JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT
2019, VOL. 39, NOS. 3–4, 164–178
https://doi.org/10.1080/01608061.2019.1632242

RESEARCH ARTICLE

The Interaction Effects of Frequency and Specificity ofFeedback on Work Performance
Jin-A Parka, Douglas A. Johnsonb, Kwangsu Moonc, and Jaehee Leeda

Click Consulting, Seoul, Korea; bWestern Michigan University, Department of Psychology, Kalamazoo,
Michigan, USA; cChung-Aug University, Department of Psychology, Seoul, Korea; dKorea Institute ofChild Care and Education, Fundamental Research and Statistics Team, Seoul, Korea
ABSTRACTARTICLE HISTORYThis study investigated the interaction effect between specificity (specific vs. global) and frequency of feedback (frequent vs.
infrequent) on the quality of work performance. Eighty participants were recruited and randomly assigned to one of the fourgroups: specific and frequent feedback, global and frequent
feedback, specific and infrequent feedback, and global andinfrequent feedback. A 2 × 2 factorial design was adopted.
Participants were asked to work on a simulated order-fulfillingtask and attended 24 sessions. The dependent variable was theerror rate of the completed tasks. The results showed that
more frequent feedback was more effective and specific feedback was more effective than global feedback in improving thequality of performance. Furthermore, an interactive effectbetween feedback frequency and specificity was found.
Specific feedback was more effective than global feedback
when the feedback was infrequent, but global feedback wascomparable to specific feedback when it was frequent.

Received 24 Jul 2018
Accepted 16 Dec 2018
Revised 18 Nov 2018
KEYWORDS

Specific feedback; global
feedback; feedback
frequency; feedback

Feedback has a long history of successful applications in the literature ofOrganizational Behavior Management (Balcazar, Shupert, Daniels, Mawhinney,& Hopkins, 1989; Bucklin, Alvero, Dickinson, Austin, & Jackson, 2000; Nolan,
Jarema, & Austin, 1999; VanStelle et al., 2012). Feedback has been applied as anintervention component or as the primary independent variable itself in variousorganizational settings and types of performance, such as sales (Loughrey,
Marshall, Bellizzi, & Wilder, 2013; Tilka & Johnson, 2018), safety (Hagge,
McGee, Matthews, & Aberle, 2017; Lee, Shon, & Oah, 2014; Myers, McSween,
Medina, Rost, & Alvero, 2010), quality control (Berglund & Ludwig, 2009; Choi,
Johnson, Moon, & Oah, 2018; Goomas & Ludwig, 2017), and customer service(Eikenhout & Austin, 2005; Reetz, Whiting, & Dixon, 2016; So, Lee, & Oah, 2013).
Despite this distinguished history, it would be inappropriate to elevate
feedback to the status of a principle of behavior (Peterson, 1982). Feedback is
simply a stimulus and like any stimulus it can come to serve any number of
CONTACT Douglas A. Johnson
behavioranalyst@gmail.com
P.O. Box 20415, Kalamazoo, MI 49019
This article has been republished with minor changes. These changes do not impact the academic content of the article.
Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/worg.
© 2019 Taylor & Francis

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functions as an antecedent (e.g., discriminative stimulus, conditioned motivating operation) or consequence (e.g., conditioned reinforcer, conditioned
punisher) for behavior (Alvero, Bucklin, & Austin, 2001; Johnson, 2013;
Johnson, Rocheleau, & Tilka, 2015; Prue & Fairbank, 1981). Just as there isgreat variation to the potential functions of feedback, there is great variation
to the potential forms feedback, which in turn has led to a great variation in
the recommendations for the delivery of feedback. Among the recommendations is that the more specific feedback is, the more effective it will be(Braksick, 2007; Daniels & Bailey, 2014; Kopelman, 1986). Williams andGeller (2000) classified feedback based on specificity into two types: specificand global. Specific feedback is defined as “the percentage of safe behavior
occurrence over a given period of time for a certain target behavior . . .
whereas global feedback is defined as an overall safety score based on thepercentage of safe work practices over a given time period across a certain
number of behaviors” (p. 136). Although these classifications are tied tosafety performance, the concepts of specific and global feedback can bebroadened to apply to non-safety related workplace implementations as
well. Specific feedback can instruct workers on how to execute a task andprovide helpful information in order to correct inappropriate task performance. In addition, specific feedback can reduce uncertainty about how wellor poorly an individual is performing on a task (Ashford, 1986; Ashford &Cummings, 1983).
However, there have only been two published studies (Lee et al., 2014;
Williams & Geller, 2000) that compare the relative effects of specific andglobal feedback on performance. Lee, Shon, and Oah examined the relative
effects of two types of feedback on safety performance and compared thegeneralization of such feedback to non-targeted safety items at a construction
site. The results from this study revealed comparable safety performancelevels under the two feedback conditions. However, global feedback produced more of a generalized effect than specific feedback on non-targeted
items. The results from Williams and Geller’s study indicated that whensocial comparison feedback was provided, safety performance was comparable for both specific and global feedback; whereas specific feedback was
more effective in improving performance than global feedback when social
comparison feedback was not provided. These results suggest that specificfeedback is not always more effective than global feedback. The contradictions between the results of empirical studies and common recommendations, as well as the fact that few studies have investigated this topic, warrants
further research.
Furthermore, it may the case that other variables may modulate theeffectiveness of specific feedback. For example, Daniels and Bailey (2014)
suggested that specific information is not always necessary because the “moreimmediate the reinforcer, the less specific it has to be” (p. 198). Immediate

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feedback may be effective even though it does not include specific information because the performer can easily rely on a history of successful performance without having to identify behavior that needs change. Increasing thefrequency with which feedback is delivered will typically reduce the temporalgap between performance and feedback regarding that performance. This
relates to another general recommendation regarding the delivery of feedback: The more frequent the delivery of feedback, the more effective it willbe. However, once again, the empirical evidence does not always cleanly alignwith conventional wisdom. For example, Balcazar, Hopkins, and Suarez(1986) found similar results comparing the effectiveness of daily and weekly
feedback (42% and 41%, respectively), yet these frequencies yielded moreconsistent effects than monthly feedback (13%). Alvero et al. (2001) reported
different results. They found that the percentage of consistent effects formonthly feedback (80%) was higher than the percentages for both daily andweekly feedback (71% and 52%, respectively). In addition, the results ofprevious studies directly comparing the relative effectiveness of different
frequencies of feedback on performance have been mixed (Alavosius &Sulzer-Azaroff, 1990; Chhokar & Wallin, 1984; Kang, Oah, & Dickinson,
2003; Leivo, 2001; Mason & Redmon, 1992; Pampino, MacDonald, Mullin, &Wilder, 2003; So et al., 2013; Van Houten, Nau, & Marini, 1980).
For example, So et al. (2013) compared the relative effects of daily andweekly feedback on customer service at a gas station. Their results indicatedthat service behaviors improved when weekly feedback was introduced andimproved further still when daily feedback was introduced. In contrast, Van
Houten et al. (1980), Chhokar and Wallin (1984), and Leivo (2001) all foundthat varied frequency of feedback did not result in a difference in performance. Specifically, Chhokar and Wallin examined the relative effects ofweekly and biweekly feedback, along with training and goal setting, on safety
behavior in a manufacturing setting. The results indicated that weekly feedback did not produce better safety performance than biweekly feedback.
In other research (Alavosius & Sulzer-Azaroff, 1990; Kang et al., 2003), theeffect frequency of feedback had on performance depended on other experimental conditions. For example, Alavosius and Sulzer-Azaroff compared therelative effects of continuous feedback, intermittent feedback, and no feedback on the acquisition and maintenance of safety behavior for healthcare
staff. The results indicated that continuous feedback increased the acquisitionof behavior more than intermittent feedback. However, there was no difference in the maintenance of safety behavior with either type of feedback. Kang
et al. examined the effects of two frequencies of feedback on work performance under hourly and incentive pay conditions. Their results indicatedthat more-frequent feedback produced better performance than less-frequent
feedback for the incentive pay groups. However, no performance difference
was found for the hourly pay groups.

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The inconsistency of results within the feedback literature highlights theneed for component analyses to isolate and compare the various options forthe delivery and composition of feedback (Johnson, 2013). Different implementations of feedback may alter the function of feedback and evoke different kinds and levels of performance. Regarding specific feedback, it ispossible that corrective feedback may function as a reflexive conditioned
motivating operation (CMO-R) in that the feedback establishes conditions
that evoke behavior to remove such conditions (Johnson & Akpapuna, 2018;
McGee & Johnson, 2015; Michael, 2004). For example, corrective feedback
may establish a threat condition that is correlated with a progressive worsening if performance does not improve. However, global feedback may involvea different type of CMO-R than specific feedback and thus evoke different
behaviors. To put it loosely, global feedback may involve a notification thatsomething is wrong and as a result an employee engages in a wide variety ofgeneral improvements (which may or may not involve the performance ofinterest to the supervisor), whereas specific feedback may involve a notification that this is wrong and as a result the employee focuses their performance
improvement efforts on a specific set of behaviors. In this manner, specificfeedback fosters a precise calibration of performance whereas global feedback
fosters a broad calibration of performance. This may account for the greater
generalized effects of global feedback but implies a risk that the performancethat is of primary interest may be neglected. As a consequence for behavior,specific feedback may serve to reinforce a narrower class of behaviors thanglobal feedback. Of course, this can be problematic if the breadth of global
feedback leads to a strengthening of irrelevant or undesirable behaviors.
Feedback delivered with great frequency may operate in a somewhat
similar manner. As noted earlier, corrective feedback could potentially operate as a CMO-R. One feature of a CMO-R is that it includes a self-terminating feature (Johnson & Akpapuna, 2018), in that it evokes behaviors that willlessen or remove the motivating operation (i.e., the employee works toeliminate the warning and the correlated threat). Once the value-altering
properties of the CMO-R are weakened, the behavior-altering properties will
also cease until the CMO-R is re-established (i.e., the threat is gone until a
new threat is delivered). Frequent corrective feedback may involve a more
frequent establishment of the CMO-R, resulting in an overall higher frequency of desired performance. As a consequence for behavior, frequent
feedback will result in a denser schedule of reinforcement than infrequent
feedback, which may be an important consideration if one is dealing with awell-learned or new performance given the differences in effectiveness ofcontinuous reinforcement and intermittent reinforcement for the development and maintenance of behavior.
Of course, many other potential behavioral functions of specific or frequent feedback should not be ruled out (SD for reinforcement or

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punishment, CMO-T, punisher, etc.). Not only are component analyses
important for resolving inconsistencies, they may be important for practicalreasons as well. There are often time and financial costs involved in theimplementation of feedback, whether it is frequent or specific in nature. Even
though evolving technology has mitigated some of the costs in delivering
feedback (Goomas & Ludwig, 2009, 2017), organizations still need to invest
resources when they commit to implementing systems that standardize thedelivery of feedback. These investments may involve the purchase of equipment to facilitate assessment and communication, managerial time for monitoring and evaluation, etc. If the components of feedback have an additiveeffect without placing an undue burden on the organization, such investments may be justified. Otherwise, a simpler intervention package may be
warranted. The present study seeks to illuminate these considerations byexamining the interaction effect between the specificity and frequency of
feedback on the quality of work performance.
MethodParticipants and setting

A total of 80 undergraduate students (47 males and 33 females) with a mean
age of 21.5 (SD = 1.58) from a university in South Korea participated in thisstudy. They were recruited via advertisements posted on the online university
bulletin board. The experiment was conducted in campus computer laboratories containing 60 personal computers with the same specifications andoperating system.
Experimental task

An order fulfillment task for a computer-simulated distribution center wasdeveloped for this study. As seen in Figure 1, this software would display
icons representing stock to select from, shipping pallets, and order sheets
listing the specifications required for the current order.
As part of completing the displayed order, participants would drag anddrop stock items to a pallet. Stock items were organized in groups of 10 items
that were placed in one of 10 district locations for a total of 100 stock items
to be selected from. An order sheet was placed in the center of the screen,with odd-numbered districts located on the left and even-numbered districts
located on the right. The sheet included the information that participants
needed to perform the tasks: location number where the product belongs(LOC), the name of the product stacked in each item (PROD), the number of
products that must be loaded onto the pallet (QTY TO PICK), the productweight (WEIGHT), and the fragility mark of the product (CAUTION). WhenJOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

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Figure 1. Work task used in this study.

the mouse pointer was hovered above the box of products, it was possible toview the full product name.
Successful completion of this task required three important steps. The firststep was to read the information on the order sheet. The second step was todecide on the order in which the items should be loaded onto the pallet,
considering the CAUTION and WEIGHT labels. The five items listed on theorder sheet had to be stacked according to the following rules in order toavoid damage:(1) An item labelled CAUTION (O) must be stacked last, no matter what
its weight.
(2) Items are to be stacked in descending order according to weight(3) If two items have the same weight, they are to be stacked in ascendingorder of the item number
The third step was to load the items onto the pallet. The loading method
was to drag the item onto the shipping pallet icon on the bottom center ofthe screen and then click the “Complete an item selection” button. Thisbutton was activated if any five items were loaded. New tasks were started
after clicking the “Complete an order” button. Participants were asked tocomplete five order sheets per session, thus processing 25 items and fivepallets. The participants’ performance results were saved automatically by thesimulation program.

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Dependent variables

The dependent variable was the average rate of six errors that could occur
during task performance. Similar to the loading errors measured in Berger
and Ludwig (2007), the current study defined errors according to the following criteria:(1) Omit: Failing to load listed items onto the pallet(2) Mispick: Loading unlisted items onto the pallet(3) Shortage: Loading fewer products of each item onto the pallet thanwere listed on the order sheet(4) Over: Loading more products of each item onto the pallet than werelisted on the order sheet(5) Weight damage: Loading items onto the pallet without complying withstacking rule(6) Drop damage: Dropping product outside the pallet area
The above six errors were automatically recorded by the simulation program. The proportion of each error was calculated as (number of items witheach error(s)/total number of items) x 100. The average rate of error was
calculated as (Σ Proportion of each error/6).
Independent variables and experimental design

The independent variables of this experiment were frequency (Frequent/
Infrequent) and specificity (Specific/Global) of feedback. Similar to the definition used by Kang et al. (2003), one feedback delivery at the end of eachexperimental session was defined as frequent feedback, whereas one feedback
delivery at the end of every fourth experimental sessions was defined as
infrequent feedback. Using Williams and Geller (2000) as a model, specificfeedback was defined as offering feedback about each of six recorded errors(e.g., a total of 25 items are executed, with error rates as follows: Omit-40%,
Mispick-35%, Shortage-20%, Over-0%, Weight Damage-10%, Drop Damage0%), whereas giving the average rate of six errors (e.g., a total of 25 items are
executed, and the average rate of six errors is 13.33%) was defined as global
feedback. A 2 × 2 factorial design was adopted and composed of the four
feedback conditions: frequent & specific feedback, frequent & global feedback, infrequent & specific feedback, and infrequent & global feedback.
Feedback was presented by the computer automatically.
Procedure

All participants attended a 30-minute orientation prior to the experiment.
During this orientation, participation consent forms were collected and the

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experimenter explained how to operate the simulated work task. The participants could review the instructions by examining printouts that were provided
in advance. Participants were also given a chance to ask any questions. After theverbal explanation, a visual demonstration was shown through a projector.
Subsequently, the participants were given 10 minutes to practice the assignments
themselves with another opportunity to ask questions. This orientation concluded when participants could correctly complete 4 out of 5 assignments. All
participants were offered an equal participation fee of 20 and informed that thefee would be provided at the completion of the experiment.
After the orientation session, participants took part in a total of 24 experimental sessions, with 8 sessions each day according to the participants’ individual schedules. The length of each experimental session was defined by thecompletion of five pallets, rather than by a fixed length of time, in order to makethe task more similar to order fulfillment work in the field. Although there wasno time limit for conducting the task, the participants were still asked tocomplete the task as quickly as possible. All participants performed work tasks
in the same computer laboratory, but there was no interaction between theparticipants, even when working simultaneously, due to being placed far apart.
The computer programs were set to present feedback automatically in accordance with the experimental conditions for each group. When each participant
had completed eight experimental sessions, the researcher gathered the information saved on the computer. The participants were permitted to take a break, use
the lavatory, and use mobile phones, messengers, and computer games whenever they pleased during the experiment.
Results
Table 1 shows means and standard deviations of the six errors across eachexperimental group. Regardless of the error type, the error rate was thehighest for the infrequent and global group than for the other three groups.
The mean of the six error types for participants in the frequent/global feedback, frequent/specific feedback, infrequent/global feedback, and infrequent/specific feedback, was 5.74 (SD = 3.16), 5.67 (SD = 3.03), 9.94 (SD = 6.02),
and 5.75 (SD = 3.28), respectively (see Table 1). To decide whether the error
rate differed across feedback frequency and specificity, a two-way analysis ofvariance (ANOVA) was conducted. The main effect of feedback frequency
Table 1. Means and standard deviations of the six errors.
Omit

Mispick

Shortage

Over

Weight Damage

Drop Damage

Frequency

Specificity

M(SD)

M(SD)

M(SD)

M(SD))

M(SD)

M(SD)

M(SD)

Frequent

GlobalSpecific
GlobalSpecific

9.22 (5.04)
9.37 (5.22)
17.97 (15.25)
10.58 (8.91)

7.86 (4.46)
8.32 (3.89)
10.94 (4.07)
8.53 (5.47)

10.67 (6.08)
10.33 (5.68)
20.09 (16.68)
11.95 (9.63).29 (.23).19 (.15).42 (.38).23 (.30)

3.01 (1.48)
3.30 (1.52)
3.91 (1.54)
2.72 (1.90)

3.37 (2.32)
2.51 (1.86)
7.20 (13.68)
1.46 (1.38)

5.74 (3.16)
5.67 (3.03)
9.94 (6.02)
5.75 (3.28)

InfrequentOverall

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and specificity was statistically significant (F(1, 76) = 5.52, p = .02, η2 = .07; F(1, 76) = 5.48, p = .02, η2 = .07, respectively). The interaction effect was also
statistically significant, F(1, 76) = 5.15, p = .03, η2 = .06. Figure 2 displays thepattern of the interaction effect.
An analysis of the simple main effect was conducted to measure differences in error rates between global and specific feedback for both thefrequent and in frequent feedback groups. For the frequent feedback group,
the effect of feedback specificity was not statistically significant (F(1,76) = .00, p = .96, η2 = .00). For the infrequent feedback group, however, asignificant difference between global and specific feedback was found (F(1,76) = 10.63, p = .00, η2 = .12).
Figure 3 displays the average error rates for specific and global feedback overtime in the frequent feedback group. Participants with the two types of feedback
showed similar error rates during all experimental sessions. However, in theinfrequent feedback group, participants given specific feedback consistently
showed a lower error rate than those given global feedback (see Figure 4).
Discussion
This study was designed to examine the possible interaction effects of feedback specificity and frequency on the quality of performance. The results of a
two-way ANOVA indicated that frequent feedback was more effective for
improving performance than infrequent feedback. This result correspondswith previous studies which found frequent feedback improves work performance (Mason & Redmon, 1992; Pampino et al., 2003; So et al., 2013).
For feedback specificity, specific feedback was more effective than global
feedback, as also corresponds with the general assumption that specificfeedback is more effective. Specific feedback provides a variety of information
about what the performer is doing well and what needs improvement. Thus,
specific feedback may have been much more helpful than global feedback in

Figure 2. Means and standard deviations of error rates across feedback frequency and specificity.

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18

Specific

Mean of Error Rate(%)

16

Global

14
12
10
8
6
4
2
0
1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Sessions

Figure 3. Average error rate by feedback specificity across sessions in the frequent-feedback
groups.
18

Specific

Mean of Error Rate(%)

16

Global

14
12
10
8
6
4
2
0
1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Sessions

Figure 4. Average error rate by feedback specificity across sessions in the infrequent-feedback
groups.

identifying the behaviors the performer needs to change. Due to the unfamiliar nature of the experimental tasks for the participants, specific feedback
would have been more effective than global feedback in mastering this task.
Above all, the interaction effect is noteworthy. The frequent feedback
group showed no difference in the quality of performance for either type of
feedback specificity, but the infrequent feedback group performed better
when provided with specific feedback. In the infrequent feedback group,participants who received specific feedback performed consistently better
during all 24 sessions than did participants who received global feedback.
These findings, along with the previous findings from Williams and Geller

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(2000) and Lee et al. (2014), clearly indicate that specific feedback is notalways more effective than global feedback. That is, specific feedback may beunnecessary when feedback can be delivered frequently.
Taken together, these results have important practical implications, particularly from a performance management perspective. If managers find it
difficult to monitor employee performance frequently or to automate observations, they should observe specific behaviors when possible and provide
specific performance feedback. If specificity proves difficult, then frequent
feedback may achieve the same effect. In short, it is critical that feedback be
specific or frequent, but one should not expect additional performance gains
from embedding both elements into feedback.
One particularly interesting finding from this study is that the error ratetended to increase slightly in the later sessions for the frequent feedback
groups, regardless of feedback specificity. This could suggest that frequent
feedback cannot be expected to indefinitely maintain performance and mayneed to be combined with other components over time (e.g., evaluative feedback, praise, tangible reinforcers, etc.). Alternatively, it may also suggest that
there could be a benefit to eventually changing from frequent to infrequent
feedback as employee proficiency improves, much as there is often a benefit toswitching from continuous to intermittent reinforcement with new learners.
The results of this study suggest several opportunities for future research. First,
different specificities of feedback should be examined with well-learned behaviors
as opposed to relatively new behaviors. Alavosius and Sulzer-Azaroff (1990),
Chhokar and Wallin (1984), and Leivo (2001) all found that different feedback
frequencies maintained behaviors equally well once the behaviors had beenacquired and mastered. Although these results are consistent with statementsthat frequent feedback is less important for maintenance than for the acquisitionof behaviors (e.g., Alavosius & Sulzer-Azaroff; Fairbank & Prue, 1982), it is notknown whether results would differ if feedback with different specificities were
provided for well-learned behaviors.
Similarly, feedback frequency or specificity may interact with high and low
performance levels. For example, Moon, Lee, Lee, and Oah (2017) found thatthe interaction effect between feedback content and performance level
affected performance. Their results indicated that social-comparison feedback was more effective than objective feedback for the high performers but
was less effective for the low performers. High performers already know therules and behaviors that are necessary for their tasks, so it is less likely that
their performance will change because of the feedback frequency or specificity. However, specific and frequent feedback can help improve performancefor low performers who are not familiar with the rules or with what behaviors are needed for performing a task.
Second, task difficulty may also interact with feedback specificity. For
difficult and complex tasks, specific feedback can be effective in improving

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performance, but with easy tasks, global feedback will be sufficient toimprove performance. Finally, in this study, feedback on incorrect responses(error rate) was provided. Daniels and Bailey (2014) argued that feedback
should be based on correct responses rather than incorrect responses.
Sigurdsson and Ring (2013) evaluated the preferences of undergraduate
students for graphic feedback on percentage of incorrect performance oron percentage of correct performance. Their results indicated that, although
the type of feedback students received for the first four quizzes did not affectsubsequent quiz performance, participants preferred feedback on correct
performance rather than on incorrect response. However, in the OBM
literature, feedback delivered on incorrect responses (e.g., Bateman &Ludwig, 2003; Berglund & Ludwig, 2009; Sasson, Alvero, & Austin, 2006)
has been found to be effective for improving performance. Therefore, more
research is needed on the relative effects of correct- and incorrect-response
feedback on performance and preferences.
Although these results demonstrate the effectiveness of feedback frequency, specificity, and the interaction between these two characteristics offeedback on work performance, there were limitations concerning the implementation of this study. One limitation was defining a session as completing
25 items rather than as a fixed amount of time in order to make it similar tothe performance in an actual logistics center. Average duration time persession was 5.71 min. (SD = .50), and there was no difference between thefour experimental groups (F(3, 76) = .276, p = .843). However, there was adifference in the average duration of sessions for each individual (Range:
4.88– 7.08) that would likely generate a difference in productivity in theactual field. Another limitation is that the task was a simulation of a work
environment and therefore may not fully capture the actual implementationof tasks in a modern distribution center or the subtleties associated with real
work performance.
Despite such limitations, the current study provides evidence regarding theimpact feedback has upon performance when considering characteristics such as
the frequency and specificity with which the feedback is delivered. Although
feedback in general has been studied often, the finer details of feedback implementation are less well understood but may be just as important. To establish amore in-depth understanding of the precise effects of feedback on performance,
it is recommended that future studies be conducted with greater frequency andwith more specific components under investigation.
Disclosure statement
No potential conflict of interest was reported by the authors.

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