Comparison of the theories of reasoned action and ...

British Journal of Educational Psychology (1998), 68,563-580 0 1998 The British Psychological Society

Printed in Great Britain

Comparison of the theories of reasoned action and planned behaviour Georgios D. Sideridis" and Aggelos Kaissidis American College of Thessaloniki, Greece

Susana Padeliadu Aristotle University of Thessaloniki, Greece

Background. Ajzen & Fishbein's (1977) theory of reasoned action and, later Ajzen's planned behaviour theory (Ajzen, 1988;Ajzen & Madden, 1986) have received great attention in the literature (e.g., Giles & Cairns, 1995). A number of researchers have attempted to explain several aspects of human behaviour (e.g., Bandura, 1997). A review of literature between 1990 and 1997 using the Psychlit and ERIC databases which pertained to the application of the theories of reasoned action and/or planned behaviour for the explanation of student study behaviour for an upcoming examination revealed one study (Clarry & Burns, 1991) in which little support for the use of the theory of planned behaviour was provided. Aims. The purpose of the present study was to examine the appropriateness of the theories of reasoned action (Ajzen & Fishbein, 1977) and planned behaviour (Ajzen & Madden, 1986) to explain student study behaviour during final examinations as pertaining to achieving a high Grade Point Average (GPA).

Sample. This comprised 136 freshmen Greek students from an American undergraduate institution located in Greece. Method. A structural equation modelling analysis using EQS 4.02 (Bentler, 1992) was used to evaluate the construct validity of the theories of reasoned action and planned behaviour. In this modelling, latent variables were a function of measured variables and direct and indirect relationships were postulated in a path-analysis framework in order to explain both theories. Since the theory of reasoned action was nested within the theory of planned behaviour, a direct comparison between them was feasible. Results. Ajzen & Fishbein's (1977) theoretical framework (reasoned action) was well supported, providing a Comparative Fit Index (CFI) of .947. The only modification between the original (Ajzen & Fishbein, 1977) and the final structural model was a direct path between motivation to comply and study behaviour. This structural model provided significant improvement over the original model providing a CFI of .976 and a non-significant value. Further, *Correspondence and requests for reprints should be addressed to Dr Georgios D. Sideridis, 32 Konstantinoupoleos, Kalamaria, Thessalonika, 55132. Greece. E-mail: [email protected]

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Georgios D. Sideridis, Aggelos Kaissidis and Susana Padeliadu inclusion of the perceived control constructs produced a model with acceptable fit also (CFI = .934). Conclusion. It is concluded that both theories describe well the study behaviour of students although inclusion of perceived behavioural control was not fully supported by the data.

Research on student achievement has focused primarily on selected teacher behaviours, instructional arrangements and other variables deemed important to the academic achievement of students (e.g., family, school environment, SES; Greenwood, Delquadri, Stanley, Terry & Hall, 1985). More recently, and with the advent of new systematic observation systems, emphasis was placed on student behaviours as they relate to student academic achievement. For example, within the ecobehavioural analysis paradigm, a number of ecological, teacher and student variables are measured and associations are formed to explain student behaviour as it relates to academic achievement (Greenwood, Carta, Kamps & Arreaga-Mayer, 1990). With the development of analytic strategies (e.g., path analysis or structural equation modelling) several researchers have attempted to explain student achievement in terms of modified environmental variables (Greenwood, Terry, Marquis & Walker, 1994). The results from this research were consistent in that student classroom behaviour, especially active academic engagement, was the most significant predictor of student’s academic achievement (Greenwood, Delquadri & Hall, 1989). Within the elementary school framework the above issues of student and teacher behaviour are particularly important as they may determine the subsequent placement of students in general or special education environments. Researchers have consistently noted that the primary issue in the education of children with learning or other difficulties is that they are more challenging to teach given slow learning rates and the diversity of their classroom behaviour (Ysseldyke, Thurlow, Mecklenburg & Graden, 1984; Thurlow, Graden, Greener & Ysseldyke, 1983). Research examining factors associated with the academic achievement of low-achieving students suggested that students engaged in low levels of active academic responding (e.g., Christenson, Thurlow & Ysseldyke, 1987; Kamps, Leonard & Greenwood, 1991). Unfortunately, a learning problem does not often ‘stay’ with childhood or the early elementary years. A large number of students, mainly with learning disabilities or dyslexia, continue to attend school and many receive college degrees. Thus, although examination of student behaviour and classroom environment is particularly important in the early years (because of the possibility of early intervention), those same variables need to be examined in later years, to examine factors that possibly explain student academic achievement. However, college education is markedly different from the elementary age school years. In college student academic achievement might only be a function of one’s own study behaviour, motivation or other variables/factors as there might not be required lectures and attendance. Thus, the previous methodologies for explaining students’ academic achievement through examining their classroom behaviour might not apply to higher education contexts. In such environments, investigation of students’ academic achievement may require the use of alternative theoretical frameworks.

Reasoned action, planned behaviour and study behaviour

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Beyond the behaviouristic and ecobehavioural models (Greenwood et al., 1990; Greenwood et al., 1985) where behaviour is a function of its antecedents and consequences, other theorists attempted to provide links and explain student behaviour through measuring variables internal or external to the individual. A widely used model for explaining human behaviour has been Ajzen & Fishbein’s theory of reasoned action (Ajzen & Fishbein, 1977, 1980) or its reformulation, the theory of planned behaviour (Ajzen, 1988). These researchers attempted to explain human behaviour based on attitudinal and social forces. The reasoned action theoretical framework received increased attention within the last 20 years as researchers attempted to explain and predict several aspects of human behaviour (e.g., seat-belt use). Their model suggests that human behaviour is a function of one’s intention to emit a certain behaviour. This intention then is formed or caused by the direct influences of (a) the individual’s belief strength towards the behaviour (attitudinal component), (b) his or her prediction about whether the outcome will really occur (attitudinal component), (c) the position of the important significant others on that behaviour or social importance (subjective norm component), and (d) the individual’s willingness to comply to the requests and desires of hidher significant others (subjective norm component). The reformulation of this theory, namely planned behaviour theory, adds the component of perceived behavioural control which in essence is one’s perceived efficacy on achieving that behaviour or the reasons inhibiting its occurrence. Thus, direct links between two aspects of behavioural control, direct and indirect and intention, were added to explain human behaviour. The indirect behavioural control component intended to assess aspects within the environment that may inhibit the occurrence of a behaviour and may not be in the direct control of the individual (e.g., goodhad weather). The direct behavioural control aspect intended to measure one’s perceived efficacy beliefs regarding performing a behaviour. Thus, perceived behavioural control refers to one’s perceived requisite abilities (e.g., knowledge, skills and competencies, locus of control) to perform a task. The relationship between the perceived control construct and Bandura’s (1997) self-efficacy or Rotter’s (1966) locus of control component is apparent. Both theoretical frameworks, the theories of reasoned action and planned behaviour, have been used in numerous studies in an attempt to explain human behaviour. The theories have been used to explain or predict exercise behaviour (Greenockle, Lee & Lomax, 1990; Kimiecik, 1992), moral behaviour (Vallerand, Deshaies, Cuerrier, Pelletier & Mongeau, 1992), seat-belt use (Budd, North & Spencer, 1984), attitudes towards people with disabilities (Theodorakis, Bagiatis & Goudas, 1995), attitudes toward providing care for suicidal patients (Pederson, 1993), organisational behaviour (Elliott, Jobber & Sharp, 1995), blood donation (Giles & Cairns, 1995), cigarette smoking (Morgan & Grube, 1994), drug and alcohol use (Laflin, Moore-Hirschl, Weis & Hayes, 1994) and others (see Ajzen & Fishbein, 1977, for a review). In the present study we are interested in trying to explain college students’ academic achievement through investigating their study behaviour. A review of the literature between 1990 and 1997 using the PsychLit and ERIC databases revealed one study that used planned behaviour theory to examine student study behaviour (Clarry & Burns, 1991). In this study, planned behaviour theory was examined in relation to trait procrastination and trait and state optimism. The theory was not supported by the data

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Georgios D. Sideridis, Aggelos Kaissidis and Susana Padeliadu

as three theoretical constructs, attitude, subjective norm and perceived behavioural control were unrelated to intention. The purpose of the present study was to examine further the appropriateness of the theories of reasoned action and planned behaviour to explain student study behaviour during final examinations as pertaining to achieving a high GPA. Criticism of studies using the theories of reasoned action and planned behaviour As mentioned previously, a number of studies attempted to investigate the construct validity of the theories of reasoned action or planned behaviour (e.g., Greenockle et al., 1990; Vallerand et al., 1992). Consequently, a number of issues have been raised regarding the methodologies of these studies. For instance, until recently most evaluations of those theories were conducted using regression analyses (either stepwise or hierarchical). Unfortunately, with regression analysis one can only evaluate the effect of one variable on another at one time. Even when one enters several predictor variables no hypotheses regarding the relationships of the variables can be postulated. A partial solution is path analysis which similarly does not allow for the simultaneous evaluation of the contribution of all variables. More recently, the use of structural equation modelling (SEM) has greatly assisted the modelling of theories (Bandura, 1997). SEM allows for the simultaneous examination of all variables and allows researchers to postulate hypothesised relationships between variables. Excellent examples of the application of reasoned action and planned behaviour using SEM can be found in the literature (Vallerand et al., 1992).However, SEM may also introduce some problems. For example, some researchers use mechanical processes (i.e., tests provided by software packages) to form models (Liu, Kaplan & Risser, 1992;Theodorakis et al., 1995). Using such an approach, one deviates from the original theory formulation, and allows the data to postulate what the relationships ought to be. Although such an approach (which resembles Exploratory Factor Analysis) can be of interest in some instances (e.g., when one exhausts the theoretical dimension), those modifications may be a function of measurement error, low power, sample idiosyncrasies,small variable to subject ratio, and violation of assumptions such as multivariate normality. Thus, with no specific model in hand, mechanical model modifications can result in uninterpretable or difficult to interpret models. Along these lines, in some studies, modelling included several crossloadings. Although crossloadings can greatly increase model fit they adversely affect model interpretation, if they are not guided by theory. In conclusion, the best approach in theory modelling is the use of path analysis within SEM where a priori theoretical models and their modifications can be evaluated. Theoretical framework This study attempted to examine how the theories of reasoned action and planned behaviour (see Figure 1) can explain student study behaviour during final examinations in order to achieve a high GPA. According to the theory of reasoned action, behaviour is a function of intention. Intention however, is formed by the direct effects of belief strength and outcome evaluation (attitudinal component), and normative beliefs and motivation to comply to them (subjective norm component). Several researchers have suggested modifications to the original formulation (e.g., Theodorakis, 1992; Theodorakis et al., 1995). The


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result has been planned behaviour theory (Ajzen, 1988; Ajzen & Madden, 1986) with the inclusion of perceived behavioural control. Other variables included in the reformulation of the above theories have been ‘role identity’ (Sparks & Sepherd, 1992), ‘attitude strength’ (Theodorakis, 1994)’ ‘knowledge’ (Wilson, Kraft & Dunn, 1989), ‘information’ (Davidson, Yannis, Norwood & Montano, 1985)’ ‘intention certainty’ (Budd & Spencer, 1984), ‘accessibility’ (Fazio & Williams, 1986), and ‘background’ (Greenockle et al., 1990). Their contribution to model development has been pilottested only and, thus, their inclusion in explaining human behaviour is not warranted. The purpose of the present study was to examine how the original theoretical frameworks of Ajzen & Fishbein (1977) and Ajzen (1988) apply to the explanation of study behaviour as pertaining to students’ GPA.

Method Participants and procedures Of the approximately 200 first year students who had gained admission to the American College of Thessaloniki, a private college in Northern Greece, 136 (94 women and 42 men) aged 17 to 25 years (A4 = 19.04, SD = 1.18) completed two questionnaires near the end of the spring 1997 semester. This sample represents approximately 85 per cent of the total population of first year students who were enrolled at that period. The majority of the college’s students were considered to belong to a higher socio-economic class, as the tuition charges of private colleges in Greece are relatively high for families with low or average income. In terms of high school grade, a minimum of 14.00 (on a 1-20 scale) was required for admission at the specific college. The mean high school GPA for the sample was 16.1 (SD = 2.86). Participants were asked to complete a questionnaire at the beginning of an English class four weeks prior to the end of the spring semester. Students were told that data would be used solely for research purposes and as such would be treated with confidentiality. Power analysis was conducted to determine the probability of obtaining significant effects. Using regression type models (path analysis is such) power for a = .05, ES = .3, N = 138 was .95, which is satisfactory. Beyond this estimate, researchers versed in this area (e.g., Tanaka, 1987) suggested that the variable to subject ratio should be 1O:l in confirmatory factor-analytic procedures. In the present study, the ratio was approximately 9:1, which is close to the suggested estimates (15 measured causal links, N = 138 students). Measures Students were administered a questionnaire which included all elements of the theory of reasoned action. Those items were selected from previous studies (e.g., Theodorakis, 1992, 1994; Theodorakis et al., 1995; Vallerand et al., 1992), and were used following modification to fit the requirements of the present study. Items were arranged in the order suggested by Ajzen & Fishbein (1980) and are shown below. Behaviour. Actual study behaviour was assessed by one item: ‘During the past four weeks I studied hard every day’. The scaling for this item ranged from 1 = ‘very unlikely’ to 4 = ‘very likely’. This behaviour was measured four weeks following

Indirect

Figure 1. Theoretical models of reasoned action and planned behaviour

DirectPath

Behavior

F C 3

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administration of the first part of the questionnaire in order to evaluate the construct validity of the two theoretical models. Behavioural intention. Intention was assessed by asking student responses on two items: ‘In order to achieve a good GPA,(a) I intend to study hard every day during the next four weeks and, (b) I am determined to study hard every day during the next four weeks’. The scaling for this item ranged from 1 = ‘very unlikely’ to 4 = ‘very likely’. Belief strength. This attitudinal construct’ was estimated with two items: (a) ‘I think that studying hard every day during the next four weeks in order to achieve a good GPA is . . .’ ranging from very bad to very good, and (b) ‘I think that studying hard every day during the next four weeks would help me achieve a good GPA’.This latter item was rated on a 1 4 scale ranging from ‘very unlikely’ to ‘very likely’. Outcome evaluation. This variable was assessed by two items: ‘My studying hard every day during the next four weeks will result in these consequences, (a) I will have better chances for postgraduate studies and, (b) I will have better job opportunities’. The scaling for these two items ranged between 1 = ‘very unlikely’ and 4 = ‘very likely’. Normative beliefs. This construct was assessed with two items: ‘I should study hard every day during the next four weeks, (a) most people who are important to me think so and, (b) my friends think so’. The scaling for these two items ranged between 1 = ‘not at all’ to 4 = ‘very much so’. Motivation to comply. This construct was assessed with two items, the same for the normative beliefs construct: ‘Generally speaking, I often do what (a) most people who are important to me think so and, (b) my friends think SO’. The scaling for these two items ranged between 1 = ‘not at all’ to 4 = ‘very much so’. Perceived behavioural control. This construct was assessed with two items, one denoting indirect and the other direct control. Indirect control was assessed by the item: ‘I believe that I will not be able to study hard during the next four weeks because of my need for leisure’. This item was scored on a 1 4 scale ranging between ‘very unlikely’

Table 1. Means and standard deviations (SDs) among the measured variables Variables

1. Intention1 2. Intention2 3. Belief Strength1 4. Belief Strength2 5. Outcome Evaluation1 6. Outcome Evaluation2 7. Subjective Norm1 8. Subjective Norm2 9. Motivation to Comdvl 10. Motivation to Comb62 11. Indirect Control 12. Direct Control 13. Study Behaviour * p < .05

Mean

SD

2.86 2.51 3.24

.71 .87 .67 .66 .75 .86 .81 .83 .78 .81 .80 .63 .75

3.31

2.83 2.85 2.68 2.41 2.25 2.22 2.45 2.72 2.56

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Table 2. Intercorrelations among the measured variables Variables

1

2

3

4

5

6

7

8

9 1 0 1 1 1 2

1. Intention1 2. Intention2 .53* 3. Belief Strength1 .26* .32* 4. Belief Strength2 .32* .31* .35* 5. Outcome Evaluation1 .25* .22* .32* .35* 6. Outcome Evaluation2 .28* .27* .19* .37* .53* 7. Subjective Norm1 .27* .16 .18* .23* .22* .25* 8. Subjective Norm2 .21* .22* .16 .23* .21* .22* .52* 9. Motivation to Comdvl .09 .02 -.04 .10 .17* .18* .17* .20* 10. Motivation to Comb62 .14 .04 .11 .28* .lo .27* .16 .25* .54* 11. Study Behaviour .30* .45* .15 .25* .17 .04 .15 .24*-.09 -.20 12. Indirect Control -.24*-.17*-.01 -.05 -.01 -.07 -.19*-.21* .05 .01 -.41* 13. Direct Control .29* .22* .21* .09 .22* .06 .08 .19* .06 - .03 .28*- .24* *p < .05

and ‘very likely’. Direct control was assessed by the item: ‘I have a lot of control over my effort in studying hard every day during the next four weeks’. Scaling ranged between ‘strongly disagree’ and ‘strongly agree’. Data analysis Descriptives. Means, standard deviations (Table 1) and intercorrelations were computed for all observed variables (Table 2). Furthermore, values of skewness and kurtosis were computed for all measured variables as the assumption of multivariate normality is a prerequisite to robust SEM (Bollen & Long, 1994; Huba & Harlow, 1987). Cronbach (1951) alpha was computed for examining the internal consistency of the items comprising the theory of reasoned action. Descriptive and internal consistency analyses were conducted using SPSS/PC+ 6.0. Further analyses for evaluating the construct validity of the theory of reasoned action were conducted with structural equation modelling using EQS 4.02 (Bentler, 1992). Structural equation modelling. SEM evaluates how well a conceptual model that includes observed variables and hypothetical constructs fits the obtained data (Hoyle & Smith, 1994). A hypothetical construct accounts for the intercorrelations of the observed variables that define that construct (Bollen & Lennox, 1991; Greenockle et al., 1990; MacCallum & Browne, 1993). The structural model in SEM deals with the hypothesised relationships, direct or indirect, between the measured variables and the constructs (Hays, Marshall, Wang & Sherbourne, 1994; Hoyle & Smith, 1994). Each construct is measured by a number of observable variables (items). Duncan & Stoolmiller (1993) suggested that models that include multiple items should be preferred to more simple models because they allow for a better estimation of the hypothesised constructs. Bentler (1992) added that a model with two items per factor is just identified with the presumption that the factors are left free to covary. The final structural models of the theories of reasoned action and planned behaviour included constructs which were defined by two items and their

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respective constructs were left free to covary with each other (to have an identified model). The adequacy of a structural model is determined by a chi-square test. This test evaluates how well the covariance matrix implied by the model fits the covariance matrix of the observed data. However, because the chi-square is heavily influenced by sample size (Bollen & Long, 1994), several fit indices have been proposed as aids to model fitting (Bentler, 1990, 1992; Joreskog & Sorbom, 1981). The fit index that has been suggested as the most appropriate one is the Comparative Fit Index because it has a 0-1 range, it has a small sampling variability, and it is unaffected by sample size (Bentler, 1990; Garrett, Ferron, Ng’andy, Bryant & Harbin, 1994). For validity purposes, fit indices with values less than .900 have not been considered acceptable (Bentler, 1990; Hays et al., 1994). Model modifications can be assisted by the use of two tests, the Wald test and the Lagrange Multiplier test (Bentler, 1992; Byrne, 1994). The Wald test is a test for evaluating whether any free parameters of a model can be restricted without substantial loss in fit (Bentler, 1992). The Lagrange Multiplier test evaluates if model fit improves as parameters are restricted (Bentler, 1992; Byrne, 1994). Although these post-hoc modifications are heavily influenced by chance (MacCallum, Roznowski & Necowitz, 1992), they could provide insight to variations of the original model (Hays et al., 1994). Within SEM it is often undesirable to have variables defining more than one construct because they usually confound the meaning of the hypothetical constructs. Thus, such modifications were not conducted as they would confound the internal validity of the theory of reasoned action. The SEM analyses were conducted using EQS 4.02 (Bentler, 1992). Table 3. Indices of fit for measurement and structural models Model

x2

255.93 Null Model Model 1 (Measurement model) (Reasoned Action theory) 74.42** Model 2 (Model 1 + covariations) 39.69 Model 3 (Model 2 + link between Motivation 32.88 to Comply and Behaviour) Model 4 (Planned Behaviour theoryModel 3 + directhndirect perceived control) 59.73

CFI

NNFI

34

,799

.675

29

,947

28

44

d.f.

Axz

Ad.$

ACFI ANNFI

399

34.73**

5

.148

.224

,976

.952

6.81*

1

.029

.051

,934

.884

55

*p < .01, **p .05,CFI

Direct Path B -Correlation 4_._.___.._.. +

Figure 2. Final structural model of the theory of reasoned action with standardised path coefficients

u l 4 w

F

..

g.

R

s

F

g.

xz

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comply and behaviour (Figure 2). Thus, Model 3 included Model 2 with the addition of a direct causal path between motivation to comply and behaviour. In this model, motivation to comply influences study behaviour both directly and indirectly. Additionally, 13 of the 16 direct paths were significant. An investigation of the weights of the model revealed interesting findings. First, the direct path of behavioural intention to actual behaviour was strong, positive and significant. The link between belief strength and intention was positive and stronger than the respective path between normative beliefs and intention. Outcome evaluation appeared to have a minuscule contribution to the direct formation of intention. Motivation to comply produced direct and indirect negative paths to both intention and actual study behaviour. Structural model of the planned behaviour theory Following examination of the theory of reasoned action it was deemed important to evaluate the contribution of perceived behavioural control to model fit. As described previously, two items defining direct and indirect behavioural control were included in the model. The final structural model of the planned behaviour theory included a covariation between perceived control and normative beliefs, and a direct path between perceived control and actual study behaviour (Figure 3). Thus, perceived control was forced to have both a direct and an indirect (through intention) influence on study behaviour. The path weights were positive indicating that the more perceived control one has the more likely it is to develop intention and perform a behaviour. This model produced a non-significant chi-square and an acceptable CFI of .934 (Table 3). Although model fit was substantially decreased compared to the final reasoned action model, it was still well within acceptable model fitting standards (Bentler, 1990).

Discussion The purpose of the present study was to examine how the original theoretical framework of Ajzen and Fishbein applies to the explanation of college students’ study behaviour during final examinations. Results indicated strong evidence in support of the theory of reasoned action for explaining student study behaviour as pertaining to attaining a high GPA. No model specification searches were conducted to further improve model fit. From the original model of the theory of reasoned action, alterations included a direct path between motivation to comply and behaviour, and covariations selected between attitudinal and subjective norm components. The latter finding has been consistent in the literature, in that the constructs of attitudes and subjective norms are correlated to cause intention and behaviour (e.g., Vallerand et al., 1992). The former has not been reported as a number of studies examined the theoretical model for explaining behavioural intention and not actual behaviour. The standardised path coefficient between belief strength and intention was strong and positive, .646 for the reasoned action model and .639 for planned behaviour theory. It implies that for every 1 standard deviation change in belief strength, intention will change approximately .64 standard deviation, when all other variables in the model are held constant. This path was stronger than the respective path between normative beliefs and intention. This finding was consistent with the literature investigating moral

w

-b

4

Correlation

[x2(44, N = 138) = 59.73,~> .05, CFI = .934, NNFI = .884]. For simplicity purposes the residuals were omitted from the model. Unidirectional arrows indicate direct causal influences. Bi-directional arrows indicate construct correlations.

Perceived Control

Directpath

Figure 3. Final structural model of the theory of planned behaviour with standardised path coefficients

wl

wl 4

F

5.

x

F

6'

E 2

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behaviour (Vallerand et al., 1992) or physical activity of corporate employees (Kimiecik, 1992). Vallerand et al. (1992) reported that attitudes appear to be more significant predictors of behavioural intention than normative beliefs. Furthermore, in a review of 26 studies, Farley, Lehmann & Ryan (1981) reported that attitudes dominate subjective norms by a factor of 1.5. It is reasonable to hypothesise that the difference in the importance lies in the control factor. That is, intentionally or unintentionally we act the way we think about most of the time (based on a behavioural belief system). Thus, attitudes are formed having in mind the consequences of a behaviour and should be closely linked to the formation of one’s intention and actual behaviour. The weights in the present model suggest that when one thinks that studying is good for achieving a high GPA, hidher intention to study is formed causing actual study behaviour. On the contrary, the normative belief system may be more remote than attitudes in causing behavioural intention and behaviour (Vallerand et al., 1992) and personal forces might be stronger than social forces. Outcome evaluation appears to have a minuscule contribution to the direct formation of intention. Thus, the consequences of study behaviour do not appear to directly cause intention. It is possible, however, that the interaction of behavioural beliefs and outcome evaluation causes the direct and strong path between behavioural beliefs and intention as shown by their large correlation coefficient. Small weights between outcome evaluation and behavioural intention have also been reported previously (Vallerand et al., 1992). Motivation to comply produced direct and indirect negative paths to both intention and actual behaviour. It is not clear why both paths were negative. It is possible, however, that other mediator variables might be responsible for such a negative effect. For example, peer and family pressure and one’s motivation to comply with them may induce unnecessary anxiety, feelings of helplessness or depression episodes that are detrimental to studying. Since this research was conducted during the end of a school year and intended to assess study behaviour during the final four weeks of the semester, exam anxiety might have had its contribution. This study provided also adequate support regarding the construct validity of planned behaviour theory. Model fit also suggested inclusion of a direct path between perceived control and behaviour which makes inherent sense. The weights between perceived control and intention-behaviour were as predicted: significant and positive indicating that the more control one thinks he/she has to study the more intention he/ she has and more studying occurs. Although model fit was substantially decreased compared to the reasoned action theory, it still remained within acceptable levels ( > .900 CFI). It is possible, however, that this decrease in model fit might have been a function of the inclusion of a new construct and two measured variables which produced a more complex and more restricted model. An advantage of this study over other studies has been the estimation of the direct and independent contribution of the five theoretical concepts and behavioural intention-behaviour. Most studies have used multiplicative terms between behavioural beliefs x outcome evaluation and normative beliefs x motivation to comply. However, as Vallerand et al. (1992) noted, those multiplicative terms do not allow examination of the unique contribution of these components to the prediction of behavioural intention and behaviour. Additionally, in SEM those multiplicative terms could produce prob-


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lems in model testing, probably due to multicollinerarity effects (i.e., high correlation between the multiplicative terms and their individual components). A limitation of this study pertains to the characteristics of this sample. The sample was not a typical sample of first year public college students found in Greece. These students were of high-SES attending an English-speaking private college. Thus, systematic replication is needed to evaluate if the present findings hold with larger samples of the same population or samples of first year students from public universities. The general purpose of this study pertained to the explanation of student study behaviour during final exams as it pertains to them achieving a high GPA. However, studying is only one behaviour linked to achieving a high GPA. Students’ attendance or their behaviour within the classroom are also important determinants of their academic achievement. Those behaviours were not investigated in the present report. Future researchers could better define academic achievement by including more variables or behaviours that might be causal to academic achievement. In summary, investigation of the theory of reasoned action as applied to student study behaviour in college suggested that the theory well explains students’ study behaviour. The only modification from the original model was the inclusion of a direct causal link between motivation to comply and study behaviour. The findings of this study are much more straightforward compared to investigations of other behaviours. A number of direct paths between outcome evaluation to behavioural beliefs or normative beliefs to attitudes have been previously suggested (Miniard & Cohen, 1981). These modifications were not needed in the present study. The final structural model strongly resembled the original reasoned action model and the weights of the hypothesised relationships were similar to those of studies measuring exercise or moral behaviour (Theodorakis et al., 1995; Vallerand et aZ., 1992). The planned behaviour paradigm was also well supported. However, inclusion of perceived behavioural control reduced model fit. Similarly, weak contribution of perceived control to behavioural intention has been reported in the literature (Kimiecik, 1992; Theodorakis, 1992). This study may be the first one to examine student study behaviour as pertained to them attaining a high GPA in college. Future studies should attempt to examine further the theory of reasoned action and replicate the present study’s findings. It will be of interest to ascertain both the magnitude of the weights that link the construct to behavioural intention as well as the signs of the weights (e.g., the negative weight between motivation to comply and intentiodbehaviour). Future studies might also attempt to examine the reformulation of the theory of reasoned action (planned behaviour) or further examine the role of other mediator variables such as attitude strength or role identify. NOTE.’ The terms ‘factor’, ‘construct’ and ‘latent variable’ have been used interchangeably in the manuscript and refer to the hypothesised factor that is defined by two or more measured variables. Similarly, the terms ‘indicator’ and ‘items’ refer to the measured variables.

Acknowledgments We appreciate the contribution of Kathy Carrer, Alexandra Zervos and Alexia Theoli who assisted in data collection, and Demetres Hemonides for his hardware and

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software support. This work was supported by a Mellon Foundation Grant. Also, special thanks are extended t o Debby Kazazis for her constant assistance throughout the project. Finally, we are thankful t o two anonymous reviewers for their thoughtful comments which really improved the manuscript.

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