JOURNAL OF TEACHING IN PHYSICAL EDUCATION, 1988.7.289.301
Descriptive Analysis of Coach Augmented Feedback
Given to Nigh School Varsity Female Volleyball Players
Regina Marldaad
Coastal Carolina College
Thomas J. Martinek
University of North Carolina at Greensboro
This study examined the nature and amount of feedback that more successful
and less successful high school varsity volleyball coaches gave to their starting and nonstarting volleyball players. Two of the four coaches studied were
considered more successful and two were considered less successful, based
on previous regular season win-loss percentages. Players of all the coaches
(N=41) were also used as subjects and identified as having either a starting
or nonstarting role on the team. All subjects were observed on three occasions for 30 minutes per observation during regular season practice. The Cole
Descriptive Analysis System (Cole-DAS) was used to observe coach augmented feedback as it was given to individual players in response to skilled
performance. A 2 X 2 multivariate analysis of variance was used to describe
the effects of (a) success of the coach, (b) role of the player, and (c) both
success of the coach and role of the player on the dependent variables of wach
augmented feedback. Results indicated that successful waches varied considerably from less successful coaches in the types of feedback given to their
players. Starting players were also found to receive significantly more audio, audiovisual, and immediate terminal feedback than nonstarting players.
Since the 1%0s, considerable research has been conducted on teaching and
coaching. An increase in the development and use of strategies for observing
teachers has brought improvement of teacher effectiveness (Siedentop, 1983).
Coaching an athletic team in a high school environment is, for the most part,
a teaching experience. Consequently, many of the observation systems developed
for teaching effectiveness could be used to learn how to develop and improve
coaching techniques and, subsequently, increase athletes' motor skill learning.
Request reprints from Thomas J. Martinek, School of Health, Physical Education,
Recreation and Dance, University of North Carolina at Greensboro, Greensboro, NC
27412-5001.
290
MARKLAND and MARTINEK
Some observational systems have been designed to describe specific aspects
of teacher-student or coach-athlete interactions and the types of feedback received
by the learner of a skiU. Feedback has been determined by motor learning
specialists to be one of the most important variables in learning a skill (Adams,
1971; Schmidt, 1982; Whiting, 1975). Coaches are, by the nature of their roles,
responsible for much of the extrinsic augmented feedback an athlete receives during
practice of an athletic activity. According to research, the kind, amount, and timing
of augmented feedback may have differentiating effects on the acquisition and
learning of motor skills (Kirschenbaum & Smith, 1983; Schmidt, 1982; Vallerand,
1983).
For example, Kirschenbaum and Smith (1983) studied the effects of four
sequences of augmented feedback given during the learning of a new task. Subjects who received positive feedback followed by negative feedback or negative
feedback followed by positive feedback outperformed subjects who received continuous positive feedback or continuous negative feedback. In a similar study,
Ramella (1983) looked at augmented feedback in relationship to the length of
post-augmented feedback intervals using a temporal-spatial task. He found that
a longer (6 sec) postaugmented feedback interval reduced error in performance
to a greater extent than a shorter (3 sec) postaugmented feedback interval.
Another factor influencing the type and amount of feedback given by coaches
is the skill level of the performer. Recent research in physical education indicates that "specific teaching behaviors directed toward high and low achievers
are related to the teachers' expectations for various students" (Martinek & Karper,
1983, 1986).
Rejeski, Darracott, and Hutslar (1979) extended the notion that the skill
level of players mediates coach feedback strategies in a sport setting. In their
study, they coded coaching behaviors directed at high- and low-skilled athletes
in a youth sports basketball league. Consistent with findings reported in the classroom, the high-ability children were reinforced more than low-ability children.
It was also found that the coaches gave more general technical information to
low-ability than to the high-ability children. Results of this study suggest that
coaches may, by their actions, sustain high and low levels of performance of their
players. Cratty (1983) argues that while feedback is a very important variable
in the learning of motor skills, high school coaches, for the most part, seldom
examine the feedback they use during practice. It would appear, then, that future
studies should begin to look at the type and amount of feedback given to the players
so that coaches can use the information to become more successful teachers of
their sport. Therefore, the purpose of this study was to examine the nature and
amount of augmented feedback that more successful and less successful high school
varsity volleyball coaches gave to their starting and nonstarting female volleyball players during regular season practice.
Procedure
Sample and Population
Four coaches used as subjects of the study were systematically chosen
from a pool of all coaches (N= 12) in the Big and Little Mac Athletic Conferences, which consist of AAA schools in western North Carolina. In order to be
29 1
COACH AUGMENTED FEEDBACK
selected in the sample, each coach must have coached at his or her same school
during the previous volleyball season. Of the 12 coaches, four were chosen as
subjects on the basis of their win-loss record during the regular season of the
previous year. The number of regular season games played by each coach was
14 to 16. The coaches were then ranked according to their percentage of wins
for that particular season. Of the four coaches who were chosen as subjects, two
had the highest percentage of wins, one had the lowest percentage of wins and
one had the third lowest percentage of wins. The coach with the second lowest
percentage of wins during the previous year was not chosen because he was no
longer coaching varsity volleyball at his school. All coaches were white females
with ages ranging from 31 to 38 years. Coaching experience in high school varsity volleyball ranged from 1 to 8 years. However, the coach who had only 1
year of experience in high school coaching had been a collegiate player and helped
coach a USVBA team for several seasons.
Players also served as subjects since they were members of the team of one of
the four coaches chosen as subjects. Table 1 describes the distribution of the
coaches, the number of their starters and nonstarters, and win-loss percentages.
Table 1
Distribution of Sample and Win-Loss Percentages of Coaches
Coach
identification
No. of
players
Starters1
nonstarters
010 of
Wins
O
h of
Losses
Procedures for Data Collection
The regular season volleyball schedule for the Big and Little Mac Conferences was approximately 10 weeks in length. During this time, teams normally
played games on Tuesday and Thursday and practiced Monday, Wednesday, and
Friday. On several occasions teams also played on Wednesday, which meant they
would have only two practices for that week. Practices for all four coaches lasted
approximately 2 hours, although Friday practices occasionally were shorter due
to conflicts with football games.
It was decided that Monday and Wednesday were the best days to observe
because some coaches had short practices on Friday and occasionally omitted
Friday practice at their own discretion. This left approximately 20 practice days
per coach to make the observations. Each coach was observed three times during
the season. This was done so that practices were observed at the beginning, rniddle, and end of the regular season. Research has shown that coaching behavior
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MARKLAND and MARTINEK
during preseason may be different from early and late season coaching (Lacy
& Darst, 1985). After obtaining game and practice schedules from each coach,
an observation schedule was set up for the observers. However, this schedule
was subject to limitations of the length of the season and the game schedules.
Coaches did not necessarily get an even distribution between observations. No
coach was observed twice in the same week.
At the beginning of each practice session, players were asked to put identification numbers on over their practice clothing. A list of each team member's
name and identification number was kept by the observers to assure that each
player received the same identification number for each observation. Once identification numbers were put on each player, no other disturbances were made
by the observers. Coaches were instructed to keep practice sessions normal and
as scheduled.
Observers began recording 10 minutes into the practice session. They recorded for 10 minutes and rested for 5 minutes. This recording procedure was
immediately repeated two more times, making the total recording time for each
observation 30 minutes.
During coding, observers recorded the player to whom the feedback was
directed, along with the feedback category, by placing tally marks in appropriate
rows (players) and columns (categories) on the coding sheet. At the conclusion
of 12 observations, tally totals for each observation period were computed as
rate scores (behaviors/practices)by dividing the total number of tallies for each
skill behavior by the number of observations per coach.
Prior to the first observation, each coach and her team were informed about
the nature of the study and their role in the data collection. They were told that
the purpose of the study was to investigate the general feedback given by coaches
to their players during practice. They were not told that the feedback patterns
would be compared to the other variables in the study. However, after completion of the study full disclosure of the study's purpose was given and, at that
time, the subjects were given the opportunity to withdraw their data. None of
the subjects chose to do so. It was felt that this debriefing procedure was necessary since prior information concerning the differences in coaches' status and
role of players would alter normal practice behavior.
Coaches were then asked to identify the roles of their players (starters, nonstarters) during the regular season. Starters were identified as any player who
consistently played at the beginning of the game or was a consistent strategical
substitute during the season. A nonstarter was any player who did not play consistently at the beginning of the game or was not a consistent strategical substitute during the season. Each coach referred to her regular season scorebook to
identify player role.
Description of the Cole Descriptive Analysis System
The Cole Descriptive Analysis System (Cole-DAS) (Cole, 1979) was used
to collect augmented feedback from the coaches under study. Cole-DAS is an
adaptation of Fishman's Augmented Feedback Tool (1975) which was originally
designed to record augmented feedback behaviors in physical education classes.
Cole-DAS consists of five categories of feedback: mode, time of delivery, type
of message, general referent, and specific referent. The categories are subdivided into 19 different feedback items. Figure 1 provides a summary of the Cole-
COACH AUGMENTED FEEDBACK
293
COLE-DAS
Mode: the sensory form through which information is conveyed.
Auditory: feedback given orally.
Auditory-Visual: feedback given orally and through teacher demonstration.
Auditory-Tactile: feedback given orally and by manual assistance.
Tactile: feedback given through manual assistancelmanipulation.
Visual: feedback given through teacher demonstrationandlor facial expressions,
head movements, hand gestures, body posturellanguage.
Time of Delivery: the placement of feedback in relation to the attempted skill.
Concurrent: feedback provided during the performance of a motor skill.
Immediate Terminal: feedback provided after the completed motor skill attempt
and before participation in one or more intervening motor skill attempts.
DelayedTerminal: feedback provided about the motor skill responsebut given after
the student has participated in one or more motor skill attempts.
Type of Message: the role of feedback. . . to reinforce, to motivate, andlor to regulate motor performancellearning.
Approval: any general verbal andlor nonverbal response of a positive nature to a
motor skill attempt, or to its subsequent result.
Disapproval: any general verbal or nonverbal reaction of a negative nature to a
motor skill attempt, or its subsequent result.
Supportive Information: specific information about those aspects of the motor skill
that were performed reasonably well, or executed correctly; acknowledgment
of the strengths of the performance, or its results.
Corrective Information: prescriptive or modifying information given in reference
to some error in the performance of a motor skill, or its results.
Convergent Questioning: asking for student interpretationof the completed motor
skill attempt, one of its subroutines, or its results. Such questions require the
student to synthesize sensory input andlor past experiences. Questions may be
positive, negative, or neutral.
General Referent: the framework within which the feedback is given.
"Whole" Movement: the performance of combinedlmultiple subroutines of the
motor skill.
Part of Movement: the performance of a specific subroutine, or the utilization of a
particular anatomical part.
Results of Movement: the outcome of the motor skill attempt. . . the end product.
Specific Referent: the mechanical elements involved in the performance of the
motor skill or displayed in its results.
Force: feedback about the strength or power expended in the motor performance
or displayed in its results.
Space: feedback about the direction, level (low, medium, high plan of movement),
relationship (players position to another player, or to an object), or size (large
vs. small) of the movement in the performance.
Rate: feedback about the time element of performance.
Figure 1 - The Cole descriptive analysis system for recording teacher augmented
feedback
294
MARKLAND and MARTINEK
DAS categories and a brief description of each. The system is limited to the observation of coach augmented feedback which occurs either during or after a
player's motor skill response. An entry tally is made for each feedback response.
Sequential or intermittent feedback responses are not considered.
As previously indicated, coding was facilitated by the use of a coding form
in which coders were instructed to place tallies under the appropriate item beside
the identification number of the player to whom the feedback behavior was directed. Ground rules were kept as simple as possible in an effort to make recording
both accurate and objective.
Training of Coders
Two observers were trained to record coach augmented feedback using
Cole-DAS. Both observers were high school students ranked within the top 5 %
of their class. One of the observers was a senior and the other a sophomore. Training included approximately 20 hours of instruction in which categories, items,
and ground rules were defined and clarified. Observers practiced coding feedback during two live volleyball practices and by watching four videotapes of volleyball practice. After each coding session, discrepancies and problems in recording
were discussed and clarified.
One of the tapes was observed and coded twice by each observer, one week
apart, in order to establish intracoder reliability. Reliability was established by
determining a percentage of agreement, based on the sum of the agreements and
disagreements for each of the feedback categories. Intracoder reliability for Coder
A and Coder B was .84 and .80, respectively. To complete the training, both
overall and categorical intercoder reliability were determined. The two observers observed one practice session, and each observer's codings were compared.
Intercoder reliability (percentage of agreement) at the end of the training sessions ranged within each category from .75 to .84. The percentage of agreement
for each of the major categories was Mode, .84; Time of Delivery, 31; Type
of Message, .78; General Referent, .79; and Specific Referent, .75. Overall
percentage of agreement was 34.
Analysis and Results
Once all 12 observations were completed (three per coach), data were prepared for analysis. In order to describe the amount and type of augmented feedback used by all the coaches, frequency percentages for each category and subcategory were conducted. Comparisons of the feedback subcategories of each
coach were also conducted. A 2 x 2 multivariate analysis of variance (MANOVA) was then used to determine significant differences between the two coaching groups and the starters and nonstarters on the feedback variables. In addition,
an interaction effect between the two independent variables was determined.
Feedback Patterns of Coaches
The feedback data collected on the four coaches showed that audio feedback
(67.26%) was the most common way in which coaches gave feedback to a player.
The time of delivery of the feedback given by coaches was immediate (95.49%)
with the type of feedback being corrective in nature (66.73%). When feedback
295
COACH AUGMENTED FEEDBACK
was given, it was generally in reference to the whole motor skill response
(78.88%). Table 2 provides a summary of the overall frequencies and percentages of the feedback behaviors collected.
The number of coded feedback in the "specific referent" category was
negligible and, therefore, was excluded from the data analysis.
Feedback Received of Players
of Successful and Less Successfil Coaches
Four 2 x 2 MANOVAs were used to analyze the feedback given to starting
and nonstarting volleyball players from successful and less successful coaches.
Each MANOVA was conducted on the subcategories subsumed under the four
general categories of Cole-DAS: Mode, Time of Delivery, Type of Message,
and General Referent.
Mode of Feedback. A significantmultivariate F was found between players
of more and less successful coaches for the Mode category, F(l, 39) = 6.89,
p < .001. Univariate analysis indicated players of more successfid coaches received
significantly more audio feedback than players of less successful coaches, F(l,
39) = 37.06, p < -001. The mean for more successful coaches was 5.73 (SD
= 2.40), and the mean for less successful coaches was 1.98 (SD = 1.10).
Table 2
Summary of Cole-DAS Frequencies and Percentages
Categories Isubcategories
Mode
Audio
Audio-visual
Audio-tactile
Visual
Tactile
Time of delivery
Concurrent
Immediate terminal
Delayed terminal
Type of message
Approval
Disapproval
Supportive
Corrective
Convergent questioning
General referent
Whole movement
Part movement
Total
Frequencies
010
2%
MARKLAND and MARTINEK
A significant multivariate F was also found between starting and nonstarting
players, F(1, 39) = 2.63, p < .05. Univariate analyses indicated that starting
players received significantly more auditory feedback than nonstarting players,
F(l,39) = 4.23, p < .05. The mean for starting players was 4.10 (SD = 2.62),
and the mean for nonstarting players was 2.90 (SD = 2.49). It was also indicated
that starting players received significantly more audiovisual feedback than nonstarting players, F(1, 39) = 10.90, p < .01. The mean for starting players was
1.99 (SD = 1.62), and the mean for nonstarting players was 0.54 (SD = 0.63).
No significant interaction effect was found between the independent variables
and mode of feedback, F ( l , 39) = .52, p > .05. Table 3 provides a summary
of the frequencies and percentages for mode of feedback.
Time of Delivery. A significant multivariate F was also found for players
of more and less successful coaches for the Time of Delivery category, F ( l , 39)
= 22.60, p < .001. Univariate analysis indicated that players of more successful
coaches received significantly more immediate terminal feedback than players
of less successful coaches, F ( l , 39) = 49.26, p < .001. The mean for more
successful coaches was 7.65 (SD = 3.14), and the mean for less successful coaches
was 2.75 (SD = 1.73).
A significant multivariate F was also found, F ( l , 39) = 8.79, p < .001.
Univariate analysis indicated that starting players received significantly more immediate terminal feedback than nonstarting players, F(1,39) = 24.10, p < .001.
The mean for starting players was 5.92 (SD = 3.55), and the mean for nonstarting players was 2.79 (SD = 2.50). No significant interaction effects were detected, F ( l , 39) = 2.35, p > .05. Table 4 provides a summary of the frequencies
and percentages for Time of Delivery.
Type of Message. In the Type of Message category, a significant multivariate F was found between players of more and less successful coaches, F(l,
39) = 7.78, p < .001. Univariate analyses indicated that players of more successful
coaches received significantly more approval than players of less successful
coaches, F(l, 39) = 6.79, p < .01. The mean for more successful coaches was
1.05 (SD = 1.06), and the mean for less successful coaches was 0.32 (SD =
0.40). It was also indicated that players of more successful coaches received significantly more corrective feedback than players of less successful coaches, F ( l ,
39) = 33.56, p < .001. The mean for more successful coaches was 5.39 (SD
= 2.61), and the mean for less successful coaches was 1.57 (SD = 1.48).
There were no significant differences found between starters and nonstarters for the Type of Message category F ( l , 39) = 2.44, p > .05. In addition,
no significant interaction effect was found, F ( l , 39) = .75, p > .05. Table 5
provides a summary of the frequencies and percentages for the Type of Message
category.
General Referent. In the General Referent category, a significant multivariate F was found between players of more and less successful coaches, F ( l ,
39) = 18.29, p < .001. Univariate analyses indicated that players of more successful coaches received significantly more whole movement feedback than players
of less successful coaches, F ( l , 39) = 31.95, p < .001. The mean for more
successful coaches was 4.93 (SD = 1.89), and the mean for less successful coaches
was 2.00 (SD = 1.52). It was also indicated that players of more successful coaches
received significantly more part movement feedback than players of less successful
COACH AUGMENTED FEEDBACK
297
Table 3
Summary of Frequencies and Percentages for the Mode Category*
Mode
Audio-visual
Audio-tactile
Visual
Tactile
More
successful (Oo)
Less
successful (010)
Starter (010)
Non
starter (010)
327 (47.9)
136 (19.9)
8 (1.2)
0 (0)
131 (19.2)
64 (9.4)
4
1 (.I)
346 (50.7)
167 (24.5)
9 (1.3)
1 (.I)
112 (16.4)
33 (4.8)
3 (.4)
0 (0)
Table 4
Summary of Frequenciesand Percentagesfor the Time of Delivery Category*
Time of
delivery
Concurrent
Immediate
terminal
Delayed
terminal
More
successful (010)
Less
successful (010)
Starter (010)
Non
starter (010)
9 (1.4)
13 (2.1)
16 (2.6)
6 (1.0)
409 (65.9)
184 (29.6)
497 (80.0)
96 (15.5)
1
(.2)
5
( 4
6 (1.0)
0 (0)
Table 5
Summary of Frequencies and Percentages
for the Type of Message Category*
Type of
message
Approval
Disapproval
Supportive
Corrective
Convergent questioning
'Total = 605
More
successful (oh)
Less
successful (010)
Starter (Oh)
Non
starter (010)
60 (9.9)
33 (5.5)
20 (3.3)
303 (50.1)
7 (1.2)
22 (3.6)
35 (5.8)
18 (3.0)
101 (16.7)
6 (1.0)
59 (9.8)
56 (9.3)
29 (4.8)
338 (55.9)
11 (1.8)
23 (3.8)
12 (2.0)
9 (1.5)
66 (10.9)
2 (.3)
MARKLAND and MARTINEK
298
coaches, F(l, 39) = 22.60, p < .001. The mean for more successful coaches
was 1.54 (SD = 0.94), and the mean for less successful coaches was 0.35 (SD
= 0.49).
A significant multivariate F was also found for starting and nonstarting
players, F(l, 39) = 7.78, p < .01. Univariate analyses indicated that starting
players received significantly more whole movement feedback than nonstarting
players, F(l, 39) = 15.48, p < .001. The mean for starting players was 3.96
(SD = 2.14), and the mean for nonstarting players was 2.05 (SD = 1.91). It
also indicated that starting players received significantly more part movement
feedback than nonstarting players, F(l, 39) = 6.17, p < .05. The mean for the
starting players was 1.08 (SD = 1.00), and the mean for the nonstarting players
was 0.51 (SD = 0.69). There was no significant interaction effect indicated, F(l,
39) = .75, p > .05. Table 6 provides a summary of the frequencies and percentages for the General Referent category.
Table 6
Summary of Frequencies and Percentages for the General Referent Category*
General
referent
Whole
Part movement
More
successful (%)
Less
successful (010)
Starter (010)
Non
starter (010)
281 (53.6)
88 (16.8)
132 (25.2)
23 (4.4)
333 (63.5)
gl(17.4)
80 (15.3)
20 (3.8)
'Total = 524
Discussion
Although this study describes the behavior of coaches in giving augmented
feedback to female high school volleyball players, the feedback behavior can only
be generalized to the population from which the sample was drawn. Neither the
size of the sample nor the scope of the study will allow for the characteristics
of augmented feedback to be suggested as those feedback behaviors best suited
for all volleyball coaches. However, the evidence from the data may contribute
to the knowledge of augmented feedback patterns which are used by some high
school volleyball coaches.
A comparison of the findings of the present study with those of Cole's
(1979), who observed instruction of the golf swing, reveals some similarities in
feedback, although the two studies looked at different types of skills (open vs.
closed). Both studies revealed four of the same subcategories as most frequently
used-auditory, immediate terminal, corrective, and whole movement. These subcategories are also supported in motor learning literature as appropriate types
of feedback for most skill performance (Adams, 1971;Klienrnan, 1983; Schmidt,
1982; Singer, 1980; Whiting, 1975).
COACH AUGMENTED FEEDBACK
299
However, there is some discrepancy among researchers as to whether it
is appropriate to use whole or part movement reference in teaching various types
of skills. Magill (1980) contended that use of whole and part movement was dependent on skill complexity and organization. Skills of high complexity and low
organization should be taught in part movement, and skills of low complexity
and high organization should be taught in whole movement. The findings of this
study are consistent with the use of whole movement, which would indicate that
the skills involved in playing volleyball may be considered to be of low complexity while highly organized. According to Singer's (1980) taxonomy, the skills
most used in volleyball are Type 11 and Type IV skills. Type II skills are those
skills in which the performer is stationary but must react to a moving object.
Type IV skills are those skills in which the performer is in motion and must also
react to a moving object. Further research in this area could be beneficial to
coaches in determining which methods are more appropriate for particular skills.
With respect to the amount and type of feedback given to individual players
by more and less successful coaches, significant differences were found in five
subcategories. Players of more successful coaches received significantly more
feedback than players of less successful coaches in subcategories of audio, immediate terminal, corrective, whole movement, and part movement. Studies which
have looked at coaching behavior in relation to success are inconclusive. Some
findings support the use of corrective feedback by successful coaches (Tharpe
& Gallimore, 1976), whereas others support the frequent use of praise (Lacy &
Darst, 1985).
Cratty (1983) stated that there is no stereotypic coaching personality or
set of behaviors which leads to success in coaching, but rather that effective coaching behavior was flexible and dependent on many aspects of the coaching environment. With this in mind, the question is raised as to whether differences
in behavior evident in this study are due to the success of the coach or are due
to other factors. The limitations of this study do not allow the researcher to determine the reasons for the differences which were found. However, some possible reasons are suggested. One reason is that the differences in augmented
feedback given by more and less successful coaches could have been a direct result
of success in the previous season. Coaches who were previously successful may
perceive their athletes as more capable and, therefore, feel they are able to handle more instruction and feedback. If research in feedback behavior is to be worthwhile, it would seem that knowledgeable coaches would be better able to use
feedback in a constructive and strategic way than the coach who has no knowledge of how feedback can be used to enhance performance.
Significant differences were also found in the amount and type of feedback
given to starting and nonstarting players. Starting players received significantly
more feedback than nonstarting players in the subcategories audio, audiovisual,
immediate terminal, whole movement, and part movement. These results support the literature which indicates that there is a need to vary feedback behavior
based on the skill level of the athlete (Fitts, 1964; Rogers, 1974; Singer, Cauraugh,
Lucariello, & Brown, 1985). However, it must be assumed that the starting players
in this particular study were more highly skilled than nonstarting players, since
no measures were taken to determine the skill level of each athlete.
Some of the literature indicated that audio and audiovisual feedback were
important to the beginner of a skill but became less important as the skill was
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MARKLAND and MARTINEK
mastered (Barbarich, 1980; Fleishman, 1966; Klienman, 1983). However, Knapp
(1972) felt that the responsibility of the coach of a competitive team sport was
to help all performers, regardless of skill level, in decision-making skills and
strategies needed for a changing situational environment.
The findings of this study also seem to suggest that the skilled athlete uses
immediate terminal, whole movement, or part movement feedback better than
the less skilled athlete. However, some studies seem to note that the skilled athlete is probably able to deal with more information, especially audio feedback,
than the unskilled athlete, because the skilled athlete is able to perform many
skills automatically (Schmidt, 1982). The coaches in this study may have understood this and, therefore, gave more information to their more skilled players
(starters).
From a social psychological perspective, Singer (1980) feels that teachercoaches often spend more time with the skilled athlete, because they want to be
part of that athlete's success. The skilled athlete is probably seen as a major contributor to the success of the coach, as well as the team; therefore, the coach
has a need to keep that athlete interested in performing well. By giving the skilled
athlete more attention, the coach may perpetuate increased motivation and performance (Fiedler, 1967). If coaches perceive the athlete to be less skilled, their
behavior toward the athlete may be different due to the perception (Horn, 1984;
Martinek & Johnson, 1979). This athlete is often seen as not having as much
impact on team or coach success, and may not receive as much attention (Fiedler, 1967).
In final discussion, it should be noted that while there are some general
patterns in feedback behavior, as indicated by this study, and some general rules
to be followed in effectively using augmented feedback, specific needs of the individual athletes in changing situations should affect the amount and type of feedback necessary for reaching optimal performance. Coaches need to be aware of
the differences in the augmented feedback they give to more and less skilled athletes and, where possible, study behaviors of the coaches who have been
successful.
References
Adarns, J.A. (1971). A closed-looped theory of motor learning. Journal of Motor Behavior, 3, 111-150.
Barbarich, J.E. (1980). A study of visualpractice on learning the volleyballforeannpass.
Unpublished doctoral dissertation, Springfield College, Springfield, MA.
Cole, J.L. (1979). A descriptiveanalysis of teacher augmentedfeedback given to university
students in beginning golf class. Unpublished doctoral dissertation, University of
North Carolina at Greensboro.
Cratty, B.J. (1983). Psychology in contemporary sport. Englewood Cliffs, NJ: PrenticeHall.
Fiedler, J.E. (1967). A theory of leadership effectiveness. New York: McGraw-Hill.
Fishman, S.E. (1975). A procedure for recording augmented feedback in physical education
classes (Doctoral dissertation, Teachers College, Columbia University, NY, 1974).
LXssertution Abstracts International, 35, 5986A-5987A.
Fitts, P.M. (1964). Perceptual-motor skill learning. In A.W. Melton (Ed.), Categoriesof
human learning. New York: Academic Press.
COACH AUGMENTED FEEDBACK
301
Fleishman, E.A. (1966). Human abilities and the acquisition of skill. In E.A. Bilodeau
(Ed.), Acquisition of skill. New York: Academic Press.
Horn, T.S. (1984). Expectancy effects in the interscholastic athletic setting: Methodological
considerations. Journal of Sport Psychology, 6 , 60-75.
Keele, S.W., Neill, W.T., & DeLemos, S.M. (1980). Individual differences in attentional
flexibility (Tech. Rep. No. 1). University of Oregon, Center for Cognitive and Perceptual Research.
Kirschenbaum, D.S., & Smith, R.J. (1983). A preliminary study of sequencing effects in
simulated coach feedback. Journal of Sport Psychology, 5 , 332-342.
Klienman, M. (1983). The acquisition of motor skill. Princeton, NJ: Princeton Book
Company Publisher.
Knapp, B. (1972). Skill in sports. London: Routledge & Kegan Paul.
Lacy, A.C., & Darst, P.W. (1985). Systematic observation of winning high school football coaches. Journal of Teaching in Physical Education, 4 , 256-270.
Magill, R.A. (1980). Motor learning: Concepts andapplications. Dubuque, LA: Wm. C.
Brown.
Martinek, T., &Johnson, S. (1979). Teacher expectations: Effects of dyadic interactions
and self-concept in elementary age children. Research Quarterly, 50, 60-70.
Martinek, T., & Karper, W. (1983). A causal model for determining expectancy effects
in physical education. Quest, 35, 155-168.
Martinek, T., & Karper, W. (1986). Motor ability and instructional contexts: Effects on
teacher expectations and dyadic interactions in elementary physical education classes.
Journal of Classroom Interaction, 21, 16-25.
Ramella, R.J. (1983). Processing knowledge of results and a multidimensional task.
Perceptual and Motor Skills, 57, 43-48.
Rejeski, W., Darracott, C., & Hutslar, S. (1979). Pygmalion in youth sport: A field
study. Journal of Sport Psychology, 1, 311-319.
Rogers, C.A. (1974). Feedback precision and post-feedback interval duration. Journal of
Experimental Psychology, 102, 604-608.
Schmidt, R.A. (1982). Motor control and learning: A behavioral emphasis. Champaign,
IL: Human Kinetics.
Siedentop, D. (1983). Developing teaching skills in physical education (2nd 4 . ) . Palo
Alto, CA: Mayfield.
Singer, R.N. (1980). Motor learning and human pelformance: An application to motor
skills and movement behaviors (3rd ed.). New York: Macrnillan.
Singer, R.N., Cauraugh, J.H., Lucariello, G., & Brown, H.J. (1985). Achievement in
related psychomotor tasks as influenced by learning strategies. Perceptual and Motor Skills, 60, 843-846.
Tharpe, R., & Gallimore, R. (1976). What a coach can teach a teacher. Psychology Today,
25, 75-78.
Vallerand, R.J. (1983). The effect of differential amounts of positive feedback on the
intrinsic motivation of male hockey players. Journal of Sport Psychology, 5, 100-107.
Whiting, H.T. A. (1975). Concepts of Skill Learning. London: Lepus.