exchange for course credit. The participants were stu-dents of sports science (n = 242) and psychology (n = 171).The average age of the participants was 21.90 (SD = 3.42)years, ranging from 18 to 43. Data collection took placefrom November 2009 to April 2010.

Application of the Feedback InterventionTheory

To investigate the impact of positive and negative feedbackon performance and goal-setting, a computer-assisted ad-aptation of the FIT was constructed. Figure 2 illustrates theconfiguration schematically. Overall, a task was performedthree times and manipulated feedback was presented afterthe first two task performances. After receiving feedback,

Figure 2. Illustration of the constructed task modulation for all feedback conditions. T1 = first task; T2 = second task; T3= second presentation of the first task.



participants were asked to choose between predeterminedoptions. Thus, two feedback loops were created in whichthe impact of feedback on goal-setting and performancecould be tested: The feedback received after the first timethe task was performed allowed us to analyze the impactof feedback on subsequent goal-setting and on task perfor-mance when the task was performed the second time (firstfeedback loop). The second feedback loop included thefeedback received after the second time the task was per-formed, subsequent goal-setting, and task performancewhen the task was performed the third time.

Feedback Conditions

The study was limited to investigating the impact of posi-tive and negative feedback-standard discrepancies. There-fore, the manipulation of feedback was appropriate. Thefeedback interventions used were either positive or nega-tive, irrespective of actual performance. Before performingthe task, participants received information concerning theexpected average performance on the subsequent task (e.g.,average performance represents a correct response to eightout of 15 items). This information was given to establish astandard of performance. Feedback interventions werebased on this standard: In the negative feedback condition,participants were told that they had given two or three cor-rect responses, and that their performance was very belowaverage. In the positive feedback condition, participantswere told that they had given 13 or 14 correct answers, andthat their performance was very above average. Providingnegative or positive feedback after the first two task per-formances resulted in four different feedback conditions.In the first condition, participants received positive feed-back twice (positive-positive); in the second, they receivednegative feedback twice (negative-negative). Participantsin the third condition received negative feedback after per-forming the first task and positive feedback after perform-ing the second task (negative-positive). In the fourth con-dition, participants received positive feedback after the firsttask performance and negative feedback after the secondtask (positive-negative).

Task Performance

To investigate the impact of feedback on performance, wechose a task to measure selective attention. The importanceof selective attention for several cognitive performance pa-rameters (e.g., concentration, memory, perceptual speed)and the possibility of an economical and less time-consum-ing measurement prompted this decision. The items repre-sented short videoclips showing different kinds of sportsthat had been selected from television broadcasts. The par-ticipants task was to indicate the number of athletes ap-pearing in each clip by pressing the corresponding numberkey on the computer keyboard. The number of athletes

shown ranged from four to nine. The difficulty was to dis-tinguish between active athletes, referees, and substitutesas well as offcourt viewers. Moreover, the duration of thepresented videoclips was very short (1,941 ms) and the re-action time was limited (2,000 ms). After the participantsreaction or after time had elapsed, the next videoclip wasstarted. The duration of 1,941 ms resulted from specificcharacteristics of the software programs for editing andpresenting the videoclips. Two tasks were devised, bothconsisting of 15 items. In previous studies, the internal con-sistency of both tasks was Cronbachs = .78. Based ontetrachoric correlation, a split-half reliability of r = .90 wasachieved. The correlation of the tasks was r = .82. Becauseof the demand of performing three different tasks in thecomputer modulation of the FIT, the first task was repeatedat the end of the second feedback loop.

Goal-Setting

After the first and second feedback intervention, partici-pants were asked to choose between predetermined op-tions. These options were deduced from the task-motiva-tion processes of FIT and differed with respect to type (neg-ative or positive) and loop of feedback. There were fiveoptions to choose from, whereas three alternatives werepresented continuously: maintain the standard, raise thestandard, and abort. Maintaining the standard meantchoosing a task with the same difficulty level. Raising thestandard meant increasing the difficulty level: Participantswere told that the following task would be more difficultthan the previous one and that the task standard would behigher. This information was simulated; all participantsperformed the same task in the second feedback loop. Thisdeception was necessary to compare task performance withrespect to different decision behaviors. The third option,which was always presented, was to abort the task. An ad-ditional alternative was provided in the negative feedbackcondition: practice and maintain the standard. Participantswho chose this option received an additional sequence ofthree trial items in which immediate feedback for correctanswers was presented. Afterwards they were to perform atask with the same level of difficulty. In the repeated neg-ative feedback condition, participants were also given thechance to perform an alternative task, which was a shortpair-based game. This alternative was offered to introducethe additional possibility of handling repeated negativefeedback in contrast to aborting the task.

Procedure

The experiment was conducted under laboratory conditionsand for each participant separately. Depending on whenthey arrived at the laboratory, participants were assigned toone of four feedback conditions. In the run-up to the exper-iment, participants were told that the research was about

B. Krenn et al.: Testing the Feedback Intervention Theory 83


the development of a task to measure selective attention.After being welcomed, the participants were asked to pro-vide informed consent to participate in the study. The fol-lowing task was performed on a computer. Participantswere told to follow the instructions on the screen. Duringthe experiment, a supervisor stayed in the laboratory to as-sist with problems or answer participants questions. At theend of the semester, the actual research objective was re-vealed to the participants.

Results

Statistical Analysis

Pearsons chi-square tests () were conducted to comparegoal-setting behavior in different feedback conditions. Theassumption of an expected cell count of at least five wasmet consistently. To investigate the effect of the chosenoptions on achievement, we carried out repeated-measuresanalyses of variance (ANOVA). The sums of correct reac-tions for each task were included as dependent within-sub-jects variables. The chosen options were used as between-subjects factors. The assumptions of repeated-measuresANOVA were met and are not specifically reported. Statis-tical significance in all cases was p < .05.

The First Feedback Loop

Two conditions were analyzed in the first feedback loop.After performing the first task, participants in two feedbackconditions (NN and NP) received negative feedback, whilethose in the other two conditions (PP and PN) received pos-itive feedback. Table 1 shows the frequency of the chosenoptions with respect to the feedback condition. To examinethe first hypothesis, the options maintain standard andpractice and maintain standard in the negative feedbackcondition were collapsed. One participant aborted the taskand was excluded from further data analysis. Pearsons chi-square test of the 2 2 contingency table revealed a signif-icant difference between the two conditions, = 212.86,df = 1, p < .001). After receiving positive feedback, 84.5%of the participants raised their standard, whereas only12.7% chose this option after receiving negative feedback.Thus, Hypothesis 1 was confirmed: Participants who re-ceived positive feedback raised their difficulty level signif-

icantly more often than those who received negative feed-back.

A repeated-measures ANOVA was conducted for thepositive and the negative feedback conditions separatelyto test Hypotheses 2 and 3. In the positive feedback con-dition, we assumed that participants raising the standardwould show a greater increase in performance than thosemaintaining the standard. Repeated-measures ANOVA re-vealed a significant effect of performance in both tasks,F(1, 205) = 44.91, p < .001, 2 = .18, but no significantinteraction between performance and the chosen option,F(1, 205) = .79, p = .375. Differences in time betweenparticipants raising the standard and those maintaining thestandard were not significant. The between-subjects effectwas significant, F(1, 205) = 12.85, p < .001, 2 = .059. Itshould be noted that, due to the unequal number of par-ticipants raising versus maintaining the standard after re-ceiving positive feedback, the results of repeated-mea-sures ANOVA have to be interpreted carefully. Hypothe-sis 2 had to be rejected. In the negative feedbackcondition, we hypothesized that participants practicing ormaintaining their standard would enhance their perfor-mance more than those raising the standard. There wereno significant differences in performance between partic-ipants selecting different options, F(2, 202) = .27, p =.766, and there was no significant interaction between thechosen options and task performance, F(2, 202) = 2.47, p= .087. The effect of performance of the first and secondtask was significant, F(1, 202) = 17.41, p < .001, 2 =.079. Thus, Hypothesis 3 was rejected. Table 2 shows themeans and standard deviations of performance on the firstand second task with respect to the selected option andfeedback condition.

The Second Feedback Loop

Corresponding to the feedback intervention in the firstfeedback loop, four different conditions were tested in thesecond loop: two consistent and two inconsistent feedbackconditions. In the consistent feedback conditions, partici-pants were confronted with either repeated positive feed-

Table 1Frequencies of the chosen options in the first feedback loopFB condition Raise

standardMaintainstandard

Practice andmaintainstandard

Abort

Positive 175 32 X Negative 26 113 66 1Note. X = option was not offered, FB = feedback.

Table 2Means (M) and standard deviations (SD) of the perfor-mances in the first (T1) and the second task (T2) consider-ing feedback condition and the selected optionsFeedback Selected option n T1 T2

M (SD) M (SD)Positive Raise standard 175 7.15 (2.26) 8.56 (2.55)

Maintain standard 32 5.53 (2.02) 7.38 (2.64)Negative Raise standard 26 6.54 (2.63) 7.69 (3.32)

Maintain standard 113 7.03 (2.49) 7.45 (2.68)Practice and main-tain standard

66 6.77 (2.60) 8.12 (2.67)



back (PP) or repeated negative feedback (NN). A combi-nation of positive and negative feedback was presented(negative before positive, NP, and positive before negative,PN, feedback) in the inconsistent feedback conditions. Af-ter the second feedback intervention, participants were todecide again. To test Hypothesis 4, participants second de-cisions in the repeated negative feedback condition and thepositive-negative feedback condition were compared. Weassumed that repeated negative feedback would cause moreavoidance behavior than a single reception of negativefeedback. The options alternative task, which was limit-ed to the repeated negative feedback condition, and abortwere collapsed because of their similar meaning of avoid-ance behavior. The chi-square test of the 2 4 contingencytable revealed a significant difference in decision behaviorbetween the two conditions, = 24.15, df = 3, p < .001.Thus, Hypothesis 4 was confirmed: Avoidance behaviorincreased after repeated negative feedback. Table 3 showsthe frequencies of the chosen alternatives for each feedbackcondition.

To examine Hypothesis 5, performance on the first andsecond task (feedback loop 1) were initially compared be-tween participants maintaining the standard after havingreceived negative feedback (n = 113) and those raising thestandard after having received positive feedback (n =175). We hypothesized that both groups of participantswould show an equal improvement in performance. Re-peated-measures ANOVA revealed a significant effect ofperformance in both tasks, F(1, 286) = 33.92, p < .001, 2= .106, a significant between-subjects effect, F(1, 286) =5.95, p = .015, 2 = .020, and a significant interaction of

task performance and chosen options, F(1, 286) = 9.79, p= .002, 2 = .033. Participants who raised the standardafter receiving positive feedback performed better thanthose who maintained the standard after receiving nega-tive feedback. In addition, to enable a more specific anal-ysis, a repeated-measures ANOVA with all three task per-formances as within-subject variables was conducted.Three groups were included as between-subject factors:participants who had raised the standard twice in the re-peated positive feedback condition (n = 81); participantswho had maintained the standard after receiving negativefeedback and raised the standard after receiving positivefeedback in the negative following positive feedback con-dition (n = 47); and participants exhibiting the same deci-sion behavior in the positive following negative feedbackcondition (n = 56). Participants who maintained the stand-ard twice in the repeated negative feedback conditionwere not included because of the small sample size (n =17). The between-subjects effect was not significant,F(2, 181) = .70, p = .499). The difference in performanceof the three tasks was significant, F(2, 362) = 25.21, p

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Impact of Feedback on Goal Setting and task performance