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LIBRARY
Michigan State
University
a ,

 

This is to certify that the

dissertation entitled

EFFECTS OF VIDEOTAPED MODELING AND
VIDEOTAPED FEEDBACK ON PERFORMANCE IN
TRAINING: AN EXAMINATION OF PERSONALITY
BY TREATMENT INTERACTIONS"

presented by

Katherine Ann Karl

has been accepted towards fulﬁllment
of the requirements for

 

 

Ph . D . degree in Management

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// Major professor
\.

 

Date March 14, 1991

 

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EFFECTS OF VIDEOTAPED MODELING AND VIDEOTAPED FEEDBACK
ON PERFORMANCE IN TRAINING: AN EXAMINATION
OF PERSONALITY BY TREATMENT INTERACTIONS

By

Katherine Ann Karl

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Management

1991

 

ABSTRACT

EFFECTS OF VIDEOTAPED MODELING AND VIDEOTAPED FEEDBACK
ON PERFORMANCE IN TRAINING: AN EXAMINATION
OF PERSONALITY BY TREATMENT INTERACTIONS
By

Katherine Ann Karl

One area of research that has shown promise in improving the effectiveness
of training is research on the use of videotape. Two types of videotaped informatiOn
have received special attention in the literature, presentation of a videotaped model,
and videotaped feedback in which the trainee observes himself or herself. Numerous
studies have clearly demonstrated that presenting videotaped models fosters the
learning of new behaviors. Similarly, research on the impact of videotaped feedback
indicates that this technique has tremendous potential to affect human behavior.
One limitation of this research, however, is that it has utilized a fixed treatment
approach. That is, it was assumed that all individuals regardless of their knowledge,
skills, abilities or other attributes (e.g., personality characteristics) would beneﬁt from
the same treatment. To that end, the purpose of the present research was to
examine the separate and combined effects of videotaped modeling and videotaped
feedback on performance in training and to examine possible individual difference

variables that may inﬂuence the effectiveness of these two techniques. In addition,

this research presented and tested a theoretical model of the processes underlying
the effects of videotaped modeling and videotaped feedback. Overall the results of
this research supported the effectiveness of videotaped modeling and the
combination of videotaped modeling and videotaped feedback. The effectiveness of
videotaped feedback was not supported nor were the proposed underlying
relationships. In addition, none of the proposed personality by treatment
interactions were supported. One significant personality by treatment interaction was
found, however, it was opposite to that which was predicted. Videotaped modeling
had a greater impact on the performance of people with external rather than internal
locus of control. Implications of these results for practitioners, recommendations for

future research, and the limitations of this research are discussed.

To Lenny

iv

 

ACKNOWLEDGMENTS

Completion of this dissertation would not have been possible without the
help, guidance, and encouragement of many individuals. First, and most importantly,
I would like to thank my husband Lenny, not only for his patience and
understanding, but for his unabated love and encouragement throughout my entire
education.

Secondly, I would like to thank my dissertation chair, Georgia Chao, for being
patient with me and Staying with me even though I changed my topic several times.
I am also grateful for the many hours She spent in helping me to improve my
writing. I would also like to thank John Hollenbeck and Dan Ilgen, my committee
members, for challenging me to think big and to always do my best work.

Several other individuals must also be acknowledged for their support. I
would like to thank Ram Narassimhan, Chairman of the Management Department
at Michigan State University, for partially funding this research. I would like to
thank Jon Werner, Doug Sego, Darrell Marriott and Jim Weber for starring in my
videotapes. I would like to thank Clare and Geraldine Karl, Damodar Golhar, and
Timothy Bowman for loaning me their videotape cameras. I would like to thank
Tom Carey, Ray Alie, Dan Farrell and Bob Landeros for encouraging their students
to participate in my research. I would like to thank Robert Erickson, Chairman of

the Speech and Pathology Department at Western Michigan University for allowing

me to use the speech labs to conduct my research. Finally, I would like to give
special thanks to Bob Landeros for allowing me to use his laser printer whenever I
wanted, for helping me with Harvard Graphics, Word Perfect 5.0, and SPSS-PC, and

for continuously providing words of support and encouragement.

vi

 

TABLE OF CONTENTS

LIST OF TABLES ..........................................

LIST OF FIGURES ..........................................

INTRODUCTION ............................................

CHAPTER 1: LITERATURE REVIEW

Theoretical Overview ................................... .
Videotaped Modeling: A Social Learning Theory Perspective ..... .
Videotaped Modeling: A Review of the Literature ..............
Videotaped Feedback: An Informational Perspective .............
Videotaped Feedback: A Self-efficacy Perspective ...............

 

 

Videotaped Feedback: A Review of the Literature ............ .

Videotaped Modeling versus Videotaped Feedback: Similarities and

Differences ........................................

Videotaped Modeling and Videotaped Feedback: A Combined

Treatment Analysis .................................. .
An Overview of Aptitude-Treatment Interaction Research .........

Videotaped Modeling: An Examination of Personality by Treatment

Interactions .........................................
Locus of Control ................................. .
Field-dependence ................................. .

Videotaped F eedback: An Examination of Personality by Treatment

Interactions .........................................
Locus of Control ................................. .
Field-dependence ................................. .

An Examination of the Relationship between General Mental

Ability, Training Treatment and Performance in Training ...... .

An Examination of the Relationship between Locus of control,
Field-dependence, General Mental Ability, Post Training Self-

efficacy and Post Training Knowledge ......................
Summary ............................................ .

Vii

37
40

CHAPTER 2: METHOD

Overview ............................................ . 42
Subjects .............................................. 43
Training Treatment Conditions .............................. 45
Measures ............................................. 47
Procedure ............................................ 50

CHAPTER 3: RESULTS

Scale Reliabilities ....................................... 52
Comparison of Treatment Groups and Confederates ............ . 53
Preliminary Analyses ................................... . 54
Hypothesis 1 .......................................... 55
Hypothesis 2 .......................................... 57
Hypothesis 3 .......................................... . 59
Hypothesis 4 .......................................... . 60
Hypothesis 5 .......................................... . 61
Hypothesis 6 .......................................... . 62
Hypothesis 7 .......................................... . 63
Hypotheses 8, 9 and 10 ................................... 64
Process Model .......................................... 65

CHAPTER 4: DISCUSSION

Overview ............................................ . 71
Videotaped Modeling and Videotaped Feedback: Main Effects and
Interaction ......................................... 71
Personality Variables ................................... . 75
Personality by Treatment Interactions ........................ 77
General Mental Ability ("g") .............................. . 81
Process Model ........................................ . 82
Practical Implications ..................................... 84
Limitations ............................................ 86
Future Research ........................................ 88
Conclusions .......................................... . 89
BIBLIOGRAPHY ........................................... . 91
APPENDICES
Appendix A - Learning Points ............................ . 102
Appendix B - Videotaped Modeling Scripts .................... 103

viii

Appendix C - Practice Role Play ............................ 112

Appendix D - Measures ................................. . 113
Demographic Variables .............................. . 113
Locus of Control ................................... . 114
Field-dependence ................................... . 117
Behavioral pre-training role play ........................ . 124
Behavioral post training role play ....................... . 125
Behavioral Measure ................................. . 126
Self-efficacy A ....................................... 127
Self-efficacy B ....................................... 129
Knowledge (A) ..................................... . 130
Knowledge (B) ..................................... . 132
Knowledge (C) ..................................... . 133

Appendix E - Post Hoc Analyses ............................ 134
An examination of the interaction between videotaped feedback

and self-ratings .................................... 134
An examination of the interaction between videotaped feedback,

self-ratings and self-efﬁcacy ........................... 137
An examination of the relationship between self-ratings and the

rater’s ratings ...................................... 139
An examination of a suppressor effect .................... . 140
An examination of the interaction between self-efficacy and

training treatment ................................ . 141
An examination of the interaction between feedback experience

and training treatment .............................. . 144

 

Table 1.
Table 2.

Table 3.

Table 4.

Table 5.

Table 6.

Table 7.

Table 8.

Table 9.

Table 10.

Table 11.

Table 12.

LIST OF TABLES

Summarization of Procedure ......................... .

Means, standard deviations, internal consistency reliabilities

and intercorrelations among all variables ................. .

Regression Results for the Impact of Videotaped Modeling and

Videotaped Feedback on Post Training Role Play Performance . .

Means, Standard Deviations and Post Hoc Comparisons by

Experimental Condition .............................. .

Regression Results for the Impact of Videotaped Modeling and

Locus of Control on Post Training Role Play Performance . . . . .

Regression Results for the Impact of Videotaped Modeling and

Field-dependence on Post Training Role Play Performance . . . . .

Regression Results for the Impact of Videotaped Feedback and

Locus of Control on Post Training Performance ........... .

Regression Results for the impact of Videotaped Feedback and
Field-dependence on Post Training Role Play Performance . . . .

Regression Results for the Impact of Videotaped Modeling and

g on Post Training Role Play Performance ..............

Regression Results for the Impact of Videotaped Feedback and

g on Post Training Role Play Performance .............. .

Regression Results for the Impact of Videotaped Modeling,
Videotaped Feedback and Field—dependence on Post Training
Knowledge .......................................

Regression Results for the Impact of Videotaped Modeling,
Videotaped Feedback and Locus of Control on Post Training
Self-efficacy ..................................... .

54

55

57

58

60

61

.62

.63

64

69

Table 13.

Table 14.
Table 15.
Table 16.

Table 17.

Table 18.

Table 19.
Table 20.
Table 21.

Table 22.

Regression Results for the Impact of Knowledge and Self-

efficacy on Post Training Role Play Performance .......... .

Regression Results for Process Model ................... .

Regression Results for Videotaped Feedback and Self-rating . .

Regression Results for Videotaped Feedback, Self-efficacy
and Self-rating ....................................

Means, Standard Deviations, and Intercorrelations

Between Training Treatment, Self-ratings, and Training
Outcome Variables ................................
Regression Results for the Impact of Videotaped Modeling and
Videotaped Feedback on Post Training Role Play Performance
Controlling for Post Training Knowledge ................
Regression Results for Videotaped Modeling and Self-efficacy .
Regression Results for Videotaped Feedback and Self-efﬁcacy .

Regression Results for Videotaped Modeling and Feedback
Experience ......................................

Regression Results for Videotaped Feedback and Feedback
Experience ......................................

xi

69
70

. 136

. 137

. 140

. 141
. 142

. 143

. 145

. 145

 

LIST OF FIGURES

Figure 1. A process model of the inﬂuence of videotaped modeling on
performance in training ............................... 7

Figure 2. A process model of the inﬂuence of videotaped feedback on
performance in training ............................. . 13

Figure 3. Predicted interaction between videotaped modeling and

videotaped feedback ................................. 19
Figure 4. A diagrammatic representation of a disordinal interaction . . . . . 21
Figure 5. A diagrammatic representation of an ordinal interaction ..... . 21

Figure 6. Predicted interaction between locus of control and videotaped

modeling ........................................ . 27
Figure 7. Predicted interaction between field-dependence and

videotaped modeling ............................... . 31
Figure 8. Predicted interaction between locus of control and videotaped

feedback ......................................... 33
Figure 9. Predicted interaction between fielddependence and

videotaped feedback ................................. 34
Figure 10. Predicted interaction between "g" and videotaped modeling . . . . 36
Figure 11. Predicted interaction between "g" and videotaped feedback . . . 37

Figure 12. A process model of the relationship between videotaped
modeling, videotaped feedback, locus of control, field-

dependence, "g" and performance in training .............. . 41
Figure 13. Training Treatment Conditions ......................... 42
Figure 14. Interaction between videotaped modeling and videotaped
feedback ........................................ . 56
xii

 

Figure 15. Interaction between videotaped modeling and locus of control . . 59

Figure 16. Main effect and interaction for post training knoweldge ...... . 67
Figure 17. Interaction between videotaped feedback and self-rating ..... . 136
Figure 18. Triple interaction between videotaped feedback, self-efficacy

and self-rating .................................... . 138
Figure 19. Interaction between videotaped modeling and self-effiacy . . . . . 144

Figure 20. Interaction between videotaped modeling and feedback
experience ....................................... . 146

xiii

INTRODUCTION

Organizations spend more than $30 billion annually on the training and
development of employees (Huber, 1985). Unfortunately, the effectiveness of
training programs is often less than desirable (Brush & Licata, 1983; Goldstein,
1986). Consequently, both researchers and trainers alike have a vested interest in
understanding the conditions under which learning will be enhanced.

One area of research that has shown promise in improving the effectiveness
of training is research on the use of videotapes. Two types of videotaped
information have received special attention in the literature: (1) a presentation of
a videotaped model, and (2) Videotaped feedback in which the trainee observes
himself or herself (Decker & Nathan, 1985). Numerous studies have clearly
demonstrated that presenting videotaped models aids in the learning of new
behaviors (for excellent reviews see Decker & Nathan, 1985; Kanfer & Goldstein,
1980). Similarly, research on the impact of videotaped feedback indicates that this
technique has tremendous potential to affect human behavior (Dowrick & Biggs,
1983; Hung & Rosenthal, 1978; Decker & Nathan, 1985).

One limitation of the videotaped modeling and videotaped feedback research,
however, is that it has utilized a fixed treatment approach. That is, it was assumed
that all individuals regardless of their knowledge, skills, abilities or other attributes

(e.g., personality characteristics) would benefit from the same treatment. Recently,

 

2

it has been argued that behavior is determined by "a complex interplay of situations
and persons" (Magnusson & Endler, 1977, and that training researchers need to
examine how aptitudes (i.e., any characteristic of a person that is predictive of his
or her success under a given treatment; Cronbach & Snow, 1977) and treatments
interact to inﬂuence learning and performance (Baldwin & Ford, 1988; Wexley,
1984).

To that end, the purpose of the present research is four fold: (1) to provide
a theoretical explanation for the processes underlying the effects of videotaped
modeling and videotaped feedback, (2) to discuss the similarities and differences
between videotaped modeling and videotaped feedback, (3) to examine the
effectiveness of these two techniques seperately and in combination with one another
and, (4) to examine possible individual difference variables that may inﬂuence the

effectiveness of these two techniques.

 

CHAPTER 1. LITERATURE REVIEW

Theoretical Overview

To date, research on videotaped modeling has relied heavily on Bandura’s
(1982) Social Learning Theory to explain its effects (Decker & Nathan, 1985), while
most explanations of the effects of videotaped feedback share one of two themes, its
motivational properties or its informational value (Hung & Rosenthal, 1978). With
regard to its informational value, it has been suggested that the effects of videotaped
feedback may be due to providing individuals with information not previously
available to them, whether from ignorance or mistaken self-perceptions (Kanfer,
1970). Bandura (1986) has similarly argued that self-observation is the ﬁrst step
toward doing something to change one’s behavior. In order for individuals to exert

inﬂuence over their actions, they have to know what they are doing. With regard

 

to its motivational properties it has been suggested that Bandura’s concept of self-
efficacy offers a framework to encompass the mechanisms underlying videotaped
feedback effects (Hung & Rosenthal, 1978). Each of these perspectives are
discussed in more detail below.
Videotaped Modeling: A Social Learning Theory Perspective

According to Bandura’s Social Learning Theory (Bandura, 1977a, 1982), the
primary determinants of behavioral change are: ( 1) expectations that one can

successfully execute a particular behavior (self-efﬁcacy); and (2) expectations that

4

a given behavior will lead to certain outcomes (outcome expectations). Although
both are important, Bandura (1982) has given the concept of self-efficacy a more
central role in the explanation of behavior change. Bandura asserts that individuals
who doubt their self-efﬁcacy will not attempt a behavior, regardless of their
expectations of outcomes. Bandura (1977a) suggests that self-efficacy inﬂuences
choice of activities, how much effort people will expend, and how long they will
persist in the face of adversity. The stronger the perception of self-efficacy, the
more likely the person is to engage in the activity, the greater his or her effort, and
the longer his or her persistence.

Research on Social Learning Theory has contributed greatly to understanding
the role of models in the learning process (Bandura, 1977b). According to Bandura
(1986), modeling inﬂuences human behavior indirectly through its inﬂuence on self-
efficacy and outcome expectations. Bandura (1982) suggests that vicarious
experience is a major source of self-efficacy. Watching other similar people
successfully perform a task can convey a vicarious sense of efficacy to individuals
that they can complete the task as well. On the other hand, observing Similar others
fail will tend to lower perceptions of self-efficacy (Brown & Inouye, 1978). Outcome
expectations are also thought to be inﬂuenced by models. By observing the
consequences of a model’s behavior, an observer is likely to gain information on
whether or not a particular behavior will lead to desired outcomes.

Videotaped Modeling: A Review of the Literature

Bandura (1986), in his comprehensive review of the literature, cited numerous

studies which have supported the mediating role of self-efficacy and outcome

expectations in the vicarious learning process (e.g., Brown & Inouye, 1978; Schunk

5
& Hanson, 1985; Omizo, Cubberly & Cubberly, 1985 ; Hamilton, Thompson & White,
1970; Kazdin, 1974b; 1975). Research shows that the extent to which modeling will
inﬂuence self-efficacy, outcome expectations and subsequent behavior change is
dependent on the characteristics of the model (Baron, 1970; Flanders, 1968; Decker
& Nathan, 1985; Bandura & Menlove, 1968). Each of these topics are described in
more detail below.

Self-eﬁicacy Expectations. Research examining the relationship between
modeling and self-efﬁcacy has shown that subjects exposed to successful models have
greater increases in self-efficacy and achievement than subjects not exposed to
models (Schunk & Hanson, 1985; Omizo, et al., 1985). In addition, observing a peer
model perform a task effectively leads to higher self-efﬁcacy and achievement than
observing a teacher model (Schunk & Hanson, 1985) and participant modeling (i.e.,
performing a task while observing a successful model) leads to higher self-efﬁcacy
and achievement than merely observing a model (Omizo et al., 1985).

Outcome Expectations. Hamilton et al. (1970) have demonstrated the
importance of rewarding the model. Their results showed that modeling was more
effective in inﬂuencing behavior when the observers see the model either rewarded
or punished for the behavior but is not effective when outcomes (i.e., either
punishment or rewards) are absent. In addition, Kazdin (1974b; 1975) has shown
that modeling with imagined favorable consequences had a signiﬁcantly greater
impact on behavior than modeling without them.

Model is Characteristics. Research shows that models will be most inﬂuential
when the model is similar to the observer in terms of age, sex, cultural background,

personality, and mood (Baron, 1970; Bandura, 1977a; Flanders, 1968; Kazdin, 1974a;

 

6
Thoresen & Hosford, 1973). Models Should also be likeable (Sampson and Insko,
1964), prestigeful (Duster & McAllister, 1973; Thoresen, Hosford, & Krumboltz,
1970), physically attractive (Bandura & Huston, 1961) and similar or slightly higher
in competence than the observer (Dowrick, 1983; Kazdin, 1974a; Kornhaber &
Schroeder, 1975; Rosenkrans, 1967).

If observers are particularly anxious, then coping models (i.e., models who
themselves appear to be anxious but are effectively learning to cope with the
situation) are generally preferred over models that demonstrate mastery and ease
in performing the task (Dillon, Graham and Aidells, 1972; Kazdin, 1973, 1974a,
1975; Meichenbaum, 1971).

Self-efficacy and subsequent behavior change are further enhanced when
multiple models are used. That is, watching different people master different tasks
is superior to exposure to the same performances by a single model (Bandura &
Menlove, 1968; Kazdin, 1974a, 1975, 1976). The rationale for multiple models is
that the observer is more likely to identify with one of the models, and if people
of widely differing characteristics succeed in many different situations then the
observer has a more reasonable basis for increasing his or her own sense of efﬁcacy.
Greater modeling will also occur when a positive model is shown (with or without
a negative model) rather than a model only depicting what not to do (Decker &
Nathan, 1985; Baldwin, 1987).

Summary. Research has demonstrated that videotaped models inﬂuence self-
efficacy (Bandura, 1986). Watching other similar people successfully perform a task
can convey a sense of efficacy to individuals that they can perform the task as well.

Research has also demonstrated that videotaped models have informational value

7
(Hamilton et al., 1970). By observing a model exhibit the desired behavior,
individuals can form an idea of how speciﬁc acts must be combined and sequenced
to produce a new behavior, and, by observing the consequences of a model’s
behavior, an observer is likely to gain information on whether or not a particular
behavior will lead to desired outcomes. In sum, it is suggested that videotaped
modeling inﬂuences learning and behavior indirectly through its inﬂuence on self-

efficacy and the acquisition of knowledge. See Figure 1.

 

Knowledge

 

 

 

 

 

Vldeotaped Performance
In
Modeling Training

 

 

 

 

 

 

 

Self-efficacy

 

 

 

Figure I. A process model of the inﬂuence of videotaped modeling on
performance in training.

 

8
Vldeotaped Feedback: An Informational Perspective
It is a widely accepted notion among training researchers that feedback is an

essential part of the human learning process (Goldstein, 1986; Wexley & Latham,
1981). Feedback provides individuals with information about the effectiveness Of
their efforts to perform a particular task. Such information allows individuals to
make adjustments in their subsequent behavior if a discrepancy between actual and
desired behavior is perceived to exist. Given the importance of feedback, videotaped
feedback has some unique advantages. For example, unlike verbal feedback, the
information imparted by videotaped feedback is not colored by others’ values or
interpretations. Rather, it emanates from a highly credible and unbiased source (the
videotape). Thus, individuals can devote full attention to the content of the
feedback, rather than the source of the information (Hung & Rosenthal, 1978). In
addition, videotaped feedback allows individuals to see themselves as others see
them. Thus, individual tendencies to protect or enhance one’s self-image through
cognitive distortion is lessened. In sum, from an informational perspective,
videotaped feedback is effective in enhancing performance in training because it
provides trainees with feedback that is both immediate and objective. This feedback
allows trainees to change their subsequent behavior thereby increasing their
knowledge and skills.
Videotaped Feedback: A Self-efﬁcacy Perspective

According to Hung and Rosenthal (1978), Bandura’s concept of self-efﬁcacy
offers a framework to encompass the mechanisms underlying the effects of
videotaped feedback. As stated earlier, Bandura (1977a, 1982) asserts that self-

efficacy (i.e., expectations that one can. successfully execute a particular behavior)

9

plays a central role in the explanation of behavior change. Self-efficacy inﬂuences
choice of activities, how much effort people will expend, and how long they will
persist in the face of adversity. According to Bandura (1977a, 1982, 1986) people
acquire information about their level of efficacy from four sources: performance
accomplishments, vicarious experiences, verbal persuasion, and physiological states.
Hung and Rosenthal (1978) suggest that the ﬁrst two sources (performance
accomplishments and vicarious experiences) have special relevance since they enter
into any treatment on videotaped feedback. Performance accomplishment occurs
when the individual performs the behavior being videotaped, and vicarious input
occurs when the individual engages in self-observation.

Recent research by Gonzalez and Dowrick (1982) and Dowrick (1983) lends
support to the use of videotaped feedback as a self-efficacy enhancing technique.
In one study Dowrick (1983) examined the effects of two videotape feedback
conditions, observing one’s errors versus observing one’s correct behaviors. The
subjects were 18 evenly matched pairs of pool players who competed with each other
twice. After the ﬁrst round, losers only were assigned to one of the two treatment
conditions. In one condition tapes were edited to Show only successful shots, and
in the other condition only the missed shots were shown. Results showed that all
subjects in the "successful shot" condition showed increases in performance whereas
less than half the other players improved.

Gonzalez and Dowrick (1982) conducted a study to investigate whether
videotapes edited so that the individual sees himself or herself performing correctly
work by providing information about proper behavior or by boosting self-efficacy.

This study was conducted using the same procedure as that described in the Dowrick

 

10

(1983) study except, rather than observing one’s errors, the videotapes were edited
so that unsuccessful shots were made to look successful. Results showed that both
groups had significant improvements in performance over a control group and that
virtually identical improvements were achieved with either apparent or real success
on tape. These authors concluded that "successful" videotaped feedback (i.e., edited
to look successful) works primarily by boosting self-efficacy and that motivation
without skills information may, at least in some conditions, be sufﬁcient for
behavioral change using videotaped feedback.
Vldeotaped Feedback: A Review of the Literature

To date, only a hadful of studies have examined the inﬂuence of videotaped
feedback in training situations, however, research examining the effectivieness of
videotaped feedback in psychotherapy and teacher education has been around for
many years. Alger and Hogan (1969) have stated that "video tape recording
represents a technological breakthrough with the kind of signiﬁcance for psychiatry
that the microscope has had for biology." Subsequent reviews in the psychotherapy
literature (Sanborn, Pyke & Sanborn, 1975; Gur & Sackeim, 1978; Hung &
Rosenthal, 1978) and the teacher education literature (Fuller & Manning, 1973) have
been far less enthusiastic. Furthermore, many of the earlier studies were highly
inadequate in terms of methodology. For example, lack of a control group, highly
subjective outcome measures and experimenter bias were common problems (Hung
& Rosenthal, 1978).

With regard to studies examining the inﬂuence of videotaped feedback in

training situations, Barbee and Keil (1973) examined the impact of videotaped

feedback on the job interviewing skills of culturally disadvantaged persons. Sixty

11

four clients from three manpower agencies were randomly assigned to one of three
treatment conditions: (a) a combined treatment group consisting of videotaped
feedback and behavior modiﬁcation techniques (identification of key behaviors,
rehearsal and reinforcement); (b) a videotaped feedback only group; and (c) a no-
treatment control group. Results indicated that the combined treatment group had
signiﬁcantly greater improvement in interview behavior. However, since these
researchers did not include a behavior modification-only treatment group, it is
impossible to conclude whether videotaped feedback had any additive contribution
to learning and behavior change over and above that of the behavior modiﬁcation
techniques.

Speas (1979) examined the impact of four treatments: modeling, role playing,
modeling plus role playing, and modeling plus role playing and videotaped feedback
on the interviewing skills of 56 soon-to-be released male in-mates. Her results
indicated that the modeling plus role playing and the modeling plus role playing and
videotaped feedback groups scored signiﬁcantly greater than the control group (i.e.,
subjects on a waiting list) on all dependent measures. In addition, the videotaped
feedback group was the only treatment group which was rated significantly higher
than the control group on probability of hire.

Del Rey (1978) examined the impact of two types of augmented information
feedback on dart throwing skill, knowledge of performance (videotaped feedback)
versus knowledge of results (verbal feedback on the difference between one’s pretest
score and present score), on dart throwing skill. Her results indicated that while all
subjects did receive immediate results feedback from the task itself, subjects who

were given knowledge of performance (videotaped feedback) had significantly better

12
form and accuracy on the post test than subjects who were given knowledge of
results.

Finally, Decker (1983) examined the impact of rehearsal group size and
videotaped feedback on the training skills of 36 undergraduates. Speciﬁcally, the
training program was designed to teach "on-the-job training" behaviors. Subjects
were randomly assigned to one of three conditions: (1) one observer/videotaped
feedback, (2) large group observing/videotaped feedback, (3) large group
observing/ no videotaped feedback. A multivariate analysis of variance with a prior
contrasts revealed that subjects in the condition employing one observer and
videotaped feedback had signiﬁcantly higher performance than the other two
conditions.

Summary. Numerous studies have supported the use of videotaped feedback
in learning and behavior change situations (Barbee & Keil, 1973; Decker, 1983; Del
Rey, 1978; Speas, 1979; Thoresen & Hosford, 1973). It has been suggested that
videotaped feedback inﬂuences learning and behavior change indirectly through its
impact on self-efficacy and the acquisition of knowledge. See Figure 2. Earlier it
was suggested that videotaped modeling also inﬂuences learning and behavior change
indirectly through its impact on self-efﬁcacy and the acquisition of knowledge. Thus,
both vidoetaped modeling and videotaped feedback are predicted to inﬂuence
learning and behavior change via the same underlying process (i.e., Figure 2 is the

same as Figure 1).

13

 

Knowledge

 

 

 

 

 

Vi de otape d Performance
In
Feedback . .
Training

 

 

 

 

 

 

 

Self-efficacy

 

 

 

Figure 2. A process model of the inﬂuence of videotaped feedback on
performance in training.

Since both training techniques are predicted to inﬂuence learning and
behavior change via the same underlying processes, one might ask whether or not
the two techniques are indeed different, and if they are different, what is the
"meaning" of this difference with regard to its inﬂuence on self-efﬁcacy and the
acquisition of knowledge? These issues are discussed in further detail below.
Vldeotaped Modeling Versus Vldeotaped Feedback: Similarities and Differences

One could argue that videotaped feedback is a speciﬁc form of videotaped
modeling in which the observer and the model are the same person. If the
individual performed the desired behavior correctly on the videotape he or she
would serve as a positive model for him- or herself. Conversely, if the individual
performed the desired behavior incorrectly on the videotape he or she would serve

as a negative model for him— or herself. The two techniques are different, however,

 

14

in that an individual observing him-or herself would have perfect identiﬁcation with
the model. In a videotaped modeling treatment, identiﬁcation with the model would
depend on the similarity between the observer and the model. Since research has
shown that observers’ perceptions of being similar to the model have a signiﬁcant
impact on the effectiveness of modeling (Baron, 1970; Bandura, 1977a; Flanders,
1968; Kazdin, 1974a; Thoresen & Hosford, 1973), one might expect that videotaped
feedback would, in some situations, have a more profound impact on self-efficacy
than videotaped modeling. In support of this argument, Bandura (1986) has found
that performance accomplishments (i.e., observing oneself succeed or fail) have a
stronger impact on self-efﬁcacy than modeling (i.e., observing someone else succeed
or fail).

The two techniques may also differ in the amount of information provided.
Modeling tapes are constructed so that they include examples of each of several
learning points. Videotaped feedback tapes, on the other hand, will only include
those behaviors exhibited by the trainee. Thus, videotaped feedback tapes may or
may not include all the learning points. As a result, one would expect videotaped
feedback to be less effective than videotaped modeling as a training technique for
tasks that require visual demonstrations. For example, physical tasks such as
dancing, aerobics, painting, golf, etc. may require visual demonstrations in order for
trainees to learn effectively. Without ﬁrst having a visual demonstration, trainees
may not be able to produce the desired behavior on their own and as a result,
observing oneself perform a task on videotape may have little or no impact on their
subsequent performance. For other tasks it may not be as necessary for the trainee

to observe the behavior being performed correctly in order to be able to produce the

 

15

behavior him or herself. For example, for social skills training, such as interview
training, it may not be necessary to observe a model maintaining eye contact with
the interviewer to learn to maintain eye contact.

Videotaped modeling and videotaped feedback are also different in that
videotaped modeling provides information about someone else’s ability to perform
a particular behavior while videotaped feedback provides individuals with
information about their own performance efforts. Information about one’s own
performance is crucial for learning and behavior change. In order for an individual
to improve his or her performance, he or she needs to know that he or she is doing
something wrong (Bandura, 1986). Thus, being aware that one’s own performance
is unsatisfactory is a necessary but not sufﬁcient condition for behavior change. Self-
observation through the use of videotaped feedback allows trainees to compare their
actual behavior to that of a standard and thereby identify what they are doing wrong.
Modeling, on the other hand does not provide this type of information. Trainees in
a modeling training program may learn what the correct behaviors are but not
whether they can perform them themselves. In other words, videotaped feedback
has greater personal relevance for the trainee. Research in the area of
communication has demonstrated that personal relevance has a positive inﬂuence
on attention and retention processes (Hovland, Janis & Kelly, 1953).

In summary, while both videotaped modeling and videotaped feedback are
predicted to inﬂuence performance in training through the same underlying processes
(i.e., knowledge and self-efficacy), several important differences between the two
techniques were noted including: degree of identiﬁcation with the model, number or

quality of behaviors exhibited by the model, and personal relevance. It has been

 

16

suggested that identiﬁcation with the model and personal relevance may be greater
when using videotaped feedback and that the number or quality of behaviors
exhibited by the model may be greater when using videotaped modeling. However,
since the present study will utilize a fixed effects design, one is necessarily limited
in making conclusions or generalizations to the speciﬁc treatments used, therefore
it is not the intent of this study to examine the relative effect of each treatment.
Vldeotaped Modeling And Vldeotaped Feedback: A Combined Treatment Analysis

As stated earlier, modeling and performance accomplishments are the two
most inﬂuential sources of self-efficacy (Bandura, 1982; 1986). Observing a model
successfully perform a task may convey a sense of efﬁcacy to the observer that he
or she can perform the task as well, while videotaped feedback may provide
individuals with information about their performance accomplishments. From an
information perspective, modeling provides individuals with visual information on
how to combine and sequence their actions to produce the new behavior, while
videotaped feedback makes individuals more aware of discrepancies between
intended and actual behavior allowing them to increase their effort or change their
strategy on subsequent trials. Thus, from both a self-efﬁcacy perspective and an
informational perspective, one might argue that a combined treatment condition
including both modeling and videotaped feedback would have a greater impact on
self-efficacy and performance than either treatment alone.

One Study that has examined the relative and combined effects of modeling
and videotaped feedback is that of Walter (1975). This author examined the effects
of modeling and videotaped feedback on the group problem solving behavior of 227

college students. Subjects were assigned to one of ﬁve experimental conditions

17
(1 = no instructions, 2 = instructions, 3 = videotaped feedback + instructions, 4
= modeling + instructions, 5 = videotaped feedback + videotaped modeling +
instructions). In Experiment I, the instructions consisted of telling subjects (N = 133)
to be more non-evaluative and to try to generate as many ideas as possible. In
Experiment H, the instructions consisted of telling subjects (N = 144) to be more
evaluative of the major points which were most likely to yield good solutions.

A total of 14 different behavioral changes were examined in each experiment
resulting in a total of 28 separate analyses of variance tests. The results indicated
that 12 statistically significant behavioral shifts were attributable to modeling, seven
statistically significant shifts were attributable to videotaped feedback and ﬁve
statistically significant shifts were attributable to the interaction of videotaped
feedback and modeling. However, five of the seven signiﬁcant effects found for the
videotaped feedback manipulation occurred in the ﬁrst experiment and were
opposite to what was predicted. It appears that subjects exposed to Videotaped
feedback in the ﬁrst experiment became less verbal, less interactive and more
inhibited. The author attributed this ﬁnding to the fact that subjects in the first
experiment expressed great curiosity, suspicion, and anxiety about possible
experimental manipulations between and after the problem solving efforts. N 0 such
feelings were expressed by subjects in the second experiment. In summary, it is
difficult to draw conclusions from Walter’s (1975) experiments due to major
methodological ﬂaws including high demand characteristics and high experimentwise
error.

Based on previous research which has demonstrated that modeling and

videotaped feedback have a positive impact on behavior change (Speas, 1979; Del

18

Rey, 1978; Decker, 1983; Kazdin, 1973, 1974a, 1975, 1976; Bandura & Menlove,

1968; Baldwin, 1987), it is predicted that both videotaped modeling and videotaped

feedback will have a significant positive impact on performance in training. It is also

predicted that the combined treatment condition including both modeling and
videotaped feedback will have a greater impact on self-efficacy and performance
than either treatment alone and that subjects in the no videotaped feedback/no
videotaped modeling condition will have signiﬁcantly lower performance than
subjects in any other condition (the no-modeling condition refers to a training
treatment that includes instruction and practice but no videotape of a model

performing the task, the no-videotaped feedback treatment condition refers to a

training treatment in which trainees receive instruction and opportunity to practice

but do not observe themselves performing the task on videotape). More Specifically,
it is predicted that:

H1: There will be two main effects and an interaction such that ( 1) subjects in the
videotaped modeling treatment conditions will have higher performance than
subjects in the no videotaped modeling treatment conditions, (2) subjects in
the videotaped feedback treatment conditions will have higher performance
than subjects in the no videotaped feedback treatment conditions, and (3)
subjects in the combined treatment condition will have Signiﬁcantly greater
performance than subjects in any other condition and subjects in the no

videotaped feedback / no videotaped modeling condition will have signiﬁcantly
lower performance than subjects in any other condition. (See Figure 3.).

l9

Vldeotaped

// MOdellng

No Vldeotaped
Performance Modeling

Tralnlng

 

 

No Vldeotaped Vldeotaped
Feedback Feedback

Figure 3. Predicted interaction between videotaped modeling and videotaped
feedback.

To date, research that has examined the effectiveness of videotaped modeling
and videotaped feedback has utilized a ﬁxed treatment approach. That is, it was
assumed that all individuals regardless of their knowledge, skills, abilities or other
attributes (e.g., personality characteristics) would benefit from the same treatment.
Recently, it has been argued that behavior is determined by "a complex interplay of
situations and persons" (Magnusson & Endler, 1977; Weiss & Adler, 1984), and that
training researchers need to examine how aptitudes (i.e., "any characteristic of a
person that forecasts his or her probability of success under a given treatment;"
Cronbach & Snow, 1977) and treatments interact to inﬂuence learning and
performance (Baldwin & Ford, 1988; Wexley, 1984). Thus, it is suggested that
individual differences may interact with the effects of videotaped modeling and

videotaped feedback to inﬂuence training outcomes. In the following section,

20

research examining the effect of the interaction between individual differences and
training treatments will be discussed in more detail.
An Overview of Aptitude- Treatment Interaction Research

The basic premise underlying aptitude-treatment interaction (ATI) research
is that no single procedure provides Optimal learning for all individuals. Some
individuals will be more successful with one training technique whereas other
individuals will be more successful with an alternative training technique.
Consequently, a greater proportion of individuals will be successful in attaining the
training objectives when the training program is differentiated for different types of
individuals.

Aptitudes and treatments may interact in two ways to inﬂuence performance
in training. The first type of ATI, a disordinal interaction, indicates that one
treatment yields high achievement for individuals at one end of the aptitude
continuum whereas a different treatment yields high achievement for individuals at
the other end (See Figure 4.). Performance would be maximized, then, if the
individuals at each end of the continuum received different treatments. In the
second type of ATI, an ordinal interaction, the aptitude-treatment regressions may
have different Slopes but the regression lines do not intersect within the aptitude
range of interest (See Figure 5.). In other words, one treatment is superior for all
individuals, but the magnitude of the difference between treatments varies at
different aptitude levels. Ordinal interactions, like disordinal interactions, may also
lead to differential assignment of individuals to treatments if the treatment that
consistently yields higher achievement is more expensive than the other treatment.

The more expensive treatment would be used only for those who benefit from it the

21

most. Those individuals who achieve at approximately the same level regardless of

treatment would receive the less expensive treatment.

 

 

 

 

 

Treatment A Treatment A
Performance Perform
In h
Trehlng Trehing
Treatment 8 __ Treatment 8
Aptitude Aptitude
Figure 4. Diagrammatic representation Figure 5. Diagrammatic representation
of a disordinal interaction. of an ordinal interaction.

Even though the notion that people respond differently in different situations
is intuitively appealing and has received a great deal of research interest, there has
been considerable debate over whether or not ATIs actually exist (Bracht, 1970), and
whether designing different treatments for different individuals is practical
(Gehlbach, 1979).

With regard to the first issue, most reviews have concluded that there is little
or no support for the existence of aptitude by treatment interactions. For example,
Bracht (1970) systematically analyzed 90 ATI studies and found that only 5 provided
evidence of a disordinal interaction. The other 85 indicated either no interaction or
ordinal interactions. Berlinger and Cahen (1973) concluded that most studies of
interaction have not been replicated, and when replicated, interactions have not been

confirmed. More recently, Pintrich, Cross, Kozma and McKeachie (1986) similarly

22
stated that ATI research findings cannot be used with any conﬁdence to construct
general principles of instructional design.

Many researchers are still optimistic that ATIs exist, however, and feel that
methodological problems provide alternative explanations for the relatively
unsupportive results found thus far (Berlinger & Cahen, 1973; Cronbach & Snow,
1977; Snow & Lohman, 1984). For example, Cronbach and Snow (1977) argued that
the results of many studies (both positive and negative) must be discounted because
of poor research procedures including: use of subgrouping rather than moderated
regression, failure to correct for error of measurement and inadequate sample size.

With regard to practicality, Millman (1974) argued that adaptive treatment
is impractical because it only beneﬁts a few individuals. This is because in most
disordinal interactions the aptitude-treatment regression lines intersect at one of the
extremes of the normal distribution of the aptitude, and most cases are in the middle
where there are small differences between treatments. Burns (1980) has also argued
against the practicality of adaptive treatment claiming that aptitudes often change
over the course of a treatment, and thus, a particular treatment assignment decision
may be valid for only a limited period of time. Consequently, aptitudes would have
to be reassessed periodically and individuals would have to be reassigned to a
different treatment if their aptitude changed.

Perhaps a more important explanation for the unsupportive results found in
ATI studies is the type of aptitude examined. To date, most ATI studies have used
measures of general or specific ability. Since, general ability and speciﬁc ability (to
a lesser extent) have been found to be highly correlated with performance across a

wide range of tasks and situations (Jensen, 1986; Hunter, 1986; Thorndike, 1986),

23

one would expect a main effect for ability such that high ability individuals perform
better than low ability individuals regardless of treatment. Thus disordinal
interactions would be extremely unlikely and ordinal interactions would be likely but
of little significance. In support of this argument, Whitener (1989) conducted a
meta-analysis of studies that examined the effect of the interaction between ability
and instructional technique. She found that the weighted average regression
coefﬁcient for the interaction term was .11 with a 90 % conﬁdence interval ranging
between -.005 to .225. Thus, this author found no support for the existence of
aptitude-treatment interactions when ability was the aptitude being examined.

It is suggested that personality variables, as opposed to general or speciﬁc
abilities, may be more likely to interact with training treatments to inﬂuence training
outcomes. This is because personality variables often have motivational components
(Rotter, 1966; Korman, 1970). Recent research in the area of training has found
that motivation, as well as ability, plays a major role in determining training
outcomes (Ryman & Biersner, 1975; Tubiana & Benshakar, 1982; Baldwin & Karl,
1987). It has also been suggested that personality variables inﬂuence training
outcomes through their inﬂuence on trainee motivation (Noe, 1986). In support of
the existence of personality by treatment interactions, Bracht (1970) noted that three
of the five studies which reported significant disordinal interactions used personality
variables.

The present study will attempt to extend past research on adaptive treatment
by examining whether personality variables are more likely than general ability to
interact with training treatment to inﬂuence training outcomes. Two personality

variables will be examined: locus of control and field-dependence. These two

24

variables were chosen because of their relevance to the two training techniques
examined in this study. For example, locus of control has been found to inﬂuence
information search (Davis & Phares, 1967), while ﬁeld-dependence has been found
to inﬂuence the amount of attention paid to social stimuli (Witkin & Goodenough,
1977). It is predicted that both of these variables will have a signiﬁcant impact on
the effectiveness of both videotaped modeling and videotaped feedback. In addition,
this study will test the proposition made above that personality variables are more
likely to interact with training treatment to inﬂuence training outcomes than general
or specific abilities. To that end, the relationship between "g", general mental ability,
and the two videotaped training treatments will be examined. Finally, the impact
of ﬁeld-dependence and locus of control on self-efﬁcacy and knowledge will be
examined.
Vldeotaped Modeling: An Examination of Personality by Treatment Interactions

Locus of Control. According to Rotter (1966), individuals who have an
internal locus of control believe that positive and negative events are contingent on
their own behavior, and therefore, are under personal control. Individuals who have
an external locus of control believe that outcomes are unrelated to their own
behaviors, beyond personal control, and therefore attribute the causes for events to
luck, fate, or the actions of others.

Research on achievement behavior clearly suggests that internals are more
achievement oriented than externals. For example, Nowicki and Strickland (1973)
found that internal beliefs in children were related to higher grades in school, as did

Gruen, Koerts, and Baum ( 1974) and Botinelli and Weizmann (1973). Similarly,

25
Brown and Strickland (1972) found internal beliefs to be related to high grade-
point averages for college students.

Waters (1972) found that internal beliefs were associated with greater
persistence on a difficult and time consuming task described as dependent on their
own skill. External beliefs, in contrast, were associated with greater persistence on
tasks described as dependent on chance.

Davis and Phares (1967) found that locus of control had a significant impact
on the information seeking behavior of 84 college students. Subjects were led to
believe that they were involved in a study of social inﬂuence and attitude change and
that their task was to inﬂuence the attitude of another person concerning the
Vietnam War. Subjects were then given a few minutes to think about what
information they might like to have about the person they would be attempting to
inﬂuence. Results indicated that internals asked for signiﬁcantly more information
about the other person than did externals.

Baumgartel, Reynolds and Pathan (1984) conducted a survey of 260 managers
who had participated in a one-week management development program designed to
improve self-understanding, interpersonal effectiveness and skill in group
membership. Their results indicated that those individuals who reported greater
effort and success in applying new knowledge were more likely to be internals than
externals. These same authors replicated this study in a sample of 246 managers in
India and found the same results.

Chambliss and Murray ( 1979) examined the impact of locus of control on 68
college women involved in a weight loss program. During the ﬁrst two weeks all

subjects were given a standard weight reduction program including moderate diet,

26

mild exercise, and simple behavioral techniques, as well as 14 diet pills to be taken
once a day (a placebo). At the end of the 2-week period half of the subjects were
debriefed about the pills and were told that successful weight loss was a result of
their own effort (self-efﬁcacy enhancing condition) while the other half was told that
successful weight loss was a result of the diet pills (drug efﬁcacy condition). These
authors found that internals in the efﬁcacy enhancing condition lost signiﬁcantly
more weight in the second 2-week period than any of the other three groups (i.e.,
internals-drug efficacy, externals-self—efficacy, externals-drug efﬁcacy).

In sum, these studies suggest that internals are more likely than externals to:
(a) actively seek out information in social situations (Davis & Phares, 1967), (b)
apply new knowledge gained in training to work settings (Baumgartel, et al. 1984),
and (c) change their behavior in treatments designed to enhance self-efﬁcacy
(Chambliss & Murray, 1979).

Since internals have the tendency to accept responsibility for outcomes, it is
suggested that internals will be more likely to believe that learning is a result of
personal effort. Thus, internals may respond more readily to modeling, because they
tend to believe that they, like the models, are in control of their environments.
Externals, on the other hand, may not beneﬁt from modeling because of their
tendency to attribute success or failure to factors beyond their control. In other
words, externals believe that outcomes are not a result of one’s own behavior
(Rotter, 1966). It follows then, that externals may also believe that changing one’s

behavior to imitate a model would have little impact on their own performance.

 

 

 

27
Based on the literature reviewed above it is predicted that:

H2: There will be two main effects and an interaction such that (1) internals will
have higher performance than externals, (2) individuals in the modeling
treatment will have higher performance than those in the no-modeling
treatment, and (3) the relationship between modeling and performance will
be greater for internals than externals (See Figure 6.).

Internals

Performance

In —-
, , Externale
Training

 

 

No Vldeotaped Vldeotaped
Modeling Modeling

Figure 6. Predicted interaction between locus of control and videotaped modeling.

Field-dependence. Witkin and Goodenough’s (1977, 1981) concept of ﬁeld-
dependent-independent cognitive style may also have implications for adaptive
treatment. Witkin and Goodenough (1981) deﬁne this concept as having three
characteristics. "First, it is a pervasive dimension of individual functioning, showing
itself in the perceptual, intellectual, personality, and social domains, and connected
in its formation with the development of the organism as a whole. Second, it
involves individual differences in process rather than content variables; that is to say,
it refers to individual differences in the how rather than the what of behavior.

Third, people’s standing on the dimensions is stable over time" (p. 58).

28

One of the main features of ﬁeld-dependence~independence is the tendency
to rely on either one self or the external environment as referents for behavior.
Individuals who rely on themselves are said to have ﬁeld-independent cognitive styles
while individuals who rely on external referents are said to have ﬁeld-dependent
cognitive styles. Field-dependence-independence, measured as one’s ability to
determine the upright in space, is significantly related to disembedding ability (i.e.,
the ease of locating simple figures in a complex ﬁgure)(Dumsha, Minard &
McWilliams, 1973; Pizzamiglio, 1976; Witkin, Goodenough & Karp, 1967).

While field-dependence-independence and locus of control bear a surface
similarity, Witkin and Goodenough (1981) claim that the two constructs are
conceptually quite different. These authors assert that "field-dependence-
independence is a process variable, representing degree of autonomous functioning
in assimilating information from self and field, [while] locus of control is an
attitudinal or belief variable, representing expectancies of internal or external control
of reinforcement, or greater or less fatalism as an outlook toward life" (p. 48). In
other words, it is possible for someone to have a tendency to search and attend to
external information (i.e., ﬁeld-dependent) and still believe that one is in control of
one’s own fate. In support of this argument, numerous studies have shown that
measures of these two dimensions are unrelated (Bartelt, 1970; Deever, 1968; Fitz,
1971; Lefcourt, Gronnerud, & McDonald, 1973; Lefcourt, Hogg, & Sordini, 1975;
Lefcourt & Telegdi, 1971; Roodin, Broughton, & Vaught, 1974; Rotter, 1966;
Shapson, 1973; Tobacyk, Broughton, & Vaught, 1975; Zara, 1970).

Research examining the relationship between ﬁeld-dependence and social

behavior has demonstrated that people who are field dependent in perception of the

29

upright and who have limited disembedding ability have an interpersonal orientation,
whereas people who are ﬁeld independent and competent in disembedding have an
impersonal orientation (Witkin & Goodenough, 1981). Thus, ﬁeld-dependent
individuals, more than field-independent individuals, pay selective attention to social
cues; they favor situations that bring them into contact with others over solitary
situations; they prefer educational-vocational domains that are social in content and
require working with people; they seek physical closeness to people in their social
interactions; and they are more open in their feelings (Witkin & Goodenough, 1977).
Other characteristics that have been ascribed to people who are ﬁeld dependent on
tests of perception of the upright and who have low disembedding ability include
warm, affectionate, tactful, accommodating, nonevaluative and accepting of others,
not likely to express hostility directly against others when such feelings are aroused
in an interpersonal context. People who are ﬁeld independent tend to be
demanding, inconsiderate, manipulating others as a means of achieving personal
ends, cold and distant in relations with others (Witkin & Goodenough, 1977).

Research on the relation between field dependence-independence and
educational-vocational preferences, choices, and performance (Quinlan & Blatt,
1972; Witkin, Moore, Goodenough, & Cox, 1977; Witkin, Moore, Oltman,
Goodenough, Friedman, Owen, & Raskin, 1977) suggests that people are likely to
favor and do better in educational-vocational domains to which their cognitive styles
suit them. Since, field-dependent people, compared with ﬁeld-independent ones,
give more evidence of interpersonal competencies, it is suggested that ﬁeld-
dependent people will perform better than field-independent people in training

programs focusing on interpersonal skills.

30

The results of other studies suggest that ﬁeld-dependence-independence may
moderate the extent to which individuals are inﬂuenced by social information (Ruble
& Nakamura, 1972; Koran, Snow & McDonald, 1971). For example, Ruble and
Nakamura (1972) examined the inﬂuence of a social cue (i.e., the experimenter
repeatedly looked and leaned very slightly toward the card containing the correct
ﬁgure) on the performance of children involved in a concept-attainment task. Their
results Showed that ﬁeld-dependent children tended to do better under this condition
than when the social cue was absent.

In addition, Koran, Snow, and McDonald (1971) examined the impact of
field-dependence and videotaped modeling on the acquisition of teaching skills.
Their results showed that field-dependent teachers were found to beneﬁt Significantly
more from the videotaped modeling treatment than ﬁeld-independent teachers,
whereas the ﬁeld-independent teachers did better, but not signiﬁcantly so, in the
written modeling treatment (subjects read a written script).

In sum, these studies suggest that ﬁeld-dependent individuals are more likely
than ﬁeld-independent individuals to attend to social stimuli and to beneﬁt from
videotaped modeling. In addition, field-dependent individuals tend to have greater
interpersonal skills than field-independent individuals. Based on these findings, it
is predicted that:

H3: There will be two main effects and an interaction such that (1) field-
dependent individuals will have higher performance than ﬁeld-independent
individuals, (2) individuals in the modeling treatment will have higher
performance than those in the no-modeling treatment, and (3) the

relationship between modeling and performance will be greater for ﬁeld-
dependent individuals than field-independent individuals (See Figure 7.).

31

Held-Dependent

Performance

—_

Field-Independent

Training

 

 

No Vldeotaped Vldeotaped
Modeling Modeling

Figure 7. Predicted interaction between ﬁeld-dependence and videotaped
modeling.

Vldeotaped Feedback: An Examination of Personality by Treatment Interactions
Locus of Control. Dweck (1975) and Diener and Dweck (1978) have shown
that children who attribute failure to insufficient effort (i.e., an internal factor), as
opposed to factors outside their control, are less likely to give up on a task after
experiencing repeated failure. In addition, research by Strassberg (1973) has found
that internals tend to have higher expectations for success than externals. Based on
the results of these studies it is suggested that internals, who have a predisposition
to attribute all outcomes (i.e., success and failures) to internal factors, may be more
likely than externals, to respond to negative feedback with increased effort. It is
further suggested that internals, when viewing a videotape of their own performance,
are more likely than externals to increase their effort on a subsequent trial if they

perceive a discrepancy between their actual performance and the standard.

32
Another area of research that seems relevant is research on intrinsic and
extrinsic feedback (Baron, Cowan, Ganz & McDonald, 1974; Baron & Ganz, 1972).
These studies demonstrated that internals performed better on form discrimination
tasks when given intrinsic feedback (i.e., subjects were allowed to discover for
themselves whether their responses were right or wrong) rather than extrinsic
feedback (i.e., the experimenter informed subjects whether or not their responses
were right or wrong). Externals, on the other hand, made more correct responses
under extrinsic feedback conditions. It is suggested that these results may also
generalize to videotaped feedback. That is, internals may respond more favorably
to conditions in which they can observe for themselves the accuracy of their
performance. Externals, on the other hand, may need speciﬁc verbal feedback from
others. Since videotaped feedback, in and of itself, does not include feedback from
an external source, but instead, allows the individual to evaluate his or her
performance for him or herself, it is suggested that videotaped feedback should be

more effective for internals than externals.
In sum, the studies reviewed above suggest that internals will perform better
in situations in which they can discover for themselves the accuracy of their
performance. In addition, internals are more likely than externals to respond to

negative feedback with increased effort. Therefore, it is predicted that:

H4: There will be two main effects and an interaction such that (1) internals will
have higher performance than externals, (2) individuals in the Videotaped
feedback treatment will have higher performance than those in the no-
videotaped feedback treatment, and (3) the relationship between videotaped
feedback and performance will be greater for internals than externals. (See
Figure 8.)

33

Internals

Performance

in ——
Externale
Tralnlng

 

 

No Vldeotaped Vldeotaped
Feedback Feedback

Figure 8. Predicted interaction between locus of control and videotaped feedback.

Field-dependence. As noted earlier, one of the main features of ﬁeld-
dependence-independence is the tendency to rely on either oneself or the external
environment as referents for behavior. Individuals who rely on themselves are said
to have ﬁeld—independent cognitive styles while individuals who rely on external
referents are said to have field-dependent cognitive styles. It was also noted that
field-dependent individuals pay greater attention to social cues, have a greater need
for information from external sources, have greater interpersonal competency, and
beneﬁt more from videotaped modeling than ﬁeld-independent individuals (Witkin
& Goodenough, 1981; Karp, 1977). Thus, it is suggested that ﬁeld-dependent
individuals will be more likely than field-independent individuals to beneﬁt from
information on the appropriateness of their social behavior (i.e., videotaped

feedback). Therefore, it is predicted that:

34

H5: There will be two main effects and an interaction such that (1) ﬁeld-
dependent individuals will have higher performance than ﬁeld-independent
individuals, (2) individuals in the videotaped feedback treatment will have
higher performance than those in the no-videotaped feedback treatment, and
(3) the relationship between videotaped feedback and performance will be
stronger for ﬁeld-dependent individuals than field-independent individuals
(See Figure 9.).

Field-Dependent

Performance

In —-
. . F ieId-lndependent
Training

 

 

No Vldeotaped Vldeotaped
Feedback Feedback

Figure 9. Predicted interaction between field—dependence and videotaped
feedback.

An Examination of the Relationship Between General Mental Ability ('g" , Training
Treatment, and Performance in Training

The hypothesis of general mental ability, in which human individual
differences range widely, was ﬁrst formally proposed by Sir Francis Galton (1869).
L.L. Thurstone, a leading American psychometrician, spent many years trying to
devise tests that he hoped would provide pure measures of a number of supposedly
distinct abilities, such as verbal, numerical, spatial, reasoning, and memory.

However, no matter how refined and homogeneous these various tests were made,

35

they always displayed substantial positive correlations with one another, indicating
that all of these tests measured something in common--a general factor (Jensen,
1986). Galton’s hypothesis of general mental ability was not subject to rigorous
empirical scrutiny until Charles Spearman (1904, 1927) invented factor analysis.
Factor analysis is essentially a class of mathematical techniques for converting a
number of observed variables (e.g., test scores) into a usually much smaller number
of hypothetical variables, called factors, which together represent all or most of the
variance that any of the observed variables have in common. It is possible to factor
analyze the correlations between three or more oblique (i.e., correlated) factors,
thereby yielding one or more higher order factors. The highest order factor at the
apex of the hierarchical factor structure is the general factor, which, following
Spearman, is conventionally labeled g when the observed variables entering into the
factor analysis are scored on a wide variety of tests of mental abilities. Factors
below the general factor in the hierarchy are referred to as group factors, because
their variance is shared by only certain groups of tests. Prominent group factors are
verbal, spatial, and numerical ability.

Earlier, it was suggested that general ability would be unlikely to correlate
differently with performance in alternative treatments since considerable research
evidence shows that correlations between general ability and performance generalize
across a wide range of tasks and situations (Jensen, 1986; Hunter, 1986; Thorndike,
1986). Thus, there is little reason to expect that modeling would interact with "g"
to inﬂuence training outcomes. Instead, it is most likely that there will be a main

effect for "g" such that individuals with higher ability perform better than lower

ability individuals in both the modeling and no-modeling treatment conditions.

36

Based on the modeling research reviewed earlier (Kazdin, 1973, 1974a, 1975, 1976;
Bandura & Menlove, 1968; Baldwin, 1987), one would also expect a main effect for
modeling, such that all individuals (regardless of ability) perform better in the
modeling condition than the no-modeling condition
Thus, it is predicted that:
H6: There will be a main effect for ability and modeling such that high ability

individuals perform better than low ability individuals in both the modeling

and no-modeling treatments and individuals in the modeling treatment
perform better than individuals in the no-modeling treatment (See Figure 10).

Hlah Ablllty

Low Abl lit
Performance y

In

Training

 

 

No Vldeotaped Vldeotaped
Modeling Modeling

Figure 10. Predicted relationship between ' and videotaped modeling.

As was suggested above with regard to modeling, there is little reason to
expect that videotaped feedback will interact with "g" to inﬂuence training outcomes.
Instead, it is most likely that there will be a main effect for "g" such that individuals
with higher ability will perform better than lower ability individuals in both the

videotaped feedback and nO-videotaped feedback treatment conditions In addition,

based on previous research which has demonstrated that Videotaped feedback has

37
a positive impact on learning and behavior change (Speas, 1979; Del Rey, 1978;
Decker, 1983), it is predicted that:

H7: There will be a main effect for ability and videotaped feedback such that high
ability individuals perform better than low ability individuals in both the
videotaped feedback and no-videotaped feedback treatments and individuals
in the videotaped feedback treatment perform better than individuals in the
no-videotaped feedback treatment (See Figure 11).

ngh Ablllty

Low Ability
Performance

in

Tralnlng

 

 

No Vldeotaped Vldeotaped
Feedback Feedback

Figure 1]. Predicted relationship between g and videotaped feedback.

If H

An Examination of the Relationship between Locus of Control, Field-dependence, g
Self-eﬁicacy and Knowledge

Earlier it was noted that while locus of control and field-dependence are
conceptually similar, research has demonstrated that the two constructs are usually
unrelated (Bartelt, 1970; Deever, 1968; Fitz, 1971; Lefcourt et a1, 1973; Lefcourt et
al., 1975 ; Lefcourt & Telegdi, 1971; Roodin et al., 1974; Rotter, 1966; Shapson, 1973;
Tobacyk et al., 1975; Zara, 1970). Field-dependence is a cognitive variable which

decribes an individual’s way of processing information, whereas, locus of control is

38

an attitudinal or motivational variable which describes an individual’s tendency to
attribute the causes of outcomes to either internal or external factors. Given these
differences it is predicted that these two variables, locus of control and ﬁeld-
dependence, will moderate the impact of training treatment on performance through
their impact on different underlying processes. Speciﬁcally, ﬁeld-depndence, a
cognitive/information processing variable, is predicted to inﬂuence knowledge but
not self-efficacy. That is, one’s tendency to rely on oneself or the environment as
referents for behavior is not expected to inﬂuence one’s conﬁdence in one’s ability
to perform a particular behavior (i.e., self-efficacy) but will effect how much
information is learned (i.e., knowledge) from external sources (vidoetaped modeling
and videotaped feedback). Locus of control, an attitudinal/ motivational variable, is
predicted to inﬂuence both self-efficacy and knowledge. This prediction is based
on research which has shown that locus of control is a signiﬁcant predictor of
academic achievement (Brown & Strickland, 1972) and effort-performance
expectancies (Lied & Pritchard, 1976). Therefore, in addition to the direct effects
predicted earlier (i.e., it was predicted that locus of control and ﬁeld-dependence
would have a direct effect on performance in training, see hypotheses 2, 3, 4 and 5),
it is also predicted that:

H8: Internals will demonstrate greater knowledge and self-efficacy than externals,

and

H9: ﬁeld-dependent individuals will exhibit greater knowledge than field-
independent individuals.

Knowledge and self-efficacy may also be related. For example, it’s possible

that the more knowledge an individual has about how to perform a particular task,

 

39
the greater his or her conﬁdence in his or her ability to perform the task. On the
other hand, knowing what to do or how to behave in a particular situation is not the
same as actually doing it. An individual may know what he or she should do in a
particular situation but may still have a low level of conﬁdence in his or her ability
to actually carry out the required behavior.

General mental ability has been found to be a signiﬁcant predictor of
performance in school, college, the armed services training programs, and in
hundreds of different occupations in business, industry, and the civil service
(Jensen,1986; Hunter, 1986). Thus, in addition to having a direct effect on
performance in training, one would expect general mental ability to have a main
effect on knowledge as well. Therefore it is predicted that:

H10: High ability individuals will demonstrate greater knowledge than low ability
individuals.

It is also possible that "g" might inﬂuence self-conﬁdence with high ability
individuals having greater self-conﬁdence than low ability individuals. However, self-
efficacy is a task speciﬁc variable and general mental ability may not necessarily be
related to one’s conﬁdence in one’s ability to perform an interpersonal task.

Finally, it should be noted that previous research that has examined the
relationship between locus of control and "g", and ﬁeld-dependence and "g" has in
most cases found little or no relationship. For example, Rotter (1966) reported that
correlations between locus of control and measures of intelligence have ranged from
.03 to -.22, while Witkin and Goodenough (1981) reported that mean correlations

between field-dependence and vocabulary, and verbal comprehension were .04 and

.14, respectively, and the relationship between ﬁeld-dependence and spatial ability

40
ranged between .30 and .60. These authors concluded that some correlation between
ﬁeld-dependence and general mental ability should be expected given that most
measures of intelligence contain measures of spatial ability.

Summary. The purpose of this study is to examine the main and interactive
effects of videotaped modeling and videotaped feedback on performance in training
and to examine whether "g", locus of control, and ﬁeld-dependence moderate the
effectiveness of these two techniques. It was predicted that videotaped modeling and
videotaped feedback would have significant main effects on performance. In
addition, it was predicted that there would be a signiﬁcant interaction between the
two treatments such that subjects in the no videotaped feedback/no videotaped
modeling condition would have signiﬁcantly lower performance than subjects in any
other condition. With regard to the individual difference variables, it was suggested

that both locus of control and field-dependence would moderate the impact of both
videotaped modeling and videotaped feedback on performance, while "g" would not
interact with either treatment. Finally, it was predicted that locus of control, ﬁeld-
dependence and "g" would all have significant main effects on knowledge and
performance in training, while only locus of control would have a significant main
effect on self-efficacy. A process model depicting these predicted relationships is
shown in Figure 12.

While it is possible that locus of control and field-dependence may interact
with both treatment variables, or, with each other and one or both of the training
treatment variables, these three and four-way interactions are very difﬁcult to

predict. Therefore, it is the intent of this study to explore these relationships but no

Speciﬁc predictions will be made.

41

 

 

 

Plaid-dependence

 

 

 

Vldeotaped
Modeling

 

 

 

 

Vldeotaped
Feedback

 

I

A Knowledge

 

  

 

 

 

 

 

 

Self-efficacy

it

 

 

 

 

 

l

 

 

Locus of Control

 

 

 

 

 

 

 

Performance
In
Tralnlng

/

 

 

 

Figure 12. A process model of the relationship between videotaped modeling,

H H

videotaped feedback, locus of control, ﬁeld-dependence, g and performance in

training.

CHAPTER 2. METHOD

Overview

This study utilized a 2 x 2 between subjects design. The first factor,
videotaped modeling consisted of two levels: with videotaped modeling and without
videotaped modeling. The second factor, videotaped feedback also consisted of two
levels: with videotaped feedback and without videotaped feedback. A
summarization of these treatment conditions is shown in Figure 13. This study also
examined the impact of three additional independent variables including locus of

control, field-dependence and g .

Videotaped Modeling

With Without

 

With 1 2

Vldeotaped
Feedback

 

Without 3 4

 

 

 

 

Figure 13. Training treatment conditions.

42

 

43

Subjects in all four training treatment groups received the same training
content. The training content used in this research study was "How to give
constructive negative feedback." This topic was chosen because previous research
has found that there is a fairly low baseline rate of accurate behavior without prior
training (Hymowitz, 1985). A pilot study of the subject population (college juniors
and seniors, N = 75) revealed that most subjects reported moderate self-efficacy in
their ability to give constructive negative feedback. Two measures of self-efﬁcacy
were used in the pilot study. In the ﬁrst measure subjects rated how certain they
were that they could give constructive negative feedback in 3 situations using a scale
ranging from 0% (not certain at all) to 100% (absolutely certain). The mean for this
measure was 70% (sd = 7%). The second measure consisted of a 5 item scale
similar to that used by Hollenbeck and Brief (1987). Responses were measured
using a 5-point Likert scale ranging from strongly disagree (1) to strongly agree (5).
The mean for the second measure was 17.44 (sd = 2.87).

Subjects

Subjects in this study were 194 juniors and seniors enrolled in introductory
management courses. All subjects received some minimal course credit for their
participation. Thirteen subjects had to be eliminated due to missing data (inaudible
videotapes). Of the remaining 181 subjects, forty-six percent of the subjects were
females (N = 84) and fifty-four percent were males (N = 97). The mean age was
21.97 (S_D = 2.8). Subjects were randomly assigned to one of the four treatment
conditions. The final sample of 181 subjects were distributed across the four
treatment conditions as follows: 42 subjects in condition 1, 46 in condition 2, 48 in

condition 3, and 45 in condition 4.

44

In line with Cohen and Cohen’s (1983) recommendations, an analysis was
conducted to determine the appropriate sample size needed to detect signiﬁcance.
Since the purpose of this study was to examine interactions between personality and
training treatment, the primary statistic of interest is sr’, or the percent of variance
accounted for by the interaction term. In addition to estimating the effect Size for
the interaction term, it is necessary to estimate R2, or the amount of variance
accounted for by the complete regression equation. Thus, a literature search was
conducted to identify effect sizes for each of the major variables examined in this
study. Koran, et al., ( 1971) reported an effect size of sr2 = .05 for the interaction
between ﬁeld-dependence and videotaped modeling, thus, .05 will be used as an
estimate for the interaction term in the present study. Baumgartel et al., (1984)
reported a significant main effect for locus of control (er = .05) such that internals
reported greater effort and success in applying new knowledge learned in a one week
management training program. A meta analysis by Burke and Day (1986) reported
an effect size of sr2 = .11 for videotaped modeling. The average effect size for
videotaped feedback in the three training studies reviewed earlier was sr’ = .14
(Decker, 1983; Del Rey, 1978; Walter, 1975). Finally, based on the results of a
recent training study by Karl, O’Ieary and Martocchio (1990) it is estimated that
pro-training feedback skills (as measured by one’s performance in a pro-training role
play) will account for approximately 25 percent of the variance in post-training
feedback skills. The number of independent variables used in this power analysis
was thirteen (1 = pre-training role play performance, 2 = videotaped modeling, 3
= videotaped feedback, 4 = videotaped feedback x videotaped modeling, 5 = locus

of control, 6 = field-dependence, 7 = locus of control x videotaped modeling, 8 =

45

locus of control x videotaped feedback, 9 = field-dependence x videotaped modeling,
10 = ﬁeld-dependence x videotaped feedback, 11 = self-efficacy, 12 = knowledge,
13 = "g"). In sum, assuming that the increment in explained variance for the
interaction term is .05, in a complete regression equation that explains a large
amount of variance (R2 = .50, a conservative estimate based on the effect sizes
reported above), the resulting sample size of 181 subjects provides power of .76 at
an alpha level of .05 to test the major hypotheses.

Training Treatment Conditions

All four training treatment groups received training on how to give
constructive negative feedback. The training lasted approximately 1 hour for all
groups. The four treatment conditions to used were: (1) videotaped modeling with
videotaped feedback, (2) videotaped modeling without videotaped feedback, (3) no
videotaped modeling with videotaped feedback, (4) no videotaped modeling without
videotaped feedback. Each of these is described below under the following
headings: videotaped modeling, no videotaped modeling, videotaped feedback, and
no videotaped feedback.

Vldeotaped modeling. The "with videotaped modeling" treatment conditions
(Conditions 1 and 3) were conducted in a manner similar to the videotaped
modeling component of a typical behavior videotaped modeling program: (a) a
videotaped introduction of the topic by the trainer, (b) presentation and discussion
of the underlying principles (i.e., learning points, See Appendix A.), and (c)
presentation of the ﬁlmed models.

The videotaped modeling stimuli used in this study consisted of videotaped

role plays of a supervisor giving feedback to a subordinate. Two different scenarios

46

were used. In the first scenario, Doug, the supervisor, talks with Jon, the
subordinate about a cost overrun problem on a recent project. In the second
scenario, Jim, the supervisor, talks with Darrell, the subordinate, about a chauvinistic
comment he made to a female coworker. Each scenario has two forms: a good
example of constructive negative feedback behavior and a poor example of negative
feedback behavior. The scripts used in these scenarios can be found in Appendix
B.

No Videotaped modeling. In the "without videotaped modeling" treatment
conditions (Conditions 2 and 4), subjects received a videotaped introduction of the
topic by the trainer and a presentation and discussion of the underlying principles
(learning points). To ensure that the "without videotaped modeling" conditions were
equal in length to the "with videotaped modeling" conditions, subjects in the "without
videotaped modeling" conditions were asked to study the learning points for
approximately 10 minutes.

Vldeotaped Feedback. In the "with videotaped feedback" conditions
(Conditions 1 and 2), subjects practiced applying the learning points in a role play
with a confederate. All role plays were videotaped and each subject viewed his or
her own videotape at the conclusion of the role play. Subjects were also asked to
rate their own performance in the role play using a 14-item behavioral rating scale.
A description of the role play is included in Appendix C.

No Vldeotaped Feedback. In the "without videotaped feedback" conditions
(Conditions 3 and 4), subjects practiced applying the learning points in a role play
with a confederate. Subjects were also asked to rate their own performance in the

role play using a 14-item behavioral rating scale. To ensure that the "without

47
videotaped feedback" conditions was equal in length to the "with videotaped
feedback" conditions, subjects in the "without videotaped feedback" conditions were
asked to study the learning points for approximately 5 minutes.
Measures (See Appendix D)

Seven variables were measured in this study: (a) background and
demographics, (b) "g", (c) locus of control, (d) field-dependence, (e) performance,
(f) knowledge of learning points, and (g) self-efficacy. Each of these is described
below under the following subheadings: individual difference measures, dependent
measure, and mediating variables.

Individual Diﬁerence Measures

Background and Demographics. Age, sex, class level, supervisory experience,
and experience in giving feedback constituted the demographic data.

"g”. Generaly mental ability was measured using the Wonderlic Personnel
Test. The Wonderlic Personnel is a 12 minute test consisting of 50 items. The
Kuder Richardson KR-20 reported in the manual (Wonderlic, 1973) is .88.

Locus of Control. Locus of control was measured using Rotter’s (1966)
Internal-external Locus of Control Scale. The scale consists of 29 question pairs (6
items are fillers), using a force-choice format. One point is given for each external
statement selected. Scores can range from zero (most internal) to 23 (most
external). Rotter (1966) obtained an internal consistency coefficient (Kuder-
Richardson) of .70 from a sample of 400 college students.

Field-dependence. Field-dependence was measured using the Short form of
the Group Embedded Figures Test (GEFT)(Jackson, 1956). The short form consists

of 12 patterns in which are "embedded" Specific figures which the individual must

48

find and trace. There is a 3-minute time limit for each pattern. An individual’s total
score is computed by summing the total seconds required to locate all 12 ﬁgures.
Jackson (1956) found that the correlation between the 12-item scale used in this
study and the original 24-item scale (Witkin, Dyk, Paterson, Goodenough, & Karp,
1962) correlated .96 for men and .97 for women. Karp (1977) reported that the
original 24-item GEFT has shown consistently high correlations with other measures
of ﬁeld-dependence. Witkin et al. (1962) reported a test-retest reliability of .89.
Dependent Measure

Performance. The performance measure consisted of a role play in which
each subject had to play the role of a supervisor who was required to give negative
feedback to a subordinate (i.e., a confederate who was trained to follow a script).
All role plays were videotaped and rated by two trained raters using a 14-item
behavioral rating scale. Specifically, both raters were given a one hour training
session that included a discussion of the learning points, a discussion of the behaviors
exhibited in the modeling tapes, and a detailed description of key behaviors to look
for. Raters were blind to treatments. The behavioral rating scale consisted of items
derived from the learning points. For example, sample items included: "stated the

purpose of the meeting early in the session, avoided general evaluative statements,"
and asked for and listened openly to the employee’s reasons for the behavior."
Responses were measured on a 5-point scale ranging from outstanding use of the
skill (5) to very poor use of the skill (1).

Mediating Variables

While the major purpose of this study was to examine the interaction between

individual differences and the videotaped modeling and videotaped feedback

49
treatments, this study also examined the process by which videotaped modeling and
videotaped feedback inﬂuence performance in training. According to the theoretical
analysis discussed earlier, videotaped modeling and videotaped feedback inﬂuence
performance indirectly through their impact on self-efficacy and task-related
knowledge. Therefore, a measure of self-efficacy and knowledge was also
administered. Each of these measures is described below.

Knowledge. The knowledge measure consisted of three paper and pencil
tests. The ﬁrst test consisted of 10 items. For each item, subjects indicated whether
they felt the item was an appropriate or inappropriate example of constructive
feedback behavior. In addition, they were asked to explain why they felt a particular
item was inappropriate. On the second test subjects were asked to write how they
would handle a particular feedback situation, including: what they would say and
in what order they would say it. On the third test subjects were asked to list as
many of the learning points as they could remember. All tests were scored by the
researcher using the keys found in Appendix D.

Self-efﬁcacy. Self-efﬁcacy was measured using two formats. Format A was
based on Bandura’s (1982) conceptualization of self-efficacy and consisted of ﬁve
scenarios involving a supervisor who must give negative feedback to a subordinate.
For each scenario, subjects were asked to indicate: (a) whether they feel they can
give the feedback described in the scenario in such a way that it would increase the
subordinate’s motivation and desire to improve (i.e., magnitude, measured as the
total number of yes’s), and (b) how certain they were that they could give the
feedback (i.e., strength, measured as the sum of all certainty values). The certainty

scale ranged from 0 to 100. Verbal descriptors occured at the following points: 0

50

= not certain at all, 25 = slightly certain, 50 = moderately certain, 75 = highly
certain, and 100 = absolutely certain. Since the Bandura-type measure of self-
efﬁcacy tends to have a low internal consistency reliability (e.g., Taylor et al., 1984
reported an internal consistency reliability of a = .60) a second measure was
developed. Format B consisted of a 7-item scale similar to that used by Hollenbeck
and Brief (1987). Responses were measured using a 5-point Likert scale ranging
from strongly disagree to strongly agree.

Procedure

Subjects were asked to Sign up for one of thirty-six training sessions with six
subjects per session. Training treatments were randomly distributed across sessions.
Due to imperfect attendence, an additional eight sessions were added, resulting in
a total of 44 training sessions. Subjects were trained in small groups of 2 to 6
people each. The training sessions and the administration of the pre and post
measures lasted approximately 2 hours and 45 minutes.

A total of nine confederates participated in this study. Each confederate was
given a two hour training session which included a discussion of the training content,
a discussion of appropriate and inappropriate role play behaviors and several
practice role plays in which confederates paired off with one another to practice
each of the three role plays used in the training. All practice role plays were
monitored by the researcher to ensure that each confederate was carrying out his or
her role as intended. Confederates were also taught how to administer the
Embedded Figures Test.

All conditions were conducted as follows. First, subjects in all conditions

were given 60 minutes to complete the pre-training paper and pencil measures (i.e.,

51

demographic measure, locus of control, field-dependence, Wonderlic). Next they
were given 5 minutes to review the pre—training behavioral role play and 10 minutes
to perform the role play with a trained confederates. All role plays were vidotaped.
Next subjects participated in their assigned treatment conditions. At the conclusion
of the training session, subjects completed the post training paper and pencil
measures (i.e., knowledge and self-efficacy A & B). Finally, subjects were given 5
minutes to review the post training behavioral role play, and 10 minutes to perform
the role play with a trained confederate. All role plays were videotaped. A
summarization of this procedure is included in Table 1.

Table 1
Summarization of Procedure

PRE-TRAINING MEASURES

1. Paper and Pencil Measures (60 minutes)

Demographics
Locus of control
Field-dependence
Wonderlic

FL? 9"!”

2. Pre-training Behavioral Role Play (15 minutes)
TRAINING TREATMENT (1 hour)

Introduction to topic

Presentation and discussion of learning points
Videotaped modeling (Conditions 1 and 3 only)
Practice role play

Videotaped feedback (Conditions 1 and 2 only)
Self-ratings

POST TRAINING MEASURES

.O‘SAPP’NI"

1. Paper and Pencil Measures (15 minutes)

a. Knowledge
b. Self-efﬁcacy

2. Post training Behavioral Role Play (15 minutes)

 

CHAPTER 3. RESULTS

Scale Reliabilities

Individual Difference Variables. The internal consistency reliabilities for the
individual difference measures were as follows: "g" (a = .68), locus of control (a =
.74), ﬁeld-dependence (a = .84).

Mediating Variables. Since Bandura’s two types of self-efficacy items (strength
and magnitude) were highly correlated (r = .66, p<.001), all ten items were
standardized to eliminate differences in response format and summed to form a
single measure of self-efficacy (a: .71). Cronbach’s alpha for the 7-item Likert-type
measure of self-efficacy was (a = .83). Since the Bandura-type measure of self-
efﬁcacy is a more direct test of Bandura’s self-efficacy theory and since Cronbach’s
alpha for the Bandura-type measure was sufﬁciently high, the second measure (i.e.,
format B) was dropped from further analyses. Internal consistency reliabilities for
the three knowledge tests were .51 for test A, .57 for test B, and .58 for test C.
The intercorrelations between tests were as follows: r,,,, = .03, rBC = .12, and rAc = .23.
Due to the extremely low scores found on test B (the average number of correct
answers was 4.81 (sd= 1.96) out of 11), the greater degree of subjectivity involved
in grading this test, and the fact that performance on test B was uncorrelated with
general mental ability (r = -.03, us), it was decided to eliminate test B from further

analyses. Since test A and C were related to each other (rAC = .23, p < .001) and

52

53

to general mental ability (r ”Mpg. = .10, p < .10, r MC, .3. = .28, p < .001) test A and
C were combined to form one single measure of knowledge (a=.65).

Dependent Measure. Inter-rater reliability for the rating of pre and post
training role play performance were (r = .84) and (r = .71), respectively. The
average of the two rater’s ratings were used as the ﬁnal measure of pre- and post
training role play performance. Cronbach’s alpha for these measures were .72 (pre-
training) and .77 (post training).

Comparison of Treatment Groups and Confederates.

The four treatment groups did not differ on any of the independent variables
including locus of control (F = .86, ns), "g" (F = .24, ns), and ﬁeld-dependence (F
= 1.28, ns), nor on any of the following demographic variables: sex (F = 1.74, ns),
age (F = .20, ns), supervisor experience (F = 1.31, ns), negative feedback experience
(F = .49, ns), and grade point average (F = 1.02, ns). A signiﬁcant difference
between conditions was found for class level (F = 7.81, p = .001), such that
conditions 2 and 3 had significantly more seniors than condition 1. Since class level
was not significantly related to any of the independent or dependent variables
examined in this study, with the exception of "g" (r = -.14, p < .05), this difference
was not considered problematic and will not be considered in subsequent analyses.

A comparison of means across the nine confederates was conducted to
determine if the confederate had any significant impact on role play performance.
An analysis of variance revealed no significant difference among confederates for
either the pre-training role play (F = 1.75, ns) or the post training role play (F =

1.87, ns).

54

Preliminary Analyses

Means, standard deviations, internal consistency reliabilities and
intercorrelations among all variables are shown in Table 2. Correlations among the
individual difference variables were signiﬁcant but low. Specifically, the correlation
between "g" and locus of control was (r = -.18, p < .01) indicating that internals
tend to have greater intelligence than externals. The correlation between ﬁeld—
dependence and "g" was (r = -.18, p < .01) indicating that ﬁeld-independent
individuals tend to have greater intelligence than ﬁeld-dependent individuals. No
Signiﬁcant relationship was found between locus of control and ﬁeld-dependence (r
= .12, ns), indicating that internals are not more likely to be ﬁeld-independent than
dependent, nor are externals more likely to be ﬁeld-dependent than field-
independent
Table 2

Means, standard deviations, intemal consistency reliabilities“ and intercorrelations among
all variables.

 

 

 

Variable M SD 1 2 3 4 5 6 7 8 9
1. Videotaped
Modeling)
2. Videotaped
Feedbackb
3. ”g" 23.85 4.12 -.05 .03 (.68)
4. Locus of Control 9.45 3.90 -.02 .10 -.18“ (.74)
5. Field-dependence 502.65 280.08 .14‘ -.03 -.18‘" .12 (.84)
6. Self-efﬁcacy (A) 0.00 5.55 .01 .08 .16“ -.02 -.O7 (.71)
7. Knowledge 28.94 351 -.06 .05 .2 " -.04 -.17“' .20" (.65)

8. Pro-training role
play performance 41.55 6.11 -.16‘ .09 .01 .00 -.04 .17' .06 (.72)

9. Post training role
play performance 54.34 6.63 .25‘” .07 .14“ .05 —.04 .33’” .32’” 27*” (.77)

 

aInternal consistency reliabilities are in the diagonal.
ideotaped modeling and videotaped feedback are dichotomous variables coded 0 = without, 1 = with.
O
p < .05.
” p < .01.
‘" p < .001.

55

Hypothesis 1

Hypothesis 1 predicted a main effect for videotaped modeling and videotaped
feedback and a signiﬁcant interaction such that subjects in the combined treatment
condition would have signiﬁcantly greater performance than subjects in any other
condition and subjects in the no videotaped feedback/ no videotaped modeling
(control) condition would have signiﬁcantly lower performance than subjects in any
other condition. This hypothesis was tested using hierarchical moderated regression
analysis in which post training role play performance was regressed on: (1) pre-
training role play performance (PRE-TR PERF), (2) videotaped modeling (VM), (3)
videotaped feedback (VF), and (4) the interaction between videotaped modeling and
videotaped feedback (VMVF). The results are shown in Table 3.
Table 3

Regression Results for the Impact of Vldeotaped Modeling and Videotaped Feedback
on Post Training Role Play Performance.

 

 

 

Step Variable R R2 A R2
1. Pre-training Role Play Performance .274 .075 .075***
2. Videotaped Modeling .406 165 090*“
3. Videotaped Feedback .410 .168 .003
4. Videotaped Modeling x Videotaped Feedback .437 .191 .023*
* p < .05.
*** p < .001.

As predicted, videotaped modeling had a Significant impact on post training
role play performance such that those subjects who received videotaped modeling
showed significantly greater improvements in role play performance than those who

did not receive videotaped modeling. The interaction between videotaped feedback

56
and videotaped modeling was also signiﬁcant (A R2 = .02, p < .05). N 0 main effect
was found for videotaped feedback.1 Thus, hypothesis 1 was only partially supported.
The interaction between videotaped modeling and videotaped feedback is shown in

Figure 14.

 

 

68
Videotaped
57 Modeling
Performance 53
In 55
Tralnlng 54
\ NO VIdBOIaped
‘3 Modeling
52
No Videotaped Videotaped

Feedback Feedback

Figure 14. InteractionAbetween videotaped modeling and videotaped feedback.
(Regression equation: Y = .36 ( PRE-TR PERF) + 2.0 (VM) - 1.26 (VF) + 3.99
(VMVF) + 38.1)

 

1One possible explanation as to why videotaped feedback had no main effect on post training role
play performance is that videotaped feedback may have had a negative impact on the performance of
some subjects and a positive impact on the performance of others. Observing oneself perform poorly
at a task may lower self-efﬁcacy and subsequent performance. On the other hand, observing oneself
perform poorly may create self-dissatisfactions that serve as motivational inducements for enhanced
effort. An alternative explanation as to why videotaped feedback had no main effect is that subjects
were not able to make accurate evaluations of their own performance. A post hoc analysis examining
these alternative explanations is presented in Appendix E.

 

 

 

57
Post hoc comparisons using the Fisher test (Keppel, 1982) revealed that subjects
in the combined treatment condition including both modeling and videotaped
feedback had greater post training performance than either treatment alone.
However, contrary to what was predicted, subjects in the control group did not
perform significantly worse than all other groups. Means, standard deviations and
post hoc comparisons by experimental condition for pre-training role play

performance, post training performance and performance change are shown in Table

 

 

4.

Table 4

Means, Standard Deviations and Post Hoc Comparisons " by Experimental Condition

Pre-Training Post Training Performance Change

Condition M SD M SD M SD

1. Control 41.45’l 4.91 52.951’ 5.61 11.30‘ 6.60

2. Videotaped Modeling 40.598 5.30 54.65a 7.54 14.07b 7.87

3. Videotaped Feedback 43.488 6.82 52.421’ 6.48 8.94“ 6.35

4. Videotaped Modeling +
Videotaped Feedback 40.582’ 6.77 57.38b 5.65 16.80c 7.66

 

‘ Comparisons among the 4 conditions were tested using the Fisher Test at the .05 level. Means
sharing common subscripts are not signiﬁcantly different.

Hypothesis 2

Hypothesis 2 predicted a main effect for locus of control and videotaped
modeling and a significant interaction such that the relationship between modeling
and performance would be greater for internals than externals. This hypothesis was
tested using hierarchical moderated regression analysis in which post training role

play performance was regressed on: (1) pre-training role play performance, (2)

 

 

58
videotaped modeling, (3) locus of control (LOC), and (4) the interaction between
videotaped modeling and locus of control (VMLOC). The results are shown in

Table 5.

Table 5

Regression Results for the Impact of Vldeotaped Modeling and Locus of Control on
Post Training Role Play Performance

 

 

Step Variable R R2 A R2
1. Pro-training Role Play Performance .271 .073 .075**"'
2. Videotaped Modeling .397 .157 084*”
3. Locus of Control .400 .160 .003
4. Videotaped Modeling x Locus of Control .424 .180 .020“
* p < .05.
*** p < .001.

As predicted, videotaped modeling had a signiﬁcant impact on post training
role play performance such that those subjects who received videotaped modeling
showed signiﬁcantly greater improvements in role play performance than those who
did not receive videotaped modeling. No main effect was found for locus of control.
However, the interaction between videotaped modeling and locus of control
explained a signiﬁcant amount of variance in performance (A R2 = .02, p < .05). This
interaction is displayed in Figure 15. Contrary to what was predicted the
relationship between videotaped modeling and performance was greater for externals

than internals.

 

 

 

59

Externale

Performance

In 66 Internals

Tralnlng

 

 

No Vldeotaped Vldeotaped
Modeling Modeling

Figure 15. InteractionA between videotaped modeling and locus of control.
(Regression equation: Y = .35 (PRE-TR PERF) - .58 (VM) - .13 (LOC) + .47
(VMLOC) + 39.0.)

Hypothesis 3

Hypothesis 3 predicted a main effect for ﬁeld-dependence and videotaped
modeling and a signiﬁcant interaction such that the relationship between modeling
and performance would be greater for ﬁeld-dependent individuals than ﬁeld-
independent individuals. This hypothesis was tested using hierarchical moderated
regression analysis in which post training role play performance was regressed on:
(1) pre-training role play performance, (2) videotaped modeling, (3) ﬁeld-
dependence, and (4) the interaction between videotaped modeling and ﬁeld-
dependence. As predicted, videotaped modeling had a signiﬁcant positive impact on

post training role play performance, however no signiﬁcant effects were found for

60
field-dependence or the interaction between field-dependence and videotaped

modeling. These results are shown in Table 6.

Table 6
Regression Results for the Impact of Videotaped Modeling and Field-dependence on
Post Training Role Play Performance

 

 

 

Step Variable R R2 A R2

1. Pre-training Role Play Performance .274 .075 .075***

2. Videotaped Modeling .406 .165 .090***

3. Field-dependence .412 .170 .005

4. Videotaped Modeling x Field-dependence .413 .170 .000
*** p < .001.

Hypothesis 4

Hypothesis 4 predicted a main effect for locus of control and videotaped
feedback and a significant interaction such that the relationship between videotaped
feedback and performance would be greater for internals than externals. This
hypothesis was tested using hierarchical moderated regression analysis in which post
training role play performance was regressed on: ( 1) pre-training role play
performance, (2) videotaped feedback, (3) locus of control, and (4) the interaction
between videotaped feedback and locus of control. Contrary to what was predicted,
no significant effects were found for either videotaped feedback, locus of control or
the interaction between videotaped feedback and locus of control. These results are

shown in Table 7.

61

Table 7
Regression Results for the Impact of Videotaped Feedback and Locus of Control on
Post Training Performance

 

 

 

Step Variable R R2 A R2

1. Pro-training Role Play Performance .271 .073 073*“

2. Videotaped Feedback .275 .076 .003

3. Locus of Control .278 .078 .002

4. Videotaped Feedback x Locus of Control .284 .081 .003
*** p < .001.

Hypothesis 5

Hypothesis 5 predicted a main effect for field-dependence and videotaped
feedback and a significant interaction such that the relationship between videotaped
feedback and performance would be greater for ﬁeld—dependent individuals than
field-independent individuals. This hypothesis was tested using hierarchical
moderated regression analysis in which post training role play performance was
regressed on: (1) pre-training role play performance, (2) videotaped feedback, (3)
ﬁeld-dependence, and (4) the interaction between videotaped feedback and ﬁeld-
dependence. Contrary to what was predicted, no signiﬁcant effects were found for
either videotaped feedback, field-dependence or the interaction between videotaped

feedback and field-dependence. These results are shown in Table 8.

62

Table 8

Regression Results for the Impact of Videotaped Feedback and F ield-dependence on
Post Training Role Play Performance

 

 

Step Variable R R2 A R2

1. Pro-training Role Play Performance .274 .075 .075***

2. Videotaped Feedback .278 .077 .002

3. Field-dependence .280 .078 .001

4. Videotaped Feedback x Field-dependence .289 .083 .005
*** p < .001.

Hypothesis 6

Hypothesis 6 predicted a main effect for ability and videotaped modeling and
no interaction. The results of a hierarchical moderated regression analysis in which
post training role play performance was regressed on: (1) pre-training role play
performance, (2) videotaped modeling, (3) "g", and (4) the interaction between
videotaped modeling and "g" is shown in Table 9. As predicted, both videotaped
modeling and "g" had a significant impact on post training role play performance,

and the interaction between "g" and videotaped modeling was not signiﬁcant.

63

Table 9

Regression Results for the Impact of Videotaped Modeling and 'g" on Post Training Role
Play Performance

 

 

SE) Variable R R2 A R2
1. Pro-training Role Play Performance .273 .074 074*"
2. Videotaped Modeling .404 .164 110*”
3- "g" .433 .188 .0247
4. Videotaped Modeling x "g" .434 .188 .000
* p < .05.
*** p < .001.

Hypothesis 7

Hypothesis 7 predicted a main effect for ability and videotaped feedback and
no interaction. The results of a hierarchical moderated regression analysis in which
post training role play performance was regressed on: (1) pre-training role play
performance, (2) videotaped feedback, (3) "g", and (4) the interaction between
videotaped feedback and "g" is shown in Table 10. As predicted, the interaction
between "g" and videotaped feedback was not significant. However, contrary to what
was predicted, no signiﬁcant effect was found for videotaped feedback, and the main

effect for "g" was only marginally signiﬁcant (A R2 = .018, p = .07).

64

Table 10
Regression Results for the Impact of Videotaped Feedback and "g” on Post Training
Role Play Performance

 

 

 

Step Variable R R2 A R2
1. Pro-training Role Play Performance .274 .075 .075***
2. Videotaped Feedback .278 .077 .002
3. "g" .308 .095 .018
4. Videotaped Feedback x "g" .325 .106 .011
* p < .05.
*** p < .001.

Hypotheses 8, 9 and 10

Hypothesis 8 predicted a main effect for locus of control such that internals
would demonstrate greater self-efﬁcacy and greater knowledge than externals.
Neither the correlation between locus of control and self-efficacy (r = -.02, ns), nor
the correlation between locus of control and knowledge were signiﬁcant (r = -.03,
ns), thus hypothesis 8 was not supported. Hypothesis 9 predicted a main effect ﬁeld-
dependence such that field-dependent individuals would demonstrate greater
knowledge than field-independent individuals. The correlation between field-
dependence and knowledge was significant but in the opposite direction (r = -.19,
p < .01). Hypothesis 10 predicted a main effect for "g" such that high ability
individuals would demonstrate greater knowledge than low ability individuals. The

correlation between g and knowledge was signiﬁcant (r = .25, p < .001) thus,

hypothesis 10 was supported.

65

Process Model

In addition to testing the ten hypotheses discussed earlier, this study also
examined the underlying process by which videotaped modeling and videotaped
feedback interact with individual differences. It was suggested that locus of control
and ﬁeld-dependence would moderate the impact of training treatment on
performance through their impact on self-efficacy and knowledge. More speciﬁcally,
ﬁeld-dependence, a cognitive/information processing variable, was predicted to
inﬂuence knowledge but not self-efﬁcacy, and locus of control, an
attitudinal/motivational variable, was predicted to inﬂuence both self-efﬁcacy and
knowledge. An analysis of these underlying processes was conducted using two
hierarchical moderated regression equations. In the ﬁrst equation, knowledge was
regressed on (1) videotaped modeling, (2) videotaped feedback, (3) the interaction
between Videotaped modeling and videotaped feedback, (4) field-dependence, (5)
locus of control, (6) the interaction between ﬁeld-dependence and videotaped
modeling, (7) the interaction between field-dependence and videotaped feedback, (8)
the interaction between locus of control and videotaped modeling, and (9) the
interaction between locus of control and videotaped feedback. In the second
equation, self-efficacy was regressed on (1) videotaped modeling, (2) videotaped
feedback, (3) the interaction between videotaped modeling and videotaped feedback,
(4) locus of control, (5) the interaction between locus of control and videotaped
modeling, and (6) the interaction between locus of control and videotaped feedback.

These results are shown in Table 11 and Table 12.

66

Table 11
Regression Results for the Impact of Videotaped Modeling, Vldeotaped Feedback and
F ield-dependence on Post Training Knowledge

 

 

 

Step Variable R R2 A R2
1. Videotaped Modeling .068 .005 .005
2. Videotaped Feedback .078 .006 .001
3. Videotaped Modeling x Videotaped Feedback .191 .036 .030*
4. Field-dependence .252 .064 .028*
5. Locus of Control .255 .065 .001
6. Field-dependence x Videotaped Modeling .263 .069 .004
7. Field-dependence x Videotaped Feedback .265 .070 .001
8. Locus of Control x Videotaped Modeling .266 .071 .001
9. Locus of Control x Videotaped Feedback .277 .077 .006
* p < .05.
Table 12

Regression Results for the Impact of Vldeotaped Modeling, Vldeotaped Feedback and
Locus of Control on Post Training Self-efﬁcacy.

 

 

 

Step Variable R R2 A R2
1. Videotaped Modeling .014 .000 .000
2. Videotaped Feedback .087 .008 .008
3. Videotaped Modeling x Videotaped Feedback .142 .020 .012
4. Locus of Control .148 .022 .002
5. Locus of Control x Videotaped Modeling .166 .028 .006
6. Locus of Control x Videotaped Feedback .239 .057 .029*
* p < .05.

**p < .01.

67
Neither videotaped modeling nor videotaped feedback had a signiﬁcant effect
on post training knowledge. There was a signiﬁcant interaction between videotaped
modeling and videotaped feedback and a main effect for ﬁeld-dependence.
However, contrary to what was predicted, ﬁeld-independent subjects exhibited
greater knowledge than ﬁeld-dependent subjects and subjects in the combined
treatment group exhibited signiﬁcantly lower post training knowledge than subjects

in any other group. These results are shown in Figure 16.

 

 

VM
29
VF
28.6
Control
Post 23
. . 27.5
Tralnlng /
27
Knowledge W I VF
26.5
26
25.6
26
Field-dependent Field-independent

Figure 16. Main effect and interaction for post training knowledge. (Regression
equation: 2 = 2.2 (VM) + 2.36 (VF) - 2.57 (VMVF) - .001 (FD) +.06 (LOC) -
.0015 (VMFD) + .001 (VFFD) -.05 (VMLC) - .14 (VFLC) + 27.47.

68

With regard to the regression result for post training self-efﬁcacy, neither
videotaped modeling, videotaped feedback, nor the interaction between videotaped
modeling and videotaped feedback had a significant impact on post training self-
efficacy. In addition, the interaction between locus of control and videotaped
modeling was not significant. The increase in R2 for the interaction between locus
of control and videotaped feedback was significant (A R2 = .029, p < .05), however,
the R2 for the complete regression equation was not (F = 1.65, ns).

A final set of analyses was conducted to examine the impact of the mediating
variables on the dependent variable and, to examine the impact of the independent
variables on the dependent variables controlling for the mediating variables. In the
first equation post training role play performance was regressed on knowledge and
self-efficacy controlling for pre-training role play performance. In the second
equation post training role play performance was regressed on: (1) pre-training role
play performance, (2) knowledge, (3) self-efficacy, (4) videotaped modeling, (5)
videotaped feedback, (6) the interaction between videotaped modeling and
videotaped feedback, (7) locus of control, (8) field-dependence, (9) "g’", (10) the
interaction between videotaped modeling and locus of control, (11) the interaction
between videotaped feedback and locus of control, (12) the interaction between
videotaped modeling and field-dependence, and (13) the interaction between
videotaped feedback and field-dependence. The results of these analyses are shown

in Table 13 and Table 14.

69

Table 13
Regression Results for the Impact of Knowledge and Self-efﬁcacy on Post Training Role
Play Performance.

 

 

Step Variable R R2 A R2
1. Pre-training Role Play Performance .231 .053 .053"
2. Knowledge .383 .146 085*"
3. Self-efﬁcacy .486 .236 090""
* p < .05.
** p < .01.
*** p < .001.

The results shown in Table 13 indicate that both knowledge and self-efficacy
explained a significant amount of variance in post-training role play performance.
However, further analysis revealed that videotaped modeling, the interaction
between videotaped modeling and videotaped feedback, and the interaction between
videotaped modeling and locus of control explained a signiﬁcant amount of variance
in post training role play performance over and above that explained by post training
knowledge and post training self-efficacy. Thus, knowledge and self-efficacy do not
appear to mediate the relationship between training treatment and post training

performance. See Table 14.

70

 

 

Table 14

Regression Results for Process Model

Step Variable R R2 A R2

1. Pre—training role play performance .229 .052 052*"
2. Knowledge .430 .185 .133"'**
3. Self-efﬁcacy .494 .244 059*”
4. Videotaped Modeling .566 .321 077*“
5. Videotaped Feedback .570 .325 .004

6. Videotaped Modeling x Videotaped Feedback .608 .370 045*"
7. Locus of Control .610 .372 .002

8. Field-dependence .611 .373 .001

9. "g" .612 .374 .001
10. Locus of Control x Videotaped Modeling .640 .410 .0 **
11. Locus of Control x Videotaped Feedback .640 .410 .000
12. Field-dependence x Videotaped Modeling .642 .412 .002
13. Field-dependence x Videotaped Feedback .642 .412 .000

 

Mp < .01.
***p < .001.

 

 

CHAPTER 4. DISCUSSION

Overview

The purpose of this research was to examine the separate and combined
effects of videotaped modeling and videotaped feedback on performance in training
and to examine possible individual difference variables that may inﬂuence the
effectiveness of these two techniques. In addition, this research presented and tested
a theoretical model of the processes underlying the effects of videotaped modeling
and videotaped feedback. Overall the results of this research supported the
effectiveness of videotaped modeling and the combination of videotaped modeling
and videotaped feedback. The effectiveness of videotaped feedback by itself was not
supported nor were the proposed underlying relationships. In addition, none of the
proposed personality by treatment interactions were supported. One signiﬁcant
personality by treatment interaction was found, however, it was opposite to that
which was predicted. These results are discussed in more detail below.
Videotaped Modeling and Videotaped Feedback: Main Eﬂects and Interaction

Based on past research (Decker & Nathan, 1985; Dowrick & Biggs, 1983) it
was predicted that both videotaped modeling and videotaped feedback would have
a positive impact on performance in training. It was also predicted that a combined
treatment condition including both modeling and videotaped feedback would have

a greater impact on performance than either treatment alone. As predicted

71

72

videotaped modeling had a signiﬁcant impact on post training role play performance
such that those subjects who received videotaped modeling showed signiﬁcantly
greater improvements in role play performance than those who did not receive
videotaped modeling. In addition, subjects in the combined treatment condition had
greater post training performance than subjects in any other group. Thus, the results
of this study support past research on the effectiveness of videotaped modeling
(Decker & Nathan, 1985; Kanfer & Goldstein, 1980) and extend past research by
providing evidence that videotaped modeling in combination with videotaped
feedback leads to greater performance than either treatment alone.

Contrary to what was predicted, no main effect was found for videotaped
feedback. One possible explanation as to why videotaped feedback had no main
effect on post training role play performance is that subjects were not able to make
accurate evaluations of their own performance. This study, unlike other studies
which have reported a signiﬁcant effect for videotaped feedback (Decker, 1983;
Barbee & Keil, 1973; Speas, 1979), did not include feedback from the trainer.
Instead subjects were allowed to watch their videotapes in private. Perhaps feedback
from the trainer is necessary in order for videotaped feedback to be effective.

In order to examine the possibility that subjects were not able to make
accurate evaluations of their own performance, a post hoc analysis was conducted
to examine the relationship between self-ratings on the practice role play and a
trained rater’s ratings on the practice role play. The results of this analysis revealed
a signiﬁcant but low correlation (r = .30, p < .001) between the performance ratings
of the trained rater and subject self-ratings. Further analysis revealed that self-

ratings on the practice role play were signiﬁcantly related to videotaped feedback

73
condition such that subjects in the videotaped feedback conditions gave themselves
slightly higher ratings than subjects in the no videotaped feedback conditions. In
sum, these results offer some support for the suggestion that subjects did not beneﬁt
from videotaped feedback because they were not able to make accurate evaluations
of their own performance.

Another possible explanation as to why videotaped feedback had no main
effect on post training performance is that all subjects did receive feedback from the
task itself. That is, on a task such as this, it is possible to evaluate one’s own
performance without external feedback. Perhaps watching oneself on videotape does
not provide significantly more information than performing the task alone.

Another possible explanation as to why videotaped feedback had no main
effect on post training performance is that videotaped feedback may have had a
negative impact on the performance of some subjects and a positive impact on the
performance of others. Observing oneself fail at a task may lower self-efficacy and
subsequent performance. It is also possible that observing oneself fail may create
self-dissatisfactions that serve as motivational inducements for enhanced effort
(Bandura & Cervone, 1986). According to Bandura (1986), social cognitive theory
postulates two cognitive mechanisms that inﬂuence motivation and behavior. The
first operates anticipatorily through self-efﬁcacy and outcome expectations. The
second, labeled a self-regulatory mechanism (Bandura, 1986), operates through
internal standards and self-evaluative reactions to one’s performance. When people
commit themselves to explicit standards, perceived negative discrepancies between
their actual performance and their internal standard creates self-dissatisfactions that

serve as motivational inducements for enhanced effort. To quote Bandura (in press):

74

People initially motivate themselves through feedforward control by setting themselves
valued challenging standards that create a state of disequilibrium . . . After people
attain the standard they have been pursuing, they generally set a higher standard for
themselves. The adoption of further challenges creates new motivating discrepancies
to be mastered. Similarly, surpassing a standard is more likely to raise aspiration than
to lower subsequent performance to conform to the surpassed standard. Self-
motivation thus involves a dual cyclic process of disequilibrating discrepancy production
followed by equilibrating discrepancy reduction. (c.f. Locke & Latham, 1990; p. 20)

Past research supports the existence of self-regulatory mechanisms. For
example, research has shown that: (a) individuals react to initial failure to reach a
performance standard by intensifying their effort, whereas repeated failures lead to
giving up the standards (Campion & Lord, 1982), (b) the higher one’s self-
dissatisfaction with substandard performance and the stronger one’s perceived self-
efﬁcacy for goal attainment, the greater the subsequent intensiﬁcation of effort
(Bandura & Cervone, 1983), and (c) subjects who receive negative feedback perform
at higher levels on subsequent trials than subjects who receive positive feedback
(Podsakoff & Farh, 1989).

While no specific goal or standard was assigned in this study, subjects were
asked to try to include as many of the learning points as possible in their role plays.
In addition, subjects in this study were asked to rate their performance on the
practice role play. Therefore, a post hoc analysis was performed to examine
whether self-evaluative reactions to one’s performance (i.e., self-ratings of one’s
performance) moderate the impact of videotaped feedback on post training
performance. The results of this analysis showed that subjects who received
videotaped feedback and gave themselves lower self-ratings had higher post training
performance than subjects who gave themselves higher self-ratings (See Appendix

E.). This result is consistent with past research which has shown that individuals

75

react to perceived negative discrepancies between their actual performance and a
standard by intensifying their effort and performance on subsequent trials (Campion
& Lord, 1982; Podsakoff & Farh, 1989). Further analysis revealed a marginally
signiﬁcant triple interaction (p < .10) between self-efﬁcacy, videotaped feedback and
self-ratings such that the greatest improvement in performance was achieved by
subjects who received videotaped feedback and had high self-efﬁcacy and low self-
ratings. This result supports past research which showed that the greatest
intensiﬁcation of effort occurred for subjects who had high self-efﬁcacy and were
highly dissatisﬁed with their performance (Bandura & Cervone, 1983). In sum, the
results of this study support past research which has demonstrated the existence of
a self-regulatory mechanism (Bandura, 1986) in which individuals react to perceived
negative discrepancies between their actual performance and their internal standard
by enhancing subsequent effort. In addition, this study extends past research by
demonstrating that this self-regulatory mechanism operates in a training setting with
the use of videotaped feedback.
Personality Variables

Hypotheses 2 through 5 predicted main effects for locus of control and ﬁeld-
dependence such that internals would have greater post training performance than
externals, and field-dependent individuals would have greater post training
performance than field-independent individuals. These predictions were based on
past research which has demonstrated that internals have greater success in learning
situations than externals (Nowicki & Strickland, 1973; Brown & Strickland, 1972;
Baumgartel et al., 1984), and that field-dependent individuals tend to have greater

interpersonal competencies than field-independent individuals (Witkin &

76

Goodenough, 1981). Contrary to what was predicted, no main effect for locus of
control or ﬁeld-dependence was found.

One possible explanation as to why locus of control did not have a main
effect on post training performance is related to the type of training techniques used.
The present study used one social inﬂuence technique (i.e., videotaped modeling)
and one self-regulation technique (i.e., videotaped feedback). Past research suggests
that externals are highly responsive to external social reinforcement and are more
inﬂuenced by conformity pressures in social inﬂuence situations than are internals
(Baron & Ganz, 1972). Internals, on the other hand, have a higher level of
achievement motivation than externals and are better able to regulate their behavior
by self-reinforcement (Baron & Ganz, 1972). It’s possible that the greater
achievement motivation and self regulation ability of internals did not put them at
an advantage over externals in this study because the training techniques used were
designed to include either self-regulation or social inﬂuence.

Field-dependence may not have had a main effect on post training
performance because of the training content used. In this study, subjects were
taught how to give negative feedback. Field—dependent individuals are described as
being warm, accommodating and accepting of others (Witkin & Goodenough, 1977).
It’s possible that ﬁeld-dependent individuals found the task of giving negative
feedback more difficult than field-independent individuals. Thus, even though field-
dependent individuals, compared with field-independent individuals, tend to have
greater interpersonal competencies (Witkin et al, 1977a; Witkin et al, 1977b), this
may not have helped them on the negative feedback task used in this study since

these individuals also have the tendency to be nonevaluative and accepting of others.

77

Field-independent individuals, on the other hand, who are described as being cold,
distant and impersonal in their interactions with others (Witkin & Goodenough,
1977), may have considered this an easy task. However, field-independent
individuals may not have had an advantage over field-dependent individuals because
the task not only involved giving negative feedback, but showing concern for the
other person’s feelings.
Personality by Treatment Interactions

Hypothesis 2 predicted a signiﬁcant interaction between locus of control and
videotaped modeling such that the relationship between modeling and performance
would be greater for internals than externals. This prediction was based on previous
research which demonstrated that internals are more likely than externals to change
their behavior in treatments designed to enhance self-efﬁcacy (Chambliss & Murray,
1979). It was also suggested that internals may respond more readily to modeling,
since they tend to believe that they, like the models are in control of their
environments. Externals, on the other hand, may believe that changing one’s
behavior to imitate a model would have little impact on their own performance,
since they tend to believe that outcomes are not a result of their own behavior. A
significant interaction was found, however, contrary to what was predicted, the
relationship between videotaped modeling and performance was greater for externals
than internals.

One possible explanation as to why the results of this study did not support
that of Chambliss and Murray (1979) is that this study used videotaped modeling as
the training intervention whereas the other study used a performance

accomplishment intervention (i.e., subjects were told that weight loss was due to

78

their own effort rather than placebo diet pills). It is possible that internals in
comparison to externals may be less responsive to external cues (videotaped
modeling) as opposed to internal cues (performance accomplishments). It is also
possible that externals, as opposed to internals may be less confident in the
appropriateness of their own behavior and as a result may be more likely to utilize
the kind of information provided by behavior models. In addition, as noted earlier,
past research has shown that externals are highly responsive to external social
reinforcement and are more inﬂuenced by conformity pressures in social inﬂuence
situations than are internals (Baron & Ganz, 1972). In sum, it is suggested that the
prediction made in Hypothesis 2 was based on a misinterpretation of Rotter’s (1966)
conceptualization of locus of control. A more accurate interpretation may be that
internals, who are confident in their ability to control their own environment, should
be less likely to imitate external role models, whereas externals may believe that the
only way they can control their environment is to imitate other people’s behavior.

Hypothesis 3 predicted a significant interaction between ﬁeld-dependence and
videotaped modeling such that the relationship between modeling and performance
would be greater for ﬁeld-dependent individuals than ﬁeld-independent individuals.
This prediction was based on past research which showed that ﬁeld-dependent
teachers were found to benefit significantly more from videotaped modeling than
field-independent teachers (Koran et al., 1971). In this study, however, no signiﬁcant
interaction was found. One possible explanation as to why ﬁeld-dependent
individuals in this study did not benefit more from videotaped modeling than ﬁeld-
independent individuals was mentioned earlier. That is, it’s possible that ﬁeld-

dependent individuals who tend to be nonevaluative and accepting of others, found

79

the task of giving negative feedback more difficult than ﬁeld-independent individuals
who tend to be cold, distant and impersonal in their interactions with others (Witkin
& Goodenough, 1977). Thus, even though ﬁeld-dependent individuals, compared
with ﬁeld-independent individuals tend to beneﬁt more from videotaped modeling
(Koran et al., 1971) this may not have helped them in this study because the task
(i.e., giving negative feedback) required them to do something that they tend to
avoid (i.e., being evaluative and nonaccepting of others).

An alternative explanation may be that field-independent individuals are just
as likely to be inﬂuenced by high performing models as ﬁeld-dependent individuals.
For example, Weiss and Nowicki (1981) examined the impact of model competence
and observer field-dependence on task satisfaction. Their results indicated that the
task attitudes of ﬁeld-dependent subjects were signiﬁcantly inﬂuenced by the
expressed attitudes of a model regardless of the model’s competence, whereas the
task attitudes of ﬁeld-independent subjects were only inﬂuenced by high performing
models. Thus, there may have been no interaction between ﬁeld-dependence and
videotaped modeling in this study because the models shown were high performing
models.

Hypothesis 4 predicted a signiﬁcant interaction between locus of control and
videotaped feedback such that the relationship between videotaped feedback and
performance would be greater for internals than externals. This prediction was
based on past research which has shown that children who attribute failure to
insufficient effort (an internal factor) are less likely to give up on a task after
experiencing failure (Diener & Dweck, 1978) and that internals perform better when

given intrinsic feedback (i.e., subjects were allowed to discover for themselves

80
whether their responses were right or wrong) as opposed to extrinsic feedback (i.e.,
the experimenter informed subjects whether or not their responses were right or
wrong; Baron et al., 1974; Baron & Ganz, 1972). Contrary to what was predicted
no signiﬁcant interaction effect was found in this study.

One possible explanation as to why no interaction effect was found is that this
study compared an intrinsic feedback situation with a no feedback situation rather
than comparing an intrinsic feedback situation with an extrinsic feedback situation.
Perhaps a significant locus of control by videotaped feedback interaction would have
been found if subjects had participated in one of two videotaped feedback
treatments: one in which subjects were allowed to watch their videotape on their
own, and one in which subjects were given feedback from the experimenter during
or after observation of their videotape.

The absence of an interaction effect may also be due to the ability of
internals to regulate their behavior by self-reinforcement (Baron & Ganz, 1972).
Internals, as opposed to externals, may not have benefited more from videotaped
feedback because they already possess self-regulation ability. Perhaps videotaped
feedback serves a compensatory function for externals that increases their self-
regulation activity. Thus, the tendency for internals, in comparison to externals, to
respond more favorably to intrinsic feedback situations may have been offset by the
tendency of videotaped feedback to increase the self-regulation activity of externals.

Hypothesis 5 predicted a significant interaction between ﬁeld-dependence and
videotaped feedback such that the relationship between videotaped feedback and
performance would be greater for field-dependent individuals than field-independent

individuals. This prediction was based on research which has shown that ﬁeld-

81
dependent individuals pay greater attention to social cues and have a greater need
for information from external sources (Witkin & Goodenough, 1981; Karp, 1977).
Thus, it was suggested that ﬁeld-dependent individuals would be more likely than
ﬁeld-independent individuals to benefit from information on the appropriateness of
their social behavior (i.e., videotaped feedback). Contrary to what was predicted no
signiﬁcant interaction was found.

One possible explanation as to why there was no significant interaction
between field-dependence and videotaped feedback is that ﬁeld-dependent
individuals, who rely on external social cues for their behavior, may not be able to
beneﬁt from videotaped feedback unless it is interpreted by an external source. As
noted earlier, this study compared an intrinsic feedback situation with a no feedback
situation. Perhaps ﬁeld-dependent individuals, in comparison to ﬁeld independent
individuals, would have performed better in the videotaped feedback treatment if
feedback from the experimenter on the quality of the subject’s performance had
been included as part of the training intervention.

General Mental Ability ('g”)

Hypotheses 6 and 7 predicted a main effect for general mental ability such
that high ability individuals in all treatment conditions would have greater post
training performance than low ability individuals. In general, high ability
individuals did perform better than low ability individuals in all treatment conditions,
however, this difference was only marginally signiﬁcant (the partial correlation
between post training performance and "g" controlling for pre-training performance
was (pr (178) = .14, p = .06). One possible explanation as to why "g" did not have

a significant effect on performance in this study may be due to individual differences

82

in negative feedback experience. A post hoc analysis conﬁrmed that "g" explained
a significant amount of variance in post training role play performance after
controlling for pre-training role play performance and negative feedback
experience (A R2 = .03, p < .05). Thus, the results of this study conﬁrm past
research which suggests that "g" is correlated with performance across a wide range
of tasks and situations (Jensen, 1986; Hunter, 1986; Thorndike, 1986).

In addition to the above mentioned main effects, hypothesis 6 predicted that

H H

the interaction between videotaped modeling and g would not be signiﬁcant and

hypothesis 7 predicted that the interaction between videotaped feedback and g

would not be signiﬁcant. As predicted, no signiﬁcant interactions between g and
training treatment were found. These results support past research indicating that
most ability by treatment interactions are not signiﬁcant (Whitener, 1989).

It was also predicted that high ability individuals would demonstrate greater
knowledge than low ability individuals. The results of this study conﬁrmed this
prediction. Post training knowledge was signiﬁcantly related to "g" such that high
ability individuals performed better on the post training learning tests than low
ability individuals.

Process Model

It was suggested that videotaped modeling and videotaped feedback may
inﬂuence performance in training indirectly through their impact on knowledge and
self-efficacy. The results showed that neither videotaped modeling nor videotaped
feedback had a significant impact on post training knowledge. There was a

significant interaction between videotaped modeling and videotaped feedback,

however, contrary to what was predicted, subjects in the combined treatment group

83

exhibited signiﬁcantly lower post training knowledge than subjects in any other
group. This ﬁnding may be due to the experimental procedure used in this study.
In order to ensure that the duration of each training session was approximately the
same across all training treatments, subjects in all conditions except the combined
treatment condition were given time to study the learning points before taking their
learning tests. It’s possible that this extra study time was beneficial to performance
on the learning test but not on the post training role play.

It is also possible that the true impact of the combined treatment condition
on post training role play performance may be suppressed because of the negative
impact it has on knowledge (i.e., the beta coefficient for the impact of the combined
treatment on knowledge was 3 = -.30). A suppressor effect occurs when the
relationship between the independent variables hides or suppresses their real
relationships with the dependent variable, which would be larger were they not
correlated (Cohen and Cohen, 1983). In order to examine the possibility of a
suppressor effect, an analysis was performed to examine the impact of the combined
treatment condition on post training role play performance controlling for post
training knowledge. The results of this analysis supported the existence of a
suppressor effect (See Appendix B). When the effects of post training knowledge
are controlled, the effect size for the combined treatment condition increases (sr’2 =
.048, p < .001, versus s12 = .023, p < .05).

With regard to post training self-efficacy, neither videotaped modeling,
videotaped feedback nor any of the predicted interactions had a signiﬁcant effect on
post training self-efﬁcacy. This result may be due to the type of self-efﬁcacy

measure used. Subjects were given descriptions of five real world situations and

 

84

were asked how conﬁdent they were in their ability to give negative feedback to the
employee described in such a way that would increase the employee’s motivation
and desire to improve without offending the employee. Even though both the
videotaped modeling treatment and the combined videotaped modeling/videotaped
feedback treatment were sufficiently strong to increase performance in a role play
situation, they may not have been strong enough to inﬂuence subject’s perceptions
of how well they could give feedback in a real world situation. Perhaps training
treatment would have had a signiﬁcant impact on self-efﬁcacy if subjects had been
asked to indicate their conﬁdence in their ability to give feedback in a role play
situation.

An additional set of analyses revealed that both knowledge and self-efficacy
explained a significant amount of variance in post-training role play performance,
however, since videotaped modeling, the interaction between videotaped modeling
and videotaped feedback, and the interaction between videotaped modeling and
locus of control explained a signiﬁcant amount of variance in post training
performance over and above that explained by post training knowledge and post
training self-efﬁcacy, knowledge and self-efﬁcacy do not appear to be mediators.
However, as mentioned above, the failure of self-efﬁcacy and knowledge to mediate
the relationship between training treatment and post training performance may be
due to the experimental procedures used in this study.

Practical Implications

The findings of the present study have several practical implications for

training professionals. In agreement with previous research (Decker & Nathan,

1985; Bandura, 1986) videotaped modeling had a positive impact on the

 

85
performance of all individuals. However, this study found that videotaped modeling
had a greater impact on the performance of externals than internals. This ﬁnding
should be good news to practitioners since past research has shown that internals
have greater success in learning situations than externals (Nowicki & Strickland,
1973; Brown & Strickland, 1972; Baumgartel et al., 1984). Thus, those training
practitioners who are debating whether to use videotaped modeling due to time or
money constraints should be advised that modeling, in addition to having a positive
impact on the performance of all subjects, has an even bigger impact on the
performance of externals who tend to have lower performance than internals in
learning situations. This study also found that a combined training treatment
including videotaped modeling and videotaped feedback had a greater impact on
post training performance than either treatment alone. This ﬁnding suggests that in
order to maximize performance in training it’s not enough to show someone what
to do, you also need to give them feedback on the quality of their performance
efforts. The results of this study suggest that videotaped feedback may be a
successful way of providing that feedback.

A third ﬁnding of interest to practitioners is that videotaped feedback did not
have a significant main effect on performance, in fact individuals in the videotaped
feedback (without videotaped modeling) treatment showed less improvement in
performance than subjects in the control group, although this difference was only
marginally signiﬁcant (p = .10). As mentioned earlier, this could be due to the way
in which videotaped feedback was provided. Trainees in this study were allowed to
watch and interpret their videotape on their own in a private room. In order for

videotaped feedback to be effective it’s possible that the individual may also need

 

86

feedback from an outside source on the quality of the behaviors being exhibited on
the videotape.
Limitations

Several limitations of the present research should be discussed. First, the
experimental procedures used in this study may have distorted the ﬁndings with
regard to the impact of videotaped modeling and videotaped feedback on self-
efficacy and knowledge. As mentioned earlier, this study found that subjects in the
combined treatment condition had the lowest post training knowledge, the highest
post training role play performance and no signiﬁcant difference between other
groups with regard to post training self-efﬁcacy. It was suggested that the subjects
in the combined treatment group may have performed lower on the learning tests
than subjects in any other group because they, unlike the others, were not allowed
any study time. It was also noted that the self-efficacy measure used in this study
measured self-efficacy for giving feedback in real world situations as opposed to self-
efficacy for this task (i.e., a role play situation). In sum, the results of this study with
regard to knowledge gained and self-efficacy do not support past research and it is
felt that the experimental procedures used may be the cause. While it is important
to keep duration of training consistent across all experimental conditions, future
research should avoid using study time as a time filler because this may distort
results with regard to learning criteria.

Another limitation of this study involves the external validity of the results
obtained here. This research involved the training of undergraduates in an
interpersonal skill (i.e., how to give negative feedback). The extent to which findings

from this sample, setting, and task are generalizable to the training of managers in

87

organizational settings is uncertain. For example, managers working in organization
typically have more experience in giving negative feedback. It is possible that
videotaped modeling and videotaped feedback may be more effective in training
individuals with lower experience. A post hoc analysis of the data in the present
study offers some support for this prediction (See Appendix E). A significant
interaction between feedback experience and training treatment was found such that
videotaped feedback had a positive impact on the performance of individuals with
little or no feedback experience and a negative impact on the performance of
individuals with greater negative feedback experience. Videotaped modeling also
had a greater impact on inexperienced individuals, although this difference was not
significant (p > .10).

Another boundary condition may be that the variance in locus of control
may be smaller in a managerial sample than in a student sample. For example,
research on locus of control suggests that managers are more likely to have an
internal locus of control as opposed to an external locus of control (Mitchell,
Smyser, & Weed, 1975). As a result, the finding that externals are more likely to
benefit from videotaped modeling than internals, may not be replicated in a
managerial sample in which there are very few externals. Further research in a field
setting is sorely needed in this area.

Finally, it should be noted that there were a large number of hypotheses
tested in this study suggesting the possibility of high experimentwise error.
According to Cohen and Cohen (1983), Type I error in multiple regression/
correlation analysis can be assessed by using a procedure similar to the Fisher test

(Fisher, 1963). That is, the contribution to Y variance of an entire set of variables

 

88

is tested for significance by the standard F test. If the F for a given set is signiﬁcant,
the independent variables which make up the set may be tested individually for
signiﬁcance by means of a standard t -test. Since the regression equation containing
the entire set of variables measured in this study was signiﬁcant (F = 5.31, p <
.001), one can conclude that experimentwise error is not a serious problem in this
study.
Future Research

While educational researchers and clinical psychologists have been conducting
research on videotaped feedback for several years (Bailey & Sowder, 1970; Fuller
& Manning, 1973) research on videotaped feedback has just recently started to
receive attention in the training literature (Decker, 1983). Videotape technology has
improved greatly over the past twenty years and it is now much cheaper and easier
to use videotaped feedback than ever before. However, more research is needed in
this area before we can conﬁdently recommend its use. This study found that
videotaped feedback did not have a positive impact on the performance of all
subjects. Future research should examine the conditions under which videotaped
feedback is beneficial to performance in training. This study found that videotaped
feedback is beneficial when combined with videotaped modeling. It was also found
to be beneficial for subjects who rate themselves low after watching themselves on
videotape. While past research has demonstrated that videotaped feedback
combined with trainer feedback is superior to trainer feedback alone, future research
should examine whether videotaped feedback combined with trainer feedback is

superior to videotaped feedback alone.

 

 

 

 

89

Future research should also continue to examine personality by treatment
interactions. Even though none of the predicted personality by treatment
interactions were supported in this study, it is felt that this may be due to either the
training content (i.e., giving negative feedback) or the training procedures used. For
example, future research should examine the interaction between field-dependence
and videotaped modeling for other managerial skills such as conducting a meeting,
public speaking, or active listening. Future research should also examine whether
externals in comparison to internals and field-dependent individuals in comparison
to field-independent individuals, beneﬁt more from videotaped feedback that
includes trainer feedback than from videotaped feedback that does not include
trainer feedback. Finally, future research should examine the relationship between
training technique and other personality variables such as self-esteem, self-focus and
self-monitoring. This recommendation is based on past research which has found
that these variables have a signiﬁcant effect on learning and performance in various
situations (Snyder, 1974; Brockner & Hulton, 1978; Salomon & McDonald, 1970;
Weiss, 1977; Weiss, 1978).2
Conclusions

Overall the results of this research support the effectiveness of videotaped
modeling and the combination of videotaped modeling and videotaped feedback on
post training role play performance. The effectiveness of videotaped feedback

without videotaped modeling was not supported. In addition, the results of this

 

2Additional post hoc analyses were conducted on the interaction between training
treatment and self-efficacy. Only one of the interaction between videotaped
feedback and self-efficacy was signiﬁcant. See Appendix E.

90
study did not support the proposed personality by treatment interactions. Several
explanations for these results were offered. It is felt that videotaped feedback may
still show promise in improving performance in training when combined with
feedback from the trainer and that personality by treatment interactions may also
be found under these conditions. Future research is necessary to examine these

predictions more directly.

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APPENDICES

APPENDIX A

 

D

APPENDIX A

LEARNING POINTS

O’s

 

b—3

.N

9.

. Talk with the employee in a private location.

Use eye contact.

Be aware of nonverbal behaviors.

Explain the problem to the employee without hostility.

Criticize the behavior, not the employee.

Be speciﬁc.

Ask for and listen openly to the employee’s reasons for the behavior.
Show that you understand the employee’s feelings.

Ask the employee for his or her ideas on how to solve the problem.

10. Ask the employee if there is anything that you can do to help.

11. Agree to review performance at a later date.

DON ’Ts

l.

2.

Use general evaluative statements.

Scold or belittle the employee because of their actions.
Make attributions for the causes of the employee’s behavior.
Compare the employee to other employees.

Rush through the feedback session.

102

APPENDIX B

SETTING:

DOUG:

APPENDIX B

VIDEOTAPED MODELING SCRIPTS

SCRIPT USED IN VIDEOTAPE # 1
"COST OVERRUNS # I "

(Running Time: 2 minutes)

An ofﬁce with a desk. One chair is positioned in front of the desk,
one chair is positioned on the side of the desk, and one chair is behind
the desk. The supervisor, Doug is alone in the office sitting behind the
desk. Jon knocks on the door, enters the room and sits in front of the
desk.

Hi Jon, come on in. There are some things I would like to talk to you
about. First of all I want you to know that, in general, I think you are
a pretty good engineer.

(DON’T USE GENERAL EVALUATIVE STATEMENTS)

You have achieved some good results on the cushion assembly, seating
assembly and engine assembly projects. And in general you’ve done
that without my help, which is nice. I like to see engineers who are
capable of running their own ship. Captains so to speak of their own
ship. But personally I would have to say that you’re in the lower half
of the 10 engineers that I supervise. Not nearly as good as Bill
Randall for example.

(DON’T COMPARE THE EMPLOYEE TO OTHER EMPLOYEES)

103

JON:

DOUG:

JON:

DOUG:

JON:

104

And, I guess I would have to say that this is because you are just not
persistent enough, you’re not thorough enough, you just don’t have the
stick-to-it-ness that is required to see a project through. Your co-
workers, are continually saying you’re a burden basically. They go
around tying up all of the loose ends for your own failure.

(DON’T SCOLD OR BELIT'I‘LE THE EMPLOYEE BECAUSE OF
THEIR ACTIONS)

What do you mean not thorough enough? After all of the good
projects that I have done for you, you can think of me as having no
stick-to-it-ness.

Well, you know what I mean.
NO, I don’t, can you give me an example?

I shouldn’t have to give you examples. Look you’ve got to admit that
on that one project you ran into some cost over runs. This basically
was because you ran off and made decisions without gathering the
appropriate information. I think that this is because things have always
come too easy for you.

(DON’T MAKE ATTRIBUTIONS FOR THE CAUSES OF THE
EMPLOYEE’S BEHAVIOR)

You know it’s the old adage when the going gets tough, rather than get
tough yourself, you take the easy way out. And your co-workers in
general say the same thing as far as needing to follow up on things that
you are responsible for. Now, I really don’t want to end this
conversation on a negative note. I think that if you would just
concentrate on these weaknesses and try to improve in these areas that
overall you could be a good employee.

Do you have anything to say?

No, I think you’ve said it all.

(DON’T RUSH THROUGH THE FEEDBACK SESSION)

 

SETTING:

DOUG:
JON:
DOUG:
JON:
DOUG:

105

SCRIPT USED IN VIDEOTAPE # 2
"COST OVERRUNS # 2 "
(Running Time: 2 minutes, 20 seconds)
An office with a desk. One chair is positioned in front of the desk,
one chair is positioned on the side of the desk, and one chair is behind

the desk. The supervisor, Doug is alone in the office standing behind
the desk.

(USE EYE CONTACT)

(BE AWARE OF NONVERBAL CUES)

Jon knocks on the door, enters the room and sits in front of the desk.
Doug sits facing Jon at the side of the desk.

Hi, Jon!

Hi Doug, how are you?

Pretty good, yourself?

Fine.

Basically the purpose of this meeting is to talk about some of the past
projects that you have been working on.

(EXPLAIN TO THE EMPLOYEE THE PURPOSE OF THE
MEETING)

You did an outstanding job on the engine assembly project and some
of the innovations you made on that project can be directly attributed
to your hard work and ingenuity. On your last project, however, I
noticed there were some cost overruns.

(EXPLAIN THE PROBLEM To THE EMPLOYEE WITHOUT
HOSTILITY)

JON:

DOUG:

JON:

DOUG:

JON:

DOUG:

106

(CRITICIZE THE BEHAVIOR, NOT THE EMPLOYEE)

(BE SPECIFIC)

Well yes. I guess we underestimated the man power required to finish
the project.

What do you think caused these cost overruns?

Well I guess it’s my fault because I didn’t get the information from the
proper people. I had a tough time getting the information I needed
and as a result I guess I just got to the point where I just decided to
go ahead on my own, and as a result that’s what caused the cost
overruns.

(ASK FOR AND LISTEN OPENLY TO THE EMPLOYEE’S
REASONS FOR THE BEHAVIOR)

Well then it looks like the problem is due to your inability to get the
appropriate information to enable you to make correct decisions. How
do you think we can make certain that this doesn’t happen again in the
future?

(ASK THE EMPLOYEE FOR HIS OR HER IDEAS ON HOW TO
SOLVE THE PROBLEM)

Well, I guess in the future I guess I’m going to have to try to be more
persistent in trying to obtain the information I need, and pay a little
more attention to detail before making a final decision on a project.

I agree 100% with that, well is there anything that I can do to help?

(ASK THE EMPLOYEE IF THERE IS ANYTHING THAT YOU CAN
DO TO HELP)

JON:

DOUG:

JON:

DOUG:

JON:

DOUG:

SETTING:

107

No, I don’t think so but you know it gets awful frustrating sometimes
when you’re trying to put together a project and you need information
from certain individuals and you can’t get them to answer you phone
calls, you can’t get them to answer your memos, they’re never in their
office, you know you just get frustrated after while and that causes
you to make mistakes and that’s why I’m having the cost overruns.

I can really feel for the frustration you’re experiencing with the road
blocks, and the obstacles that exist with the communication process.

Is there any area I can help with to relieve you of these problems?
Maybe I could make some contacts for you?

(SHOW THAT YOU UNDERSTAND THE EMPLOYEE’S FEELINGS)

Well, yes in certain situations, that would be a great idea.

Okay, just let me know when you need my help and I’ll do whatever
I can. By the way what’s the project deadline for your new project?

Well, I think that project is coming along fine, it’s supposed to be
completely ﬁnished in 2 or 3 months, I believe the actual completion
date is May lst.

Well then why don’t I back with you on March 1st to check with you
on the progress you’re making on the new project.

(AGREE TO REVIEW PERFORMANCE AT A LATER DATE)

***THEEND***

SCRIPT USED IN VIDEOTAPE # 3
"A CHAUVINISTIC REMARK # 1"
(Running Time: 40 seconds)

An ofﬁce with a desk. One chair is positioned in front of the desk,
one chair is positioned on the side of the desk, and one chair is behind
the desk. The supervisor, Jim is alone in the office sitting behind the
desk. Darrell knocks on the door, enters the room and sits in front of
the desk.

 

JIM:

DARRELL:
JIM:

DARRELL:

JIM:

108

Hi Darrell, come on in. There is something I would like to talk to you
about. I’ve heard that you are somewhat bigoted toward your female
coworkers.

(DON’T SCOLD OR BELI'I'I‘LE THE EMPLOYEE BECAUSE OF
THEIR ACTIONS)

Bigoted? What do you mean bigoted?

I think you know.

If I said something out of line, I’m sorry but I assure you I never
meant anything by it. I’m certainly not a bigot.

Well, others seem to think differently. You know I used to think you
were a pretty good manager, but now, I don’t know what to think.

(DON’T USE GENERAL EVALUATIVE STATEMENTS)

Look, Bob Jones has more female employees in his unit than you and
he never has these kinds of accusations made of him.

(DON’T COMPARE THE EMPLOYEE TO OTHER EMPLOYEES)

You know I really think this women thing is due to your own
insecurities as a man. I think that in general, the women you work
with threaten you.

(DON’T MAKE ATTRIBUTIONS FOR THE CAUSES OF THE
EMPLOYEE’S BEHAVIOR)

Well, I don’t know what else to say, except that I hope we never have
to have this conversation again.

(DON’T RUSH THROUGH THE FEEDBACK SESSION)

***THEEND***

SETTING:

JIM:
DARRELL:
JIM:
DARRELL:

JIM:

109

SCRIPT USED IN VIDEOTAPE # 4
"A CHAUVINISTIC REMARK # 2"
(Running Time: 1 minute, 30 seconds)
An office with a desk. One chair is positioned in front of the desk,
one chair is positioned on the side of the desk, and one chair is behind

the desk. The supervisor, Jim is alone in the ofﬁce standing behind
the desk.

Darrell knocks on the door, enters the room and sits in front of the
desk. Jim sits facing Darrell at the side of the desk.

(BE AWARE OF NONVERBAL CUES)

Hi, Darrell!

Hi Jim, how are you?

Pretty good yourself?

Fine

Basically the purpose of this meeting is to discuss an incident that was

recently brought to my attention.

(EXPLAIN TO THE EMPLOYEE THE PURPOSE OF THE
MEETING)

(USE EYE CONTACT)

Now it’s probably minor, but I think it’s something we should talk
about. It involved a comment you made to a female co-worker.

(EXPLAIN THE PROBLEM To THE EMPLOYEE WITHOUT
HOSTILITY)

DARRELL:

JIM:

DARRELL:

JIM:

DARRELL:

JIM:

DARRELL:

110

What comment? What did I say?

Well it was a comment you made that was interpreted as being quite
sexist or chauvinistic.

(CRITICIZE THE BEHAVIOR, NOT THE EMPLOYEE)

(BE SPECIFIC)

Sigh. I knew this was going to come up, but I really don’t see any
reason for it. Really, Jim, I didn’t mean anything by it. I was really
trying to compliment her on the ﬁne job that she had done. If I came
off as chauvinistic it was just the way she interpreted it. No way was
I a chauvinist in that situation.

(ASK FOR AND LISTEN OPENLY TO THE EMPLOYEE’S
REASONS FOR THE BEHAVIOR)

Yes, I realize that people often interpret things differently than they
were intended. However, if we are going to maintain good working
relationships with our coworkers, we’ve got to be careful in how we
phrase our opinions.

(SHOW THAT YOU UNDERSTAND THE EMPLOYEE’S FEELINGS)

Yes, well I guess I can see why she may have misinterpreted my
remark.

Well, what do you think you could do differently in the future to
prevent this from happening again?

(ASK THE EMPLOYEE FOR HIS OR HER IDEAS ON HOW TO
SOLVE THE PROBLEM)

I’ll just have to choose my words more carefully.

JIM:

DARRELL:

JIM:

111

Is there anything I can do to help?

(ASK THE EMPLOYEE IF THERE IS ANYTHING THAT YOU CAN
DO To HELP)

Well no, I don’t think so, but if I have any further problems I’ll get
back to you.

Good, why don’t I check back with you in a couple of weeks, say the
first of the month. and we’ll see how things are going. Thanks for your
time Darrell. I’ve got great confidence in you.

(AGREE TO REVIEW PERFORMANCE AT A LATER DATE)

***THEEND***

APPENDIX C

APPENDIX C

PRACTICE ROLE PLAY

ROLE FOR SUBJECT: Supervisor, Pat Johnson

Robin Benson has been with your company, a management consulting ﬁrm,
for the past nine months. She/he is extremely intelligent and displays a great deal
of initiative and creativity. Her/his only real fault is that she / he is sometimes rude,
arrogant and uncooperative. She/he has a tendency to criticize her/his coworkers
ideas without taking their feelings into account. Frequently, Robin’s comments are
accurate, but she/ he often cause defensiveness in the rest of the group.

This was the case in a recent group meeting between yourself, Robin and
three other employees. On several occasions Robin interrupted a peer’s comments
to point out the weaknesses in that idea. At one point she/he said, "No way! Are
you crazy or did you leave your brains at home today? That’s absolutely ridiculous.
It would never work. First of all, . . . ." At this point the recipient of this tirade
clammed up and didn’t say another word for the rest of the meeting.

You have decided to talk brieﬂy with Robin about this behavior in a few
minutes.

ROLE FOR CONFEDERATE: Robin Benson

You are Robin Benson a junior consultant for a major management
consulting firm. You have recently graduated from Harvard with an MBA.
You love your job and attack each project with a great deal of enthusiasm.
Unfortunately your co-workers don’t Share your enthusiasm. Most of them are dull
and unimaginative.

Your boss, Pat Johnson has just notified you that she/he would like to talk to
you about a group meeting you attended earlier this week. Overall, you feel the
meeting went quite well. You expressed a lot of good ideas and Pat seemed to
agree with you.

112

APPENDIX D

APPENDIX D

MEASURES
DEMOGRAPHIC VARMBLES
1. What is your class level? Junior Senior
2. What is your age? years
3. What is your G.P.A.? (out of 4.0)
4. What is your sex? Female Male

5. Have you ever held a supervisory position?
(If you answered No, skip questions 6 and 7.)

Yes N o

 

6. Have you ever given negative feedback to one of your subordinates?

Yes No

 

 

(If you answered No, skip question 7.)

7. Approximately how many times have you given negative feedback to one or
more of your subordinates.

113

114

LOC US OF CONTROL

For each of the items below, circle the statement that you agree with most.

FILLER 1.
B 2
A 3
A 4
A 5
B 6
B 7
FILLER 8.
B 9

a

b.

979’

Children get into trouble because their parents punish them too
much.

The trouble with most children nowadays is that their parents
are too easy with them.

Many of the unhappy things in people’s lives are partly due to
bad luck.
People’s misfortunes result from the mistakes they make.

One of the major reasons why we have wars is because people
don’t take enough interest in politics.

. There will always be wars, no matter how hard people try to

prevent them.

In the long run people get the respect they deserve in this
world.

. Unfortunately, an individual’s worth often passes unrecognized

no matter how hard he tries.

The idea that teachers are unfair to students is nonsense.
Most students don’t realize the extent to which their grades are
inﬂuenced by accidental happenings.

Without the right breaks one cannot be an effective leader.
Capable people who fail to become leaders have not taken
advantage of their opportunities.

No matter how hard you try some peOple just don’t like you.
People who can’t get others to like them don’t understand how
to get along with others.

Heredity plays the major role in determining one’s personality.

. It is one’s experiences in life which determine what one is like.

I have often found that what is going to happen will happen.
Trusting to fate has never turned out as well for me as making
a decision to take a definite course of action.

 

FILLER

FILLER

10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

115

. In the case of the well prepared student there is rarely if ever

such a thing as an unfair test.

. Many times exam questions tend to be so unrelated to course

work that studying is really useless.

. Becoming a success is a matter of hard work, luck has little or

nothing to do with it.

. Getting a good job depends mainly on being in the right place

at the right time.

. The average citizen can have an inﬂuence in government

decisions.

. This world is run by the few people in power, and there is not

much the little guy can do about it.

. When I make plans, I am almost certain that I can make them

work.

. It is not always wise to plan too far ahead because many things

turn out to be a matter of good or bad fortune anyhow.

. There are certain people who are just no good.
. There is some good in everybody.

. In my case getting what I want has little or nothing to do with

luck.

. Many times we might just as well decide what to do by ﬂipping

a coin.

. Who gets to be the boss often depends on who was lucky

enough to be in the right place first.

. Getting peOple to do the right thing depends upon ability, luck

has little or nothing to do with it.

. As far as world affairs are concerned, most of us are the victims

of forces we can neither understand, nor control.

. By taking an active part in political and social affairs the people

can control world events.

. Most people don’t realize the extent to which their lives are

controlled by accidental happenings.

. There really is no such thing as "luck."

. One should always be willing to admit mistakes.
. It is usually best to cover up one’s mistakes.

FILLER

FILLER

A

20.

21.

22.

23.

24.

25.

26.

27.

28.

29.

9‘?”

0‘5”

C7!”

C79"

116

It is hard to know whether or not a person really likes you.
How many friends you have depends on how nice a person you
are.

In the long run the bad things that happen to use are balanced
by the good ones.

Most misfortunes are the result of lack of ability, ignorance,
laziness, or all three.

With enough effort we can wipe out political corruption.

. It is difficult for people to have much control over the things

politicians do in ofﬁce.

Sometimes I can’t understand how teachers arrive at the grades
they give.

There is a direct connection between how hard I study and the
grades I get.

A good leader expects people to decide for themselves what
they should do.

. A good leader makes it clear to everybody what their jobs are.

Many times I feel that I have little inﬂuence over the things that
happen to me.

. It is impossible for me to believe that chance or luck plays an

important role in my life.

People are lonely because they don’t try to be friendly.

. There’s not much use in trying too hard to please people, if they

like you, they like you.

There is too much emphasis on athletics in high school.

. Team Sports are an excellent way to build character.

What happens to me is my own doing.
Sometimes I feel that I don’t have enough control over the
direction my life is taking.

. Most of the time I can’t understand why politicians behave the

way they do.
In the long run the people are responsible for bad government
on an national as well as on a local level.

117

FIELD-DEPENDEN CE

COLOR KEY

RED GREEN ORANGE BLUE YELLOW BROWN BLACK

\Illlllll II

Instructions:

I am going to Show you a series of colored designs. After you examine each design, I will show
you a simpler ﬁgure, which is contained in the larger design. Your job will be to locate the smaller
ﬁgure inside the larger ﬁgure. Let’s go through a practice trial to show you how it is done. First I will
show you the simple ﬁgure for 15 seconds, then I will take it away and Show you the larger design. As
soon as you ﬁnd the ﬁgure please trace it with your pen so that I can make sure it is correct.

   

 

Practice Trial

We will proceed the same way on all trials. I would like to add that in every case the smaller
ﬁglre will be present in the larger design. It will always be in the upright position. There may be
several of the smaller ﬁgures in the same large design, but you are to look only for the one in the
upright position. Work as quickly as you can, since I will be timing you; but be sure the ﬁgure you ﬁnd
is exactly the same as the original ﬁgure both in size and in proportions. If you ever forget what the
small ﬁgure looks like, you may ask to see it again. Are there any questions?

118

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124

BEHAVIORAL PRE-TRAINING ROLE PLAY

ROLE FOR SUBJECT: President Pat Jones

You have just asked Chris Marshall to come to your office for a conference.
Chris is the production manager for the firm. In most respects, you regard Chris as
an ideal executive. Chris is cost-conscious and efﬁcient, intelligent, and displays
great initiative and unquestionable integrity. Under Chris’s guidance, output has
increased steadily. Moreover, Chris is a personal friend.

You have called Chris to your office to discuss a problem which has been
bothering you. Despite Chris’s many virtues, there is one major problem. Younger
executives in the department refuse to work for him/ her. They complain that Chris
is authoritarian and never allows them to handle any problem on their own. Chris
is constantly looking over their shoulder and tells them exactly how to conduct even
the most trivial aspects of their job.

Recently many bright young people have left the company. You are determined
that Chris must either reverse this trend or leave the company himself/herself.

You would like to appoint Chris to the vacant position of executive vice-
president of the company. At the same time, you are afraid that you may have to
terminate Chris for the good of the company.

ROLE FOR CONFEDERATE: Production Manager Chris Marshall

You have just been notified that your boss, Pat Jones, the president of the
company, wants to see you in his office. Pat Jones is an old personal friend, and you.
have enjoyed working for him/her.

You are the production manager and productivity has never been higher.
You are very proud of your accomplishments but there is one problem that bothers
you. The quality of lower and middle managers in your department is extremely low.
You have lost several of these people lately, but you were glad to see most of them
go. Most of them were irresponsible and not very bright. It is your feeling that the
company should offer substantially higher salaries in hopes of attracting better
quality personnel. In addition, you feel that they should institute a personnel testing
program to weed out incompetent and irresponsible applicants.

125

BEHAVIORAL POST TRAINING ROLE PLAY

ROLE FOR SUBJECT: Blair Stanley, Department Head

You are Blair Stanley the head of the electrical section in the engineering
Department at the American Construction Company. Pat Burke is one of eight first-
line supervisors who reports to you. Pat’s unit is very productive and his group has
shown steady improvement over the last two years. However, his cooperation with
other supervisors in the section leaves much to be desired. Before you made him
a supervisor his originality and technical knowledge were available to your whole
section. Now he acts like a lone wolf. You’ve asked other supervisors to talk over
certain problems with him but they tell you he offers no suggestions. He tells them
he’s busy or listens disinterestedly to their problems, kids them or makes sarcastic
remarks, depending on his mood. Recently he allowed Terry Smith, one of the
supervisors in another unit, to make a mistake that he could have forestalled by
letting him know the status of certain design changes which he knew about and had
seen. It is expected that supervisors cooperate on matters involving design changes
that affect them. You are meeting with Pat in a few minutes to discuss this matter.

ROLE FOR CONFEDERATE: Pat Burke, Supervisor

You are Pat Burke, a supervisor of the electrical section in the Engineering
Department at the American Construction Company. One junior designer, six
draftsmen, and two clerks report to you. You feel that you get along ﬁne with your
group. You have always been pretty much of an idea person and apparently have
the knack of passing on your enthusiasm to others in your group. There is a lot of
"we" feeling in your unit because it is obvious that your group is the most productive.

The other supervisors in your section do not have your enthusiasm. Some of
them are dull and unimaginative. You used to help them a lot, but you soon found
that they leaned on you and before long you were doing their work. Since you no
longer help the other supervisors your production has gone up.

You did one thing recently that has bothered you. There was a design change
in a set of plans and you should have told Terry Smith (a fellow supervisor) about
it, but it slipped your mind. Terry was out when you had it on your mind and then
you got involved in a hot idea with your junior designer, and forgot all about the
matter with Terry. As a result, Terry had to make a lot of unnecessary changes and
he was quite sore about it. You told him you were sorry and offered to make the
changes, but he turned down the offer.

126

BEHAVIORAL MEASURE

Please rate your own performance in the practice role play using the following scale:

5 - Outstanding use of the skill

4 - Good use of the skill

3 - Average use of the skill

2 - Poor use of the skill

1 - Very poor or no use of the skill

5 4 3 2 1 1. Explained the problem to the employee without hostility.

5 4 3 2 1 2. Criticized the behavior, not the employee.

5 4 3 2 1 3. Avoided general evaluative statements.

5 4 3 2 1 4. Described speciﬁcally what the employee had done
incorrectly.

5 4 3 2 l 5. Avoided making attributions for the causes of the employee’s
behavior.

5 4 3 2 1 6. Asked for and listened openly to the employee’s reasons for
the behavior.

5 4 3 2 1 7. Showed that he/she understood the employee’s feelings.

5 4 3 2 1 8. Asked the employee for his or her ideas on how to solve the
problem.

5 4 3 2 1 9. Asked the employee if there was anything that he/ she could
do to help.

5 4 3 2 1 10. Agreed to review performance at a later date.

5 4 3 2 1 11. Did not rush through the feedback session

5 4 3 2 1 12. Avoided comparing the employee to other employees.

5 4 3 2 1 13. Used Eye contact.

5 4 3 2 1 14. Used appropriate nonverbal behavior.

127

SELF -EFFI CACY A

Listed below are ﬁve situations involving performance feedback. Under the column, CAN DO, place
a check ( ) below the situations in which you feel you could give effective performance feedback. That
is, do you feel you could present the feedback described in such a way that it will increase the
employee’s motivation and desire to improve without offending the employee?

Next, for the situations you checked under the CAN DO column, indicate in the CERTAINTY column,
how certain you are that you could give effective performance feedback (that is how strong is your belief
that you could give the feedback described in such a way that it would increase the employee’s
motivation and desire to improve).

Rate your degree of certainty by recording a number from 0 to 100 using the scale below:

 

0 25 50 75 100
| I I | I
Not Certain Slightly Moderately Highly Absolutely
At All Certain Certain Certain Certain

1. Sue Johnson is an extremely nice, energetic person who is fun to have around. She is always eager
to help out and seems to motivate everyone around her. She is also extremely sensitive and has on
two occasions broken into tears when told that she was doing something wrong. Recently, you
noticed that she has been making an excessive number of personal calls during work hours. How
certain are you that you could provide Sue with effective performance feedback?

 

CAN DO CERTAINTY

2. James Smith is an exceptionally competent employee. He has been with your company for 10 years.
As far as productivity and dependability are concerned he is your top employee. Recently you have
received several complaints from his female co-workers that he makes sexist comments to them.
You are especially concerned about this because the turnover rate for women in his department is
higher than in other departments, and you’re afraid that someone might ﬁle a sexual harassment
charge. How certain are you that you could provide James with effective performance feedback?

 

CAN DO CERTAI NTY

128

Karen Black is one of your assistant mangers. She is your brightest and most highly skilled
employee. Recently you have received several complaints from her employees. It seems that she
is very critical of their work and often leaves them feeling inept, confused or stupid. She never tells
them when they do something right,only when they do something wrong. How certain are you that
you could provide Karen with effective performance feedback?

 

CAN DO CERTAINTY

 

Dan Green is a conscientious hard working employee. When it comes to effort, he tries harder than
any of your other employees. He is also very meticulous when it comes to details, and always turns
in top quality work. Unfortunately, he takes twice as long to ﬁnish his work assignments as anyone
else. This is costing your department a lot of money in overtime. Furthermore, your other
employees have been complaining that Dan doesn’t pull his own weight and that they are getting
tired of having to do extra work because he is always behind. How certain are you that you could
provide Dan with effective performance feedback?

CAN DO CERTAINTY

 

Your organization prohibits smoking in all public areas, therefore, employees are no longer allowed
to smoke at their desks. Smoking is allowed only in the smoking lounge, which is a very small out
of the way room located two ﬂoors up. You have on two occasions caught Tom Wilson smoking
at his desk. Yesterday you overheard him telling another co-worker that he didn’t give a *#@$ !
what you said, no one could take away his rights. How certain are you that you could provide Tom
with effective performance feedback?

 

CAN DO CERTAINTY

129

SELF -EFFI CACY B

Poorly presented performance feedback can result in distrust, hostility, dissatisfaction, and turnover.
Effective performance feedback should be motivational and should encourage development. For each
of the following items please use the scale below:

Strongly Disagree Disagree Neutral Agree Strongly Agree
l

| I I |
1 2 3 4 5

 

1. I am conﬁdent in my ability to give effective negative performance
feedback to others. 1 2 3 4 5

2. I feel certain that when I tell others what they are doing wrong, they
feel motivated to improve. 1 2 3 4 5

3. I think that my skill in giving effective negative feedback could be

improved substantially. 1 2 3 4 5
4. I don’t feel that I am very good at giving effective negative performance

feedback to others. 1 2 3 4 5
5. My negative feedback skills are not as good as I would like. 1 2 3 4 5
6. My ability to give effective negative feedback is better than most peOple’s. 1 2 3 4 5

7. It is very difﬁcult for me to give effective negative feedback to others. 1 2 3 4 5

130

KNOWLEDGE (A)

For each of the items listed below please indicate whether you feel it is an appropriate (A) or
inappropriate (1) example of constructive feedback behavior. In addition, if you feel the behavior is
inappropriate, give a brief explanation why.

I A 1. "You are doing ﬁne, but you could do a little better.’

General evaluative statement. Not spgiﬁg.

 

 

 

I A 2. "Overall, you’re not a bad employee."

General evaluativo statement. Not Specific

 

 

I A 3. "You’ve still got a lot of room for improvement. Look at John and Sue for example.
They haven’t had any problems getting their reports turned in on time.

Compared the employee to other employees.

 

 

 

l A 4. The feedback giver does almost all of the talking.

The feedback giver should ask and listen omnly to the employee’s reasons

 

for Lhe belﬂvior. ask for ideas on how to solve the problem, and ask

 

 

what helshe (the feedback giver) can do to l_Ieln.

 

l>
O\

l>
\1

I>
oo

l>
so

A 10.

131

"I can’t believe you forgot about the meeting. ’I forgot’ is not an acceptable excuse.
It’s time you grew up and stopped being so irresponsible."

Don’t scold or belittle the employee. Explain the problem to the employee

 

without hostilitv.

 

"I can understand you’re having a creativity block, we all get stuck from time to time."

Showed understanding of the employee’s feelings.

 

 

 

"This is the third time this week that you’ve been late coming back from lunch."

Egplained the problem to the employee without hostility.

 

 

 

"What can I do to help you improve your writing skills?

Asked the employee what helshe could do to help.

 

 

 

"I would like to meet with you next Wednesday, between four and ﬁve o’clock to discuss
how the solutions from this meeting are working."

Agpeed to review performance at a later date.

 

 

 

"Jan, have you got a minute?" Why don’t we go get some coffee and donuts in the
employee snack room. "I want to discuss a recent phone conversation I had with one
of your clients."

 

Should discuss the problem in a private location.

132
KNOWLEDGE (B)
Recently, your secretary has been acting rude toward clients. She never smiles, or greets them when
they come into the Ofﬁce. She often acts like She’s too busy to bother with them. Describe below how

you would go about telling her that her performance is unacceptable. Describe in detail how you would
handle the situation (i.e., what you would say to her and in what order you would say it?).

Sub'ects received 1 oint each for includin the followin learnin oints in eir answer.

DO’S

1. Talk with the employee in a private location.

 

2. Use eye contact.

 

3. Be aware of nonverbal behaviors.

 

 

4. Explain the problem to the employee without hostilitv.

 

5. Criticize the behavior, not the omployee.

 

6. Be specific.

7. Ask for and listen oponly to the emplom’s reasons for the behavior.

 

 

 

8. Show that you understand the omployee’s feelings.
9. Ask the employee for his or her ideas on how to solve the problem.
10. Ask the employee if there is anﬂhing that you can do to heln.

11. Agpee to review porformance at a later date.

 

 

 

 

 

 

 

 

 

133

KNOWLEDGE (C)

In the space below, list as many of the learning points that you can remember.

Subjects received 1 point each for listing the following learning points in their answer.

 

DON’TS

1. Use general evaluative statements.

 

2. Scold or belittle the employee because of their actions.

 

3. Make attributions for the causes of the employee’s behavior.

 

4. Compare the employee to other employees.

 

5. Rush through the feedback session.

 

DO’s

1. Talk with the employee in a private location.

 

2. Use eye con—tact.

3. Be aware of nonverbal behaviors.

4. Eyplain the problem to the employee without hostility.

 

5. Criticize the behavior, not the employee.

 

6. Be specific.

7. Ask for and listen oppnly to the employee’s reasons for the behavior.

 

8. Show th_at you understand the employee’s feelipgs.

9. Ask the employee forpis or her ideas on how to solve the problem.

 

 

10. Ask the employee if there is anﬂhing that you can do to help.

 

11. Agpee to review p_erformance at a later date.

 

 

 

 

 

APPENDIX E

APPENDIX E

POST HOC ANALYSES

An Examination of the Interaction Between Vldeotaped Feedback and Self-ratings
One possible explanation as to why videotaped feedback had no main effect
on post training performance is that videotaped feedback may have had a negative
impact on the performance of some subjects and a positive impact on the
performance of others. Observing oneself fail at a task may lower self-efﬁcacy and
subsequent performance. It is also possible that observing oneself fail may create
self-dissatisfactions that serve as motivational inducements for enhanced effort
(Bandura & Cervone, 1983). According to Bandura (1986), social cognitive theory
postulates two cognitive mechanisms that inﬂuence motivation and behavior. The
first operates anticipatorily through self-efﬁcacy and outcome expectations. The
second, labeled a self-regulatory mechanism (Bandura, 1986), operates through
internal standards and self-evaluative reactions to one’s performance. When people
commit themselves to explicit standards, perceived negative discrepancies between
their actual performance and their internal standard creates self-dissatisfactions that
serve as motivational inducements for enhanced effort. Past research supports the
existence of self-regulatory mechanisms. For example, research has shown that:

(a) individuals react to initial failure to reach a performance standard by intensifying

134

135

their effort, whereas repeated failures lead to giving up the standards (Campion &
Lord, 1982), (b) the higher one’s self-dissatisfaction with substandard performance
and the stronger one’s perceived self-efﬁcacy for goal attainment, the greater the
subsequent intensification of effort (Bandura & Cervone, 1983), and (c) subjects who
receive negative feedback perform at higher levels on subsequent trials than subjects
who receive positive feedback (Podsakoff & Farh, 1989).

While no speciﬁc goal or standard was assigned in this study, subjects were
asked to try to include as many of the learning points as possible in their role plays.
In addition, subjects in this study were asked to rate their performance on the
practice role play. Therefore, a post hoc analysis was performed to examine whether
self-evaluative reactions to one’s performance (i.e., self-ratings of one’s performance)
moderate the impact of videotaped feedback on post training performance. This
post hoc prediction was tested using a hierarchical moderated regression analysis in
which post training role play performance was regressed on: (1) pre-training role
play performance, (2) videotaped feedback, (3) self-rating (SRT), and (4) the
interaction between videotaped feedback and one’s self-rating (VFSRT). See Table
15.

As predicted the interaction between videotaped feedback and self-rating was
signiﬁcant. Subjects who received videotaped feedback and gave themselves lower
self-ratings had greater post training performance than subjects who gave themselves
higher self-ratings. The opposite was true for subjects who did not receive
videotaped feedback. That is, subjects who gave themselves higher self-ratings had
higher post training performance than subjects with gave themselves lower self-

ratings. This interaction is displayed in Figure 17.

136

 

 

 

1:23:32}: Results for Videotaped Feedback and Self-rating'.

Step Variable R R2 A R2

1. Pre-training Role Play Performance .275 .076 .076***
2. Videotaped Feedback .279 .078 .002

3. Self-rating .283 .080 .002

4. Videotaped Feedback x self-rating .319 .102 .022"‘

* p < .05.
*** p < .001.

aCoefﬁcient alpha for the self-rating measure was .78.

56

 

 

Low

55 Self-rating
Performance 64

in 53 ngh

If- I

Tralnlng 8° rat "9
52
51

No Vldeotaped Vldeotaped

Feedback Feedback

Figure 17. Jnteraction between videotaped feedback and self-rating. (Regression
equation: Y = .29 (PRE-TR PERF) + 17.0 (VF) + .19 (SRT) - .33 (VFSRT) +
28.97.)

137

An Examination of the Interaction Between Videotaped Feedback, S elf-ratings and S elf-
eﬂicacy

An additional regression analysis was performed to examine whether self-
efficacy interacts with feedback Sign (self-ratings) and videotaped feedback to
inﬂuence subsequent performance. In other words, post training role play
performance was regressed on: (1) pre-training role play performance, (2) videotaped
feedback, (3) self-rating (SRT), (4) self-efficacy (SE), (5) the interaction between
videotaped feedback and one’s self-rating (VFSRT), (6) the interaction between
videotaped feedback and self-efﬁcacy (VFSE), and (7) the triple interaction between
videotaped feedback, self-rating and self-efficacy (VFSRTSE). The results of this

regression analysis are shown in Table 16.

 

 

 

Rzggssign Results for Videotaped Feedback, S elf-eﬁficacy and S elf-ratinga.

Step Variable R R2 A R2

1. Pre-training Role Play Performance .261 .068 .068***
2. Videotaped Feedback .269 .072 .004

3. Self-rating .276 .076 .004

4. Self-efﬁcacy .394 .155 .07 ***
5. Videotaped Feedback x self-rating .411 .169 .0141'
6. Videotaped Feedback x self-efﬁcacy .428 .183 .0141'
7. Videotaped Feedback x self-rating x self-efﬁcacy .445 .198 .0151’

1’ p < .10.

***p < .001.

138
A marginally significant triple interaction was found (er = .015, p < .10)
such that the lower one’s self-rating and the higher one’s self-efﬁcacy, the greater
one’s post training performance. Thus, the results of this study are similar to that
of Bandura and Cervone (1983) who found that the higher one’s self-dissatisfaction
with substandard performance and the stronger one’s perceived self-efﬁcacy for goal
attainment, the greater the subsequent intensiﬁcation of effort. This triple

interaction is displayed in Figure 18.

69 ngh SE / Low SET
58
67
Low SE / High SRT
Performance 58
in
65
Training
54
53 ngh SE / High SRT
T" Low SE / Low SRT
52 _—

 

 

 

No Videotaped Videotaped
Feedback Feedback

Figure 18. Triple interaction between videotaped feedback, self-efficacy and self-
rating. (Regression equation: Y = .23 (PRE-TR PERF) + 8.8 (VF) + .05 (SRT)
+ .45 (SE) - .15 (VFSRT) + 1.48 (VMSRT) - .04 (VFSESRT) + 42.3.)

139

An Examination of the Relationship Between Self-ratings and the Rater’s Ratings

An alternative explanation as to why videotaped feedback had no main effect
on post training role play performance is that subjects were not able to make
accurate evaluations of their own performance. In order to test this prediction self-
ratings on the practice role play were correlated with performance ratings on the
practice role play. Performance ratings on the practice role play were obtained from
one of the trained raters who evaluated a sample (N=127) of the videotaped
practice role plays using the same 14-item behavioral rating scale used to evaluate
the pre-training and post training role plays (67 of the 194 videotaped practice role
plays were either taped over or inaudible). The results of this analysis revealed a
correlation coefficient of (r = .30, p < .001) suggesting a signiﬁcant but low level
of agreement between the performance ratings of the trained rater and subject self-
ratings. Further analysis revealed that subjects in the videotaped feedback
conditions were no more or less accurate than subjects in the no-videotaped
feedback conditions. More specifically, the correlation between self-ratings and
performance ratings was (r = .29, p < .01) for subjects in the videotaped feedback
conditions and (r = .30, p < .01) for subjects in the no videotaped feedback
conditions. In addition self-ratings on the practice role play were signiﬁcantly
related to videotaped feedback condition (r = .15, p < .05) such that subjects in the
videotaped feedback conditions gave themselves Slightly higher ratings (Mean = 51.6,
SD = 5.6) than subjects in the no videotaped feedback conditions (Mean = 49.8, SD

= 6.7). Correlations are shown in Table 17.

140

Table 17
Means, standard deviations, and intercorrelations between training treatment, self-ratings
and training outcome variables.

 

Variable M SD 1 2 3 4 5 6 7 8
1. Videotaped
Modelingb
2. Videotaped
Feedback”
3. Self-ratings 50.73 6.20 .01 .15‘ ——
4. Self-efﬁcacy (A) .00 5.56 .01 .08 .3 m ---
5. Knowledge 28.94 351 -.06 .05 .02 .20“ ~-

6. Pre-training role
play performance 41.55 6.11 -.16‘ .09 .17" .17‘ .06 ---

7. Practice role
play performance 51.43 6.14 .15“ .00 .30W -.01 .13 .11

8. Post training role
play performance 54.34 6.63 25°" .07 .10 .33m .32m .27m .27‘“ -—-

 

bVideotaped modeling and videotaped feedback are dichotomous variables coded 0 = without, 1 = with.
t
p < .05.
" p < .01.
"” p < .001.

An Examination of a Suppressor Eﬁ‘ect

Since post training knowledge was positively related to post training role play
performance (r = .32, p< .001), and the combined treatment condition was found
to have a positive impact on post training role play performance (13 = .26, p < .05)
and a negative impact on post training knowledge ()3 = -.30, p < .05), the true
impact of the combined treatment condition on post training role play performance
may be suppressed because of the negative impact it has on knowledge. In order to
examine the possibility of a suppressor effect, an additional analysis was performed
to examine the impact of the combined treatment condition on post training role

play performance controlling for post training knowledge. Speciﬁcally, post training

141
role play performance was regressed on: (1) pre-training role play performance, (2)
knowledge, (3) videotaped modeling, (4) videotaped feedback, (5) the interaction
between videotaped modeling and videotaped feedback.
Table 18

Regression Results for the Impact of Videotaped Modeling and Videotaped Feedback
on Post Training Role Play Performance Controlling for Post Training Knowledge

 

 

Step Variable B R R2 A R2
1. Pre-training Role Play Performance .29 .249 .062 .062**"'
2. Post training knowledge .37 .398 .158 096*“
3. Videotaped Modeling .10 .514 .264 .106**"‘
4. Videotaped Feedback -,17 .516 .267 .003
5. Videotaped Modeling x Videotaped Feedback .39 .561 .315 .048***
"‘ p < .05.
** p < .01.
*** p < .001.

The results shown in Table 18 support the existence of a suppressor effect.
When the effects of post training knowledge are controlled, the effect size for the
combined treatment condition increases (sr’2 = .048, p < .001, versus sf = .023, p <
.05).
An Examination of the Interaction Between Self-eﬂicacy and Training Treatment

Research has shown that low self-esteem subordinates were more likely to
imitate or model their supervisors than high self-esteem subordinates (Weiss, 1977;
1978). Since self-efficacy is a similar construct to self-esteem, it is suggested that low
self-efficacy subjects in this study may beneﬁt more from videotaped modeling than

high self-efficacy subjects. Research has also shown that the performance of low

142
self-esteem individuals, but not high self-esteem individuals, decreases under
conditions of high self-focus (a mirror, an audience or a videotape camera)
(Brockner, 1979). This finding suggest that videotaped feedback may have a
negative effect on the performance of low self-efficacy individuals, but not high self-
efficacy individuals. In order to test these predictions two hierarchical moderated
regression analyses were performed. In the first equation performance on the post
training role play was regressed on: (1) pre-training role play performance, (2)
videotaped modeling, (3) self-efficacy and (4) the interaction between videotaped
modeling and self-efficacy. In the second equation performance on the post training
role play was regressed on: (1) pre-training role play performance, (2) videotaped
feedback, (3) self-efﬁcacy, and (4) the interaction between videotaped feedback and

self-efficacy. The results of these analyses are shown in Table 19 and Table 20.

Table 19
Regression Results for the Interaction Between Vldeotaped Modeling and Self-efﬁcacy

 

Step Variable R R2 A R2
1. Pre-training Role Play Performance .261 .068 .068***
2. Videotaped Modeling .386 .149 121*“
3. Self-efﬁcacy .476 .227 .078***
4. Videotaped Modeling x Self-efﬁcacy .477 .228 .001

 

***p < .001.

143

Table 20
Regression Results for the Interaction Between Videotaped Feedback and Self-eﬁ‘icacy

 

 

 

Stgp Variable R R2 A R2
1. Pre-training Role Play Performance .261 .068 068*"
2. Videotaped Feedback .269 .072 .004
3. Self-efficacy .393 .154 082*“
4. Videotaped Feedback x Self-efﬁcacy .422 .178 .024"'
* p < .05.
*** p < .001.

N 0 significant interaction was found between videotaped modeling and self-
efficacy, however, there was a signiﬁcant interaction between videotaped feedback
and self-efficacy, such that low self-efﬁcacy individuals performed better in the
videotaped feedback conditions than the no videotaped feedback conditions and high
self-efficacy individuals performed better in the no videotaped feedback conditions

than the with videotaped feedback conditions. See Figure 19.

144

 

 

57
High
56 Self-efficacy
Performance 65
in Low
54 -
Training Self efﬁcacy
53
52
No Vldeotaped Vldeotaped

Feedback Feedback

Figure 19 Interaction between videotaped feedback and self-efficacy. (Regression
equation: Y = .24 (PRE- TR PERF) + 6.5 (VF) + 4.6 (SE)- 4.2 (VFSE) + 44.28.)

An Examination of the Interaction Between Feedback Experience and Training
Treatment

A final set of analyses were performed to examine the possibility that
experienced feedback givers would be less likely to beneﬁt from videotaped
modeling and videotaped feedback than inexperienced feedback givers. This
prediction is based on the assumption that experienced feedback givers have already
established patterns of interacting with other and may be less likely to learn from
watching their mistakes. In order to test these predictions two hierarchical
moderated regression analyses were performed. In the ﬁrst equation performance
on the post training role play was regressed on: (1) pre-training role play

performance, (2) videotaped modeling, (3) feedback experience and (4) the

 

145

interaction between videotaped modeling and feedback experience. In the second
equation performance on the post training role play was regressed on: (1) pre-
training role play performance, (2) videotaped feedback, (3) negative feedback
experience (NFBE), and (4) the interaction between videotaped feedback and
feedback experience (VFNFBE). The results of these analyses are shown in Table
21 and Table 22.

Table 21

Regression Results for the Interaction Between Videotaped Modeling and Feedback
Experience

 

 

 

Step Variable R R2 A R2
1. Pre-training Role Play Performance .267 .071 .071***
2. Vid60t3p6d MOdCling .422 .178 .107***
3. Feedback Experience .426 .181 .003
4. Videotaped Modeling x Feedback Experience .433 .187 .006
* p < .05.

** p < .01.

*** p < .001.
Table 22

Regression Results for the Interaction Between Vldeotaped Feedback and Feedback
Experience

 

 

Step Variable R R2 A R2
1. Pre-training Role Play Performance .267 .071 .071***
2. Videotaped Feedback .269 .072 .001*
3. Feedback Experience .272 .074 .002
4. Videotaped Feedback x Feedback Experience .327 .107 .033*

* p < .05.

***p < .001.

146
A signiﬁcant interaction between videotaped feedback and negative feedback
experience was found such that videotaped feedback had a positive impact on the
performance of individuals with little or no feedback experience and a negative
impact on the performance of individuals with greater negative feedback experience.
Videotaped modeling also had a greater impact on inexperienced individuals,

although this difference was not significant (p > .10). See Figure 20.

 

 

57
66
Performance Low Feedback
in 55 Experience
Training
54 High Feedback
Expeﬁence
No Vldeotaped Vldeotaped
Feedback Feedback

Figure 19. Interaction between videotaped feedback and negative feedback
experience. (Regression equation: Y = .29 (PRE-TR PERF) + 1.26 (VF) + .10
(NFBE) - .16 (VFNFBE) + 41.87.)

 

 

 

 

 

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