Modeling and Self-Efficacy: A Test of Bandura's Model

Transcription

1 JOURNAL OP SPORT PSYCHOLOGY, 1985, 7, Modeling and Self-Efficacy: A Test of Bandura's Model Edward McAuley Kansas State University Female undergraduate students (N = 39) were assigned to one of three conditions: aided participant modeling (APM), unaided participant modeling (UPM), or a control group followed by practice trials of a gymnastic skill. Subjects in both modeling groups reported higher selfefficacy expectations and lower anxiety ratings than the control group following treatment. The aided participant modeling group scored higher on the performance measure than did the unaided participant modeling group, and both modeling groups scored higher than the control group. Path analytic techniques were employed to test the fit of the data to Bandura's (1977a) self-efficacy model and an anxiety reduction model. Self-efficacy was a significant predictor of skill performance, but the anxiety-performance path was nonsignificant. Although Bandura's model did not fully explain the fit of the data to the fully recursive model, it proved to be a more parsimonious explanation of behavior change than was the anxiety reduction model. Despite the limitations imposed on the data by the small sample size, the present study suggests that self-efficacy is an influential determinant of motor skill acquisition. Bandura (1977a) has conceptualized behavioral change as being mediated by a common cognitive mechanism, self-efficacy. Self-percepts of efficacy are concerned with an individual's belief that helshe can successfully execute the behavior requi1.d to produce a certain outcome. Efficacy expectations serve to determine an individual's choice of activity, the amount of effort that will be expended, and persistence in the face of obstacles or aversive stimuli. Bandura states that self-efficacy cognitions are situation-specific rather than reflecting a global personality trait. Empirical support for self-efficacy can be found in a number of studies by Bandura and his colleagues with snake phobics (e.g., Bandura & Adams, 1977; Bandura, Adams, & Beyer, 1977; Bandura, Adams, Hardy, & Howells, 1980). Increases in self-efficacy have been induced through a variety of treatment modalities including performance accomplishments, vicarious experience, verbal persuasion, and emotional arousal. Performance based treatments appear to be the most influential sources of efficacy information. Participant modeling, in which the subject observes a model successfully complete a task This article is based on a doctoral dissertation presented to the Graduate College of the University of Iowa. Appreciation is extended to Diane Gill and Dan Russell for assisting with the early stages of this research, and to Deborah Feltz and two anonymous reviewers for their helpful suggestions and comments on an earlier draft of this manuscript. Requests for reprints should be sent to Edward McAuley, Dept. of PEDLS, Aheam Gymnasium, Kansas State University, Manhattan, KS

2 284 McAULEY and then is physically guided through the task by the model, has consistently been reported as the most successful method of enhancing efficacy expectations (Bandura & Adams, 1977; Feltz, Landers, & Raeder, 1979). Since self-efficacy cognitions are proposed by Bandura to have motivational effects, such cognitions should also be an important component of motor skill acquisition. Several studies have examined the effects of efficacy expectations on motor performance (e.g., Feltz et al., 1979; Weinberg, Gould, Yukelson, & Jackson, 1981; Weinberg, Yukelson, & Jackson, 1979). In general, the results of these studies have shown increases in selfefficacy expectations to be positively related to increases in the quality of sport performance. Feltz and her colleagues (1979) conducted a study that examined the effects of different types of modeling on self-efficacy cognitions and back-diving performance. Participant modeling was found to be significantly more successful in raising efficacy expectations and improving performance than either live or videotape modeling. Bandura's self-efficacy theory predicts that increases in self-efficacy produced by various treatment modalities lead to both behavior change and anxiety reduction. Recent studies by Feltz (1982), Feltz and Mugno (1983), and Schunk (1981) have tested the causal model suggested by Bandura. All of these studies found self-efficacy to be an important determinant of performance, but they also found direct effects of treatment on performance (Schunk, 1981) and of past performance on future performance (Feltz, 1982; Feltz & Mugno, 1983). Other theorists have criticized Bandura's model of behavioral change as it applies to avoidance behavior, arguing that the anxiety response habit is the direct cause of both self-efficacy expectations and behavioral change (Borkovec, 1978; Eysenck, 1978; Wolpe, 1978). Eysenck has referred to efficacy expectations as nothing more than an "epiphenomenal" by-product, basing his argument in dual process theory Wowrer, 1947) in which anxiety extinction directly eliminates avoidance behavior. Borkovec (1978) stated that dual process theory may well be a more parsimonious explanation for avoidance behavior if the assessment of self-efficacy adds little to behavioral prediction beyond that already accounted for by anxiety reduction. Consequently, we are faced with two competing theoretical models that attempt to explain behavioral change in avoidance behavior. Bandura argues that behavioral change is determined by self-efficacy expectations and that efficacy cognitions also lead to anxiety reduction. Eysenck (1978) suggests that anxiety reduction mediates behavior change and that self-efficacy cognitions are merely coeffects of reduction in anxiety. The present study was designed to further investigate the role of modeling as a teaching modality for motor skill acquisition and to evaluate the roles of anxiety and self-efficacy as determinants of skill acquisition. Subjects Method Female undergraduate students (N = 39) enrolled in physical education skills classes volunteered as subjects for this study. Bandura has taken great care to ensure that subjects selected for treatment were highly anxious and avoidant of the behavior under study. For this study, only those subjects who had had no previous gymnastics experience or training were selected for participation. It was reasoned that this would provide a suffi-

3 TEST OF BANDURA'S MODEL 285 ciently anxious sample when confronted with the task. Subjects were randomly assigned, one to each of the three experimental conditions described below, resulting in 13 subjects in each condition. All were treated and tested individually with no other subjects present. Task The target task in this study was a dive forward roll mount onto a gymnastic balance beam from a springboard. From a short approach run, the subject was required to use a two-footed takeoff from the springboard, place her hands on top of the beam, elevate the hips as high as possible while piking at the waist (bending with straight legs), tuck the head into the chest, and roll forward with legs apart to a sitting position on the beam. Although it appears dangerous and difficult to a novice, this task is actually a rather basic trick to which many variations can be added to increase the difficulty rating (Murray, 1979). The beam was 4 in. wide and was set at a height of 3 ft 4 in. (8 in. below competition height). Foam tumbling mats were placed on either side of the beam to avoid risk of injury to the subjects if they should fall. A 314 in. rubber pad was attached to the surface of the beam in order to soften its impact on the neck and shoulders. Experimental Conditions Two modeling groups were used in this study. One group received physically guided participant modeling, hereafter referred to as aided participant modeling (APM), and the other group received live modeling with practice, heder called unaided participant modeling (UPM). These treatment conditions are described below. Aided Participant Modeling (APM). The model described the target task in detail and then gave a physical demonstration. Both the description and the demonstration were repeated once again. Afterward, each subject was asked to repeat the verbal description of the task in order to show she understood the requirements. The subject was then allowed four practice trials during which the model provided her with both verbal feedback and physical assistance. Four trials were considered sufficient by a gymnastic expert for the subjects to gain a kinesiological understanding of the task. As the subject began to roll forward on the beam, the model supported her hips to help slow them down onto the beam. The model then grasped the subject's arm, bringing the upper body forward and into a sitting position. After each practice trial the model gave feedback on the relative correctness of the attempt. Unaided Participant Modeling WM). Subjects in the UPM underwent a procedure similar to that of the APM group, except that no physical assistance was provided by the model. Subjects were allowed four practice trials following the two verbal descriptions and physical demonstrations by the model. Traditionally, live modeling treatments have comprised the subject's viewing a model without practice. But since practice trials were allowed in this study, this treatment group was labeled unaided participant modeling WPM).' Control Group. Subjects assigned to the control group were shown a short instructional film on uneven parallel bar exercises and informed that the experimenter was examining the effect of the viewing of gymnastic films upon the learning of a task on another 'The renaming of the modeling conditions was suggested by an anonymous reviewer who felt that unaided and aided participant modeling more accurately reflected the process being carried out in each condition.

4 286 McAULEY piece of equipment. The film was shown twice and then subjects were given a detailed description of the task and asked to repeat the description. Subjects were then allowed four practice trials with no physical assistance or verbal feedback. Models Two female undergraduate students sewed as the models in the modeling groups. Both models had had over 5 years of competitive gymnastic experience and had been teaching gymnastics for the past 2 years. Each model was assigned to a similar number of APM and UPM subjects. After having participated in several training sessions prior to the study, both models were considered to be equally competent. Dependent Measures Gymnastic Eficacy Measure (GEM). The GEM was designed for this study to assess efficacy expectations for gymnastic performance. The measure was constructed in a manner similar to that employed by Bandura (1977a). Six gymnastic activity items for balance beam were listed in hierarchical order of difficulty, with the final item being the target task. The items were ranked according to difficulty by eight collegiate gymnasts, who were in complete agreement about the rank ordering of the tasks in terms of difficulty level. For tasks that the subjects felt they could perform, they rated on a 100-point probability scale how certain they were about performing them. A rating of 100 points indicated absolute certainty, whereas a rating of 10 points indicated the subject was highly uncertain she could perform the task. Self-efficacy cognitions were assessed by totaling these certainty ratings across items and then dividing by the total number of items on the measure. For example, a total confidence score of 300 divided by the total number of items on the scale (6) would result in a score of 50 for strength of self-efficacy. For the purpose of this study, only the self-efficacy for the target task was used in the analyses since the other items were considered to be more generalized measure^.^ A detailed descrip tion of the tasks on the GEM was given to any subject who was uncertain as to what any task entailed. Competitive State Anxiety Inventory (CSAI). The CSAI is a self-report state anxiety inventory, a shortened 10-item version of the Spielberger, Gorsuch, and Lushene (1970) State Anxiety Inventory. It required the subject to indicate how she was currently feeling, using a Cpoint scale for each item. For example, the subject was asked to respond to the statement "I am feeling calm" by indicating whether she was feeling very calm, not calm at all, or somewhere in between. Reliability and validity for the CSAI in competitive sport settings have been well documented (see Gruber & Beauchamp, 1979; Martens, Burton, Rivkin, & Simon, 1980). Performance. The performance measure was based on the subjects' performance of three forward roll mounts onto the beam following the experimental treatment. The three performance mounts were lfideotaped and rated by three independent judges. This procedure assured that the judge$ remained blind to the treatment conditions. The judges scored each performance attempt on a 5-point scale, ranging from 1 point for approaching and bouncing on the springboard but failing to begin rotation, to a score of 5 points for The data were analyzed using the target task efficacy score and the total GEM score separately as the self-efficacy measure. Results of the data analysis were almost identical, and as recommended by an earlier reviewer, only the target task was used for the final analyses. Items included on the Gymnastic Efficacy Measure are available on request from the author.

5 TEST OF BANDURA'S MODEL 287 completing the mount in piked position and finishing in a sitting position astride the beam. Interjudge reliability was calculated at.91 using the Kappa coefficient (see Cohen, 1960) over all trials. Any disagreement among judges was reconciled by reviewing the performance, comparing it to the judging criteria, and discussing the mount in question. All disagreements were reconciled within a few minutes. The scores for each mount were summed together to give a final performance score. Subjects also completed a scale following the three performance trials which indicated their perceived level of success on the gymnastic task. Subjects were asked, "How successful do you think you were in the performance of your last three attempts?" Responses were indicated on a 9-point Likert scale, with 1 indicating the subject felt she had been very unsuccessful and 9 indicating the opposite extreme. Procedure Upon arriving at the gymnasium, each subject was asked to complete an informed consent form, the Gymnastic Efficacy Measure (GEM), and the Competitive State Anxiety Inventory.(CSAI). The subject was then assigned to an experimental treatment. After completing the treatment phase (i.e., following the fourth practice trial), each subject once again completed the GEM and CSAI. All subjects were then allowed three performance trials without physical assistance or verbal feedback. The performances were videotaped, and the self-rating scale was completed following performance. Subjects were then debriefed and told the real purpose of the study. Any subject who had failed to complete any of the performance trials was then physically guided through the task following debriefing. This ensured that all participants achieved some degree of success. Results The data were analyzed in two phases. The first phase examined the effects of the treatment conditions upon self-efficacy, anxiety, performance, and the self-rating of performance. The second phase of the analysis explored the fit of these data to Bandura's (1977a) model of behavioral change and the alternative anxiety based model offered by Eysenck (1978). Effects of the Experimental Treatments One-way ANOVAs were first conducted upon the pretreatment dependent variables of self-efficacy expectations and anxiety. No significant differences were found among the treatment groups on any of the pretreatment dependent variables. The groups were therefore assumed to be equal prior to treatment, and subsequent analyses were conducted on the posttreatment measures only. The pre- and posttreatment means for anxiety, selfefficacy, and performance are shown in Table 1. As can be seen, anxiety decreased over time for the two modeling groups but increased over time in the control group. A one-way MANOVA tested for differential effects of the two models on the posttreatment dependent variables. The overall MANOVA was nonsignificant. A one-way MANOVA was used to examine differences among the treatment groups on all of the dependent measures. The overall MANOVA3 was significant, F(8, The F statistics reported in the MANOVAs are F approximations based on Witks's Lambda Criterion.

6 288 McAULEY Table 1 Descriptive Statistics for Anxiety, Efficacy Expectations, and Performance Anxiety (Pre) Anxiety (Post) Treatment M SD M SD APM UPM Control Efficacy (Pre) Efficacy (Post) M SD M SD APM UPM Control Performance M SD APM UPM Control 66) = 8.96, p < Subsequent univariate analyses revealed significant differences among groups for the following: self-efficacy, F(2, 36) = 9.58, p <.001; anxiety, F(2, 36) = 3.67, p <.05; self-rating, F(2, 36) = 15.67, p <.0001; and performance, F(2, 36) = 44.21, p <,0001. Duncan's multiple range tests were used to further investigate differences among the groups. Both modeling groups exhibited significantly higher efficacy expectations and significantly lower anxiety levels than did the control <.05; see Table 1). Differences between the modeling groups on efficacy expectations and anxiety were not statistically significant. The APM group performed significantly better (M = 11.46) than the UPM group (M = 9.07), which in turn performed significantly better than the control group (M = 5.38). All comparisons were significant at the.05 level. The APM group rated their performance significantly higher (M = 6.07) than the UPM group (M = 4.53), who in turn rated their performance significantly higher than the control group (M = 3.15). In summary, the modeling treatments resulted in increased efficacy cognitions, lower anxiety, and qualitatively better performance when compared to a control group. The two modeling conditions did not differ significantly in either self-efficacy or anxiety but the APM group performed significantly better following treatment than did the UPM group. Path Analysis Before progressing further with the path analyses of the data, it is appropriate to proffer a warning about the interpretation of these results. The use of path analytic techni-

7 TEST OF BANDURA'S MODEL 289 Table 2 Correlations Among Efficacy, Anxiety, and Performance Posttreatment Anxiety Efficacy Performance Anxiety Efficacy Performance ques with such a small sample size and a number of predictors is problematic (see Kerlinger & Pedhazur, 1973). One should therefore interpret the results of these analyses with some caution. The correlation matrix to be analyzed is shown in Table 2. The measures of selfefficacy and anxiety used in the analyses were posttreatment measures. In computing the correlations, the treatment group variable was dummy-coded into two variables, aided participant modeling (treatment 1 in Figures 3 and 4) and unaided participant modeling (treatment 2 in Figures 3 and 4). Treatment 1 represents a contrast between the aided participant modeling condition and the other two conditions, whereas the treatment 2 variable contrasts the unaided participant modeling condition and the other conditions. The judges' rating of performance was used to represent the performance construct, since it was felt that this measure provided an objective indicator of the person's performance on the task. Path analyses were then conducted to compare the ability of the self-efficacy model proposed by Bandura (1977a) and the anxiety-reduction model favored by Eysenck (1978) to explain the correlations shown in Table 2. In conducting these analyses, the theoretical models suggested by Bandura (see Figure 1) and Eysenck (see Figure 2) were compared to their respective fully recursive models (i.e., one that includes all possible pathways among variables, see Figures 3 and 4). Two techniques were used to compare these models to the fully recursive model (see Pedhazur, 1982, for a more detailed discussion). First, a chi-squared goodness-of-fit statistic was computed that indicated how well each model fit the data in comparison to the fully recursive model. Since the fully recursive model contains all possible pathways among the variables, it can explain all the correlations among the variables. A second measure of the goodness of fit, the Q coefficient (Pedhazur, 1982), was also calculated. If the chi-square is nonsignificant, this means that the data fit the proposed model. Therefore, this chi-square test also represents the overall ability of the model to account for the correlations shown in Table 2. The degrees of freedom for this chi-square test are equal to the number of overidentifying restrictions in the model (i.e., paths set at zero in the model being tested). For example, in Bandura's model the df = 3 since three possible paths are omitted that are present in the fully recursive model (compare Figures 1 and 3) One problem with the above chi-square test is that it is affected by the sample size. In the present context, the small sample size could lead to a model that provides a relatively poor fit of the data but still results in a nonsignificant chi-square, e~roneously indicating that the model fit the data. Pedhazur (1982) therefore recommends also exam-

8 McAULEY Treatment 1 Performance Treatment 2 Figure 1 - Bandura's model. The correlations are zero-order correlations with an asterisk (*) indicating a probability level of p <.05. The U statistic indicates the residual variance unexplained by the variables in the model at that point (Also true for Figure 2.) Treatment 1 Treatment 2 Performance Figure 2 - Anxiety Reduction model. (See note, Figure 1.) ining the Q coefficient for the model, since it is not affected by sample size. The coefficient represents the ratio of the variance explained by the theoretical model relative to that explained by the fully recursive model. Q can vary from 0 to 1, with values close to 1 indicating that the theoretical model can explain nearly all of the explainable variance in the dependent or endogenous variables. Bandura's model predicts that treatment will have a direct effect on efficacy and an indirect effect on performance through the direct path between efficacy and performance. These predicted pathways were all statistically significant. A further prediction made by Bandura (1977a) is that increases in self-efficacy should result in a decrease in anxiety. This path was also statistically significant. Thus, we have some initial support for Bandura's theoretical model of behavioral change. Examination of the overall fit of Bandura's model to the data provided further support for Bandura's contention that self-efficacy is an important determinant of behavior

9 TEST OF BANDURA'S MODEL Figure 3 - Fully Recursive model (Bandura). An asterisk indicates a significant correlation (p <.05). The U statistic indicates the residual variance unexplained by the variables in the model at that point. (Also true for Figure 4.) Figure 4 - Fully Recursive model (Anxiety Reduction). (See note, Figure 3.) change. However, the chi-square goodness-of-fit test resulted in a significant value, x2 (3) = 15.20, p <.01, indicating that Bandura's model did not completely explain the relationships among the variables. The Q ratio for Bandura's model was.426. Although Bandura's model did not adequately fit the data, the direct path between efficacy and performance and the indirect path between treatment and performance via efficacy were significant. However, the direct path between the treatment variables and performance was not only significant but also stronger than the efficacy-performance path. The expected path between efficacy and anxiety in the full model was nonsignificant. Eysenck suggests that self-efficacy is merely an epiphenomenon or by-product of anxiety reduction, and that changes in behavior are determined by the mediation of anxiety between the treatments and behavior. Figure 2 presents this model and indicates that, consistent with the model, significant paths were found between the treatments and anxiety, anxiety and efficacy, and anxiety and performance. Once again, the direct treatrnent-

10 292 McAULEY performance path was significant. The anxiety-performance path, although significant, was not as strong as one would expect if anxiety is to be considered the sole detehinant of behavioral change. Comparison of this model to the fully recursive model produces x2 (3) = 123.9, p <,0001, and Q =.032, suggesting that the model proposed by Bandura (1977a), provides a better fit to the data than the anxiety-reduction model. Indeed, in considering Figure 4, it can be seen that the anxiety-performance path is nonsignificant in the full model (i.e., when self-efficacy expectations are statistically controlled). Discussion The present study was designed to empirically evaluate Bandura's theory of behavioral change in an experimental sport setting. According to the theory, one of the key determinants of behavioral change is selfefficacy (Bandura, 1977a). Self-efficacy is thought to influence persistence, emotional arousal, and ultimately behavior. Self-efficacy information is obtained from a number of different sources, the most influential being those that are performance based (e.g., participant modeling). This study contrasted the effects of aided participant modeling (APM), unaided participant modeling (UPM), and a control condition on self-eff~cacy expectations, anxiety, and the acquisition of a motor skill. The results generally supported previous research, with subjects in the modeling groups expressing stronger efficacy expectations and lower levels of anxiety, as well as performing better on a gymnastic task than the control group. The substantial overlap between the two modeling treatments probably accounts for the lack of significant differences in efficacy perceptions and anxiety between these two modeling groups. Had there been a "traditional" live modeling group (i.e., observing a model perform but no opportunity for practice), the expected differences among the groups reported elsewhere in the literature (Bandura, 1977a; Feltz et al., 1979) may have materialized. Additionally, one must consider the size of the sample used in the experiment. Although the means were in the expected direction, having only 13 subjects in each cell detrimentally affects the statistical power. As a mode of instruction, aided participant modeling clearly produced a higher standard of performance regardless of what mediated between the treatment and the performance. This finding is consistent with the findings of Feltz et al. (1979) for a diving task and Bandura and Adams (1977) with snake phobics. Subjects in the APM group rated their performance higher than those in the UPM modeling group, and both modeling conditions rated their performances higher than those in the control group, suggesting that the modeling treatments made the subjects feel more competent and satisfied with their performance than did those subjects in the control group. Theoretically relevant relationships among variables in Bandura's model were examined in this study and the results replicated those found in other studies (Bandura et al., 1977; Bandura & Schunk, 1981; Feltz et al., 1979). High self-efficacy expectations were negatively correlated with anxiety and positively related to performance scores. Anxiety and performance were also negatively related. In order to explore these relationships more fully and to compare Bandura's model to that proposed by Eysenck (1978), path analytic techniques were employed. Although path analysis is not a statistical tool with which to prove or disprove theoretical models, it is considered a potent method for rejecting untenable models (Kerlinger & Pedhazur, 1973). The data from the present study were found to be compatible with previously reported

11 TEST OF BANDURA'S MODEL 293 findings (e.g., Bandura, 1977a) in that efficacy cognitions were significant predictors of performance of a motor skill and mediated between modeling treatments and performance. This is not to say that the model presented by Bandura is complete. As Bandura has recently stressed, self-efficacy is a common mechanism in the mediation of behavior and as such should not be expected to fully explain human behavior (Bandura, 1984). How human behavior is determined can encompass many forms and consequently can be mediated by many diverse mechanisms (Bandura, 1977b, 1984). Mechanisms such as self-evaluation, goal-setting, and self-efficacy are a few of the mediating variables recently reported to exert significant influence on performance (Bandura & Cervone, 1983). Thus, the results of the present study offer confirmatory support for self-efficacy being a significant predictor of performance in the motor skill domain. How can one explain the direct effect of treatment upon performance in these data? It is quite possible that subjects in the APM group received different physical and cognitive informational cues from the UPM and control groups. Consequently, this information may have been processed independently of efficacy information. It is difficult to know for certain if such a process was actually taking place, and future research must address the possibility of treatments having both a direct effect on behavior and an indirect influence upon behavior through self-efficacy expectations. These influences should perhaps be more thoroughly monitored from trial to trial. However, as indicated above, other mediating mechanisms are undoubtedly accounting for the direct treatmentperformance paths. The direct effect of treatment on performance is consistent with the findings of Schunk (1981), Feltz (1982), and Feltz and Mugno (1983). Schunk found that his treatments for improving math accuracy in grade school children were directly influencing math accuracy independent of any mediating influence of self-efficacy. He argued that cognitive skills such as solving math problems could be developed independently of changes in selfefficacy. Schunk further stated that since there was a strong relationship between efficacy and accuracy, his data supported the contention that changes in performance (accuracy) depended largely on changes in self-efficacy. However, the self-efficacy/accuracy relationship was stronger than the treatrnent/accuracy relationship in Schunk's study. Feltz (1982) and Feltz and Mugno (1983) in multiwave path analyses of diving performance found self-efficacy to be a significant mediator of performance, but after the first dive, previous diving performance was found to be a stronger predictor of future performance than was self-efficacy. The failure of the anxiety-reduction model to explain behavior change in this study is compatible with the findings of previous researchers, who have reported that anxiety and/or defensive actions are merely coeffects of the behavior change process as opposed to being causal factors in the process (Bandura, 1977b). A more recent study by Williams, Dooseman, and Kleifield (1984) reported a weak but significant relationship between performance related anxiety and phobic behavior. However, when statistically controlling for self-efficacy, no predictive value was exhibited by anxiety. But when anxiety was controlled, efficacy expectations remained strong predictors of phobic behavior. The results of the present study parallel those of Williams et al. (1984) and testify to the superiority of the self-efficacy performance relationship over the anxiety-reduction performance relationship. A criticism of the present study is the small sample population used and, as already suggested, one must be cautious in interpreting the results. The results lend some support to Bandura's (1977a) theoretical model that suggests self-efficacy cognitions are impor-

12 tant determinants of behavioral change. Modeling treatments were found to be significant sources of efficacy informaton, anxiety reduction, and potent influencers of motor skill acqnisitim. Path analytic techniques determined Bandura's (1977a) model to fit the data better than an anxiety-reduction model. The presence of direct paths between treatments and performance suggest that other factors are also instrumental in influencing behavior change (Bandura, 1984). The present study and the work of Feltz (1982) and Feltz and Mugno (1983) all suggest that more complex alternatives to the fundamental theoretical model presented by Bandura (1977a) are required. The need for further applications of Bandura's model in more diverse settings is clear. Statistical tools such as path analysis and linear structural equations analysis (Joreskog & Sorbom, 1981) must also be employed if researchers are interested in testing whether the theoretical models in question fit the data. References Bandura, A. (1977a). Self-efficacy theory: Toward a unifying theory of behavioral change. Psychological Review, 84, Bandura, A. (1977b). Social learning theory. Englewood Cliffs, NJ: Prentice-Hall. Bandura, A. (1984). Recycling misconceptions of perceived self-efficacy. Cognitive Therapy and Research, 8, Bandura, A., & Adams, N.E. (1977). Analysis of self-efficacy theory of behavioral change. Cognitive Therapy and Research, 1, Bandura, A., Adams, N.E., & Beyer, J. (1977). Cognitive processes mediating behavioral change. Journal of Personality and Social Psychology, 35, Bandura, A., Adams, N.E., Hardy, A.B., & Howells, G. (1980). Tests of the generality of selfefficacy theory. Cognitive Therapy and Research, 4, Bandura, A., & Cewone, D. (1983). Self-evaluative and self-efficacy mechanisms governing the motivational effects of goal systems. Journal of Personality and Social Psychology, 45, Bandura, A., & Schunk, D.H. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. Journal of Personality and Social Psychology, 41, Borkovec, T.D. (1978). Self-efficacy: Cause or reflection of behavioral change. In S. Rachman (Ed.), Advances in behaviour research and therapy (Vol 1). Oxford: Pergammon Press. Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, Eysenck, H.J. (1978). Expectations as causal elements in behavioral change. In S. Rachman (Ed.), Advances in behaviour research and therapy (Vol. 1). Oxford: Pergammon Press. Feltz, D.L. (1982). Path analysis of the causal elements in Bandura's theory of self-efficacy and an anxiety-based model of avoidance behavior. Journal of Personality and Social Psychology, 42, Feltz, D.L., Landers, D.M., & Raeder, V. (1979). Enhancing self-efficacy in high-avoidance tasks: A comparison of modeling techniques. Journal of Sport Psychology, 1, Feltz, D.L., & Mugno, D.A. (1983). A replication of the causal elements in Bandura's theory of selfefficacy and the influence of autonomic percqtion. Jownalof Sport Psychology, 5, Gmber, J.J., & Beauchamp, D. (1979). Relevancy of the competitive state anxiety inventory in a sport environment. Research Quarrerly, 50, Joreskog, K.G., & Sorbom, D. (1981). Lisrel V: Analysis of linear strucrural rehtionships by the method of maximum likelihood. Chicago: National Education Resources. Kerlinger, F.N., & Pedhazur, E.J. (1973). Multiple regression in behavioral research. New York: Holt, Rinehart & Winston.

13 TEST OF BANDURA'S MODEL 295 Martens, R., Burton, D., Rivkin, F., & Simon, J. (1980). Reliability and validity of the Competitive State Anxiety Inventory (CSAI). In C.H. Nadeau, W.R., Halliwell, K.M. Newell, & G.C. Roberts (Eds.), Psychology of motor behavior and sport Champaign, IL: Human Kinetics. Mowrer, O.H. (1947). On the dual nature of learning: A re-interpretation of "contingency" and "problem-solving." Harvard Educatiow/ Review, 17, Murray, M. (1979). Women S gymnastics for coach, participant, nnd spectator. Boston: Allyn & Bacon. Pedhazur, E.J. (1982). Multiple regression in behavioral research. New York: Holt, Rinehart & Winston. Schunk, D.H. (1981). Modeling and attributional effects on children's achievement: A self-efficacy analysis. Journal of Educatio~/ Psychology, 73, Spielberger, C.D., Gorsuch, R.C., & Lushene, R.E. (1970). Zhe State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press. Weinberg, R.S., Gould, D., Yukelson, D., & Jackson, A. (1981). The effect of preexisting and manipulated self-efficacy on a competitive muscular endurance task. Journal of Spon Psychology, 3, Weinberg, R.S., Yukelson, D., &Jackson, A. (1979). Expectations and performance: An empincal test of Bandura's self-efficacy theory. Journal of Sport Psychology, 1, Williams, S.L., Dooseman, G., & Kleifield, E. (1984). Comparative effectiveness of guided mastery and exposure treatments for intractable phobias. Journal of Consulting and Clinical Psychology, 52, Wolpe, J. (1978). Self-efficacy theory and therapeutic change: A square peg for a round hole. In S. Rachman (Ed.), Advances in behavior research and therapy (Vol. 1). Oxford: Pergarnmon Press. Manuscript submitted: November 19, 1984 Revision received: February 28, 1985