Psychology 2011. Vol.2, No.3, 241247 Copyright © 2011 SciRes. DOI:10.4236/psych.2011.23038 Psychometric Properties of the Greek Version of the Test Anxiety Inventory Georgia Papantoniou1, Despina Moraitou2, Dimitra Filippidou1 1University of Ioannina, Ioannina, Greece; 2Aristotle University of Thessaloniki, Thessaloniki, Greece. Email: gpapanto@uoi.gr, demorait@psy.auth.gr, dfili@hotmail.com Received January 30th, 2011; revised March 15th, 2011; accepted April 20th, 2011. The present study examined the psychometric properties of the Greek version of Spielberger (1980) selfreport measure of test anxiety, the Test Anxiety Inventory (TAI). The total sample consisted of 231 undergraduate stu dents (124 male, 107 female). The results verified the well established twofactor structure for the TAI. The two factors represented the Worry (TAIW) and Emotionality (TAIE) subscales, respectively. Furthermore, on the bases of the confirmatory factor analyses, using either the set of 20 items or the set of 16 items, we found con vincing support for the existing relationship between the two subscales of the Test Anxiety Inventory. The in ternal consistency of the twentyitem TAIT scale and for the eightitem Worry and Emotionality subscales ranged from Cronbach’s α = .81 to .94. The GTAI and its subscales showed differential statistically significant relationships with a selfreport measure of cognitive interference. Keywords: Psychometrics, Test Anxiety, Greece Introduction Education is vital for every country in the world, and Greece is not an exception as a strong and effective education can help boost the development of the country. As testing is a common practice in contemporary society, like Greek society, for mak ing important decisions about an individual’s status in school, college, and work (Lowe, Lee, Witteborg, Prichard, Luhr, Cullinan, Mildren, Raad, Cornelius, & Janik, 2008; Zeidner, 1998), it is no wonder that test anxiety is a significant educa tional problem affecting many of students in our schools and colleges. Students with test anxiety feel tense, fearful and worried in evaluative situations (Spielberger, Gonzalez, Taylor, Anton, Algaze, Ross, & Westberry, 1979; Spielberger & Vagg, 1995). Research relating test anxiety to academic performance has established that high levels of test anxiety are associated with lower levels of students’ learning and performance (Sub & Prabha, 2003). Often testanxious students at all levels of edu cation perform more poorly on standardized tests (Everson, Millsap, & Rodriguez, 1991) and receive poorer grades (Chapell, Blanding, Silverstein, Takahashi, Newman, Gubi, & McCann, 2005) than they ought to because anxiety and other testtaking deficiencies interfere with their performance, either directly or indirectly (Efklides, Papadaki, Papantoniou, & Ki osseoglou, 1997, 1999; Lowe et al., 2008; Metallidou & Vla chou, 2007). In order to assess individual differences in test anxiety, Spielberger developed the Test Anxiety Inventory (TAI; Spiel berger, 1980) which is a selfreport instrument. The TAI is one of the most widely used of the test anxiety inventories as it has been translated or adapted for many populations (see Ware, Galassi, & Dew, 1990). Spielberger had two major goals in developing the TAI: (1) to construct a brief, valid selfreport measure of the test anxiety which was highly correlated with other measures of the con struct and (2) to use factor analytic procedures to measure the emotionality and worry components of the test anxiety identi fied by Liebert and Morris (1967). Emotionality refers to per ceived autonomic reactions (physiological arousal) evoked by evaluative stress (Spielberger & Vagg, 1995), whereas worry refers to cognitive concerns about the consequences of failure (Morris & Liebert, 1969). Worry tends to be associated with performance decrements on cognitive and intellectual tasks, but emotionality is not (see Hembree, 1988; Hong, 1998; Spielber ger et al., 1979; Van der Ploeg, 1984). For the TAI’s original development, exploratory factors ana lytic procedures (principal axis factoring with varimax rotation) have been used by its constructors. According to them, the TAI consists of 20 items, and contains two subscales measuring worry and emotionality. Each subscale is defined by eight items, with the remaining four (1, 12, 13, & 19) items not ordinarily included in subscale scores as the results did not indicate clear patterns favoring either subscale (Spielberger et al., 1979). There are conflicting views of the factor structure of the TAI as regards (a) the necessity of the 20item TAI, and (b) the interrelations of the two components of test anxiety. Despite Spielberger and colleagues (Spielberger, Gonzalez, Taylor, Algaze, & Anton, 1978; Spielberger et al., 1979) having re ported correlations between the Worry and Emotionality sub scales of .71 for males and .64 for females, most studies of the factorial structure of the TAI using exploratory factor analysis, have employed orthogonal rotations (e.g. varimax) following a principal factor extraction (Hedl, 1984; Schwarzer & Kim, 1984; Spielberger et al., 1978, 1979; Van der Ploeg, 1983). On the other hand, most researchers that used confirmatory factor analysis have established a twofactor oblique model of the 16item TAI, composed of correlated Worry and Emotionality
G. PAPANTONIOU ET AL. 242 factors (Benson & Tippets, 1990; Everson, Millsap, & Rodri guez, 1991; Gierl & Rogers, 1996; Ware, Galassi, & Dew, 1990). Although the 20item TAI had been administered in Greek samples (Hatzidimitriadou, 1995; Papantoniou & Efklides, 2004; Vasilaki & Vamvoukas, 1997) and its internal consis tency had been estimated, to our knowledge, neither the 20item, nor the 16item TAI have been tested extensively re garding their factor structure in Greek population. Hence, the main objective of this study was to examine the psychometric properties of the Greek long and short version of the TAI (fac tor structure, internal consistency and convergent validity) in order to determine whether it is a useful tool for the study of test anxiety in the Greek cultural context. Based on previous work, we hypothesized that the GTAI (both the long and the short version) would have the same two factor structure of Worry and Emotionality. There also were expected interrelations between these factors (Hypothesis 1). The TAI total score and both subscales have been shown to have high internal consistency in previous research (Benson & Tippets, 1990; Hatzidimitriadou, 1995; Spielberger et al., 1979; Ware, Galassi, & Dew, 1990). Thus we hypothesized that the Greek instrument would show similar range of internal consis tency (Hypothesis 2). The relationship between the TAI and its subscales with other anxiety measures (e.g., Sarason’s Test Anxiety Scale, TAS; Liebert & Morris’s Worry and Emotionality Question naire, WEQ; the STAI State and Trait Anxiety scales, and the STAI State Anxiety scale administered under examination stress conditions) all provide evidence of convergent validity (Spielberger et al., 1979). In the present study, in terms of con vergent validity, we expected that the GTAI would be corre lated positively with a selfreport measure of cognitive inter ference, namely, the Cognitive Interference Questionnaire, CIQ (Sarason, Sarason, Keefe, Hayes, & Shearin, 1986) (Hypothesis 3). Method Participants The total sample consisted of 231 volunteer undergraduate students (124 male, 107 female) attending Schools of social sciences, mathematics, physical sciences, informatics, engi neering and life sciences at Greek Universities. Instruments The Test Anxiety Inventory (TAI). The TAI is a selfreport psychometric scale that was designed by Spielberger (1980) to “measure individual differences in test anxiety as a situa tionspecific personality trait”. The TAI was developed for use with adolescents and adults and consists of 20 items that ask respondents to indicate how they generally feel in test situations by reporting the frequency that they experience specific symp toms of anxiety before, during and after examinations. Re spondents rate their responses on a 4point Likerttype scale. The four response choices are: (1) almost never, (2) sometimes, (3) often, and (4) almost always. Values of item 1 are reversed. The TAI has two subscales that assess worry and emotionality as major components of test anxiety. Each subscale consists of eight items with the remaining four items not ordinarily in cluded in either subscale. The eight items that form the TAI Worry subscale (TAIW) are: 3, 4, 5, 6, 7, 14, 17, and 20. The eight items that constitute the TAI Emotionality subscale (TAIE) are: 2, 8, 9, 10, 11, 15, 16, and 18. The TAI yields a total score based on all twenty items, a score for Worry based on the subset of eight items and a score for Emotionality based on the other eightitem subscale. The TAI had been translated into Greek by Hatzidimitriadou (1995; Stogiannidou, Kiosseoglou, & Hatzidimitriadou, 1999) and its reliability had also been assessed. For Hatzidimitriadou’s (1995) sample (N = 296 adolescents, 161 male and 135 female), Cronbach’s α values had been .91 for the twentyitem TAIT scale, .81 for the eightitem worry subscale, and .86 for the eightitem emotionality subscale. For Vasilaki and Vamvoukas’ (1997) sample (N = 424 elementary school pupils), Cronbach’s α value had been .80 for the twentyitem TAIT scale. For Pa pantoniou and Efklides’ (2004) sample (N = 390 adolescents and young adults, 170 male and 220 female), Cronbach’s α values had been .90 for the twentyitem TAIT scale, .75 for the eightitem worry subscale, and .86 for the eightitem emotion ality subscale. However, since none of the aforementioned studies was an adaptation study of the TAI in Greek population, in this study it was preferred the original version of the TAI to be translated into Greek by the first author and back translated by one independent bilingual psychologist. The backtranslated questionnaire was then compared to the original and a few mi nor modifications were applied. The Cognitive Interference Questionnaire (CIQ). The CIQ (Sarason et al., 1986) is a 22item questionnaire designed to measure, following performance on a task, the degree to which people experienced various types of thoughts while working on it, and the degree to which these thoughts are viewed as inter fering with concentration. According to its constructors (see Sarason et al., 1986), the CIQ measures two types of thoughts, taskoriented worries and offtask thoughts. The “Taskoriented Worries” dimension was chosen to test the convergent validity of the GTAI. For the purposes of previous studies, the first 10 items of the CIQ, providing postperformance reports of the frequency of occurrence of taskoriented worries, had been translated into Greek by the first author; the single factor struc ture of the Greek version of the “Taskoriented Worries” di mension of the CIQ was verified with CFA and its reliability was also assessed (see Papantoniou & Efklides, 2004; Papanto niou, Moraitou, Dinou, & Katsadima, 2010). Participants were asked to indicate the frequency of occurrence of taskrelated thoughts that intruded while they were working on the exami nation in an introductory course of their School, on a 5point scale from 1 (never) to 5 (very often). Cronbach’s α was ac ceptable: .83 for this sample. Procedure Data were collected across multiple sessions ranging in size from 15 to 20 participants. Questionnaires were administered during participants’ examination in cognitive ability tests. The TAI was administered at the beginning of the examination. Participants also provided demographic information, including age, gender, and class level (freshman, sophomore, junior or senior) prior to completing the questionnaires. The CIQ was administered at the end of the examination. Participation in the study was voluntary and participants were informed that all results were confidential.
G. PAPANTONIOU ET AL. 243 Statistical Analysis Although exploratory factor analysis is useful in test con struction, it does not provide an especially convincing test of the factorial structure of scale as it does not permit the investi gator to hypothesize and confirm which of a series of alterna tive plausible latent factor models best fits the data. Therefore we used confirmatory factor analyses to compare the factor structures, implied for the TAI by previous theory and empiri cal research, using either the 20 or the 16 items. Structural equation models were conducted in EQS Version 6.1 and per formed on covariance matrix using the Maximum Likelihood estimation procedure (Bentler, 2005). Starting from the covari ance matrix, the viability of a twofactor model composed of correlated Worry and Emotionality factors, inferred from Spielberger et al. (1979), was tested in sequential fashion against a series of logically nested alternative models. A nonstatistical significance of the χ2test indicates that the implied theoretical model significantly reproduces the sample variancecovariance relationships in the matrix. Since this test is sensitive to sample size, model fit was also evaluated by using the root mean squared error of approximation (RMSEA). The RMSEA tests how well the model would fit the population covariance matrix. A rule of thumb is that RMSEA < .05 indi cates close approximate fit and values between .05 and .08 suggest reasonable error of approximation (Kline, 2005). The Comparative Fit Index (CFI) which is one of the indexes as sessing the relative improvement in fit of the researcher’s model compared with a baseline model was also used. A rule of thumb for the CFI is that values greater than .90 may indicate reasonably good fit of the researcher’s model (Kline, 2005). In addition, model fit was evaluated by using the standardized root mean squared residual (SRMR). The SRMR is a measure of the mean absolute correlation residual, the overall difference be tween the observed and the predicted correlations. Values of the SRMR less than .10 are generally considered favourable (Kline, 2005). As regards the sample size requirements, for SEM techniques, it is recommended as a rule of thumb that there be at least five observations per estimated parameter (Hair, Anderson, Tatham, & Black, 1998). A total of 20 parameters were estimated in confirmatory factor model. Hence, the sample size for path model had to exceed 100. Thus, the sample size exceeded the minimum recommended level for performing confirmatory factor analysis. Results Initially, we used confirmatory factor analyses to examine the factor structure, established by Spielberger et al. (1979) in the TAI Manual, using the 20 items. More specifically, we compare the following three factor structures: Model A, a onefactor model in which all twenty items loaded on a single latent factor; Model B, a twofactor model in which all sixteen items of the two subscales, Worry and Emotionality, loaded on a firstorder latent factor. Both this firstorder latent factor and the four items, that are not included in the Worry and Emotion ality subscales, loaded on a secondorder latent factor called TAIT; and Model C, a threefactor model in which the two subscales, Worry and Emotionality, were firstorder latent fac tors. Both these firstorder latent factors and the four items, that are not included in them, loaded on a secondorder latent factor called TAIT. For each confirmatory factor analysis (CFA) model, a single path was freed from the relevant factor to each item. No cross loadings were allowed. In the last model containing more than one factor, latent factors were defined without any covariance between them as they loaded on a secondorder latent factor. For all models, the metric was set by fixing factor variances to 1.0. The fits of the models compared directly using chisquare difference tests. As shown in Table 1, for all three models, the chisquare goodnessoffit statistic was significant (p < 0.001), thus lead ing to the rejection of the null hypothesis of good fit. Therefore information from other indicators of fit was assessed. The RMSEA fell in the marginal range of .05  .08 (see Kline, 2005) indicating at least adequate fit for these models based on this criterion. Specifically, the RMSEA was below .08 for the single and the twofactor models (Model A: RMSEA = .074, Model B: RMSEA = .074) and below .07 for the threefactor model (Model C: RMSEA = .069). Standardized rootmean square residual (SRMR) values were below .08 (ranged from .050 to .053) indicating also good fit for all models tested. All CFI values also fell in the marginal range of .90  .95 (see Brown, 2006). In conclusion, the fit indices of the final model (Model C) indicated that the final model [χ2(168, Ν = 231) = 352.73, p = .000, χ2/df = 2.10, CFI = .93, RMSEA = .069, SRMR = .050] fits the data better than the rest models of this set of analysis (Brown, 2006). Furthermore, we compared Models A and B with Model C using the chisquare difference test. The results showed that the Δχ2 was significant in all cases: Model A & Model C: Δχ2(Δdf = 2) = 30.66, p < .001; Model B & Model C: Δχ2(Δdf = 1) = 30.29, p < .001. Thus, on the basis of the chisquare difference tests, comparisons of CFI, and the low value of its RMSEA and SRMR, the bestfitting model was unambiguously the three factor model with the firstorder latent factors (Worry & Emo tionality) and the four items, that are not included in them, Table 1. Summary of fit tests for Confirmatory Factor Analysis Models with 20 ΤΑΙ items. Model (factor) χ2 P CFI χ2/df SRMR RMSEA Model A (Single factor) χ2(170, N = 231) = 383.39 < .001 .914 2.26 .053 .074 Model B (Twofactors: one firstorder and one secondorder latent factors) χ2(169, N = 231) = 383.02 < .001 .914 2.27 .053 .074 Model C (Threefactors: two firstorder and one secondorder latent factors) χ2(168, N = 231) = 352.73 < .001 .925 2.10 .050 .069
G. PAPANTONIOU ET AL. 244 loaded on a secondorder latent factor called TAIT (Model C). Moreover, this model has also the advantage of previous theo retical and empirical validation (see Spielberger et al., 1979). Model C is displayed in Table 2. Consequently, a second set of confirmatory factor analyses of Models A  C was performed, using only the sixteen TAI items in the Worry and Emotionality subscales. In this revised item set, we excluded the four items (Items 1, 12, 13, & 19) which were not used in computing scores on the Worry and Emotionality subscales because double loadings on these items are reported in the TAI Manual. More specifically, the CFA models that were tested on the revised set of 16 items were the following: Model A, a one factor model in which all sixteen items loaded on a single latent factor; Model B, a twofactor model in which the two subscales, Worry and Emotionality, were firstorder latent factors. In this model CFA was performed twice. At the first performance, latent factors were defined without any covariance between them (Measurement model: Model B1). At the second per formance, latent factors were allowed to freely intercorrelate (Structural model: Model B2); and Model C, a threefactor model in which the two subscales, Worry and Emotionality, were firstorder latent factors that loaded on a secondorder latent factor called TAI. However, during our trial to test Model C, the EQS program (Bentler, 2005) warned that a parameter estimate is not inside the specific boundaries. More specifically, the disturbance of the firstorder Worry factor was being held at the lower bound ary (.000) specified for the problem. The constraint of this pa rameter at lower boundary indicates a solution which is not acceptable: that the firstorder Worry factor could be perfectly predicted from the secondorder latent factor called TAI. In addition, as shown in Table 3, Measurement Model B1 would clearly be rejected, and in the interests of saving space, these results are not detailed further. As regards the rest two models, using the sixteen item set, the chisquare goodnessoffit tests were statistically significant for them (for Models A and B2, p < .001), resulting in a rejec tion of the null hypothesis of good fit. Therefore information from other indicators of fit was assessed. The CFI values fell in the marginal range of .90  .95 (see Brown, 2006) and the RMSEA fell in the marginal range of .05  .08 (see Kline, 2005) indicating adequate fit for these models based on these criteria (Model A: RMSEA = .080, Model B1: RMSEA = .072). Stan dardized rootmeansquare residual (SRMR) values were be low .08 (ranged from .050 to .054) indicating also good fit for the models tested. In conclusion, the fit indices of Model B2 indicated that this model [χ2(103, Ν = 231) = 224.69, p = .000, χ2/df = 2.18, CFI = .94, RMSEA = .072, SRMR = 0.050] fits the data better than Model A of this set of analysis (Brown, 2006). Furthermore, we compared Model A with Model B2 using the chisquare difference test. The results showed that the Δχ2 was significant: Model A & Model B2: Δχ2(Δdf = 1) = 30.83, p < .001. Thus, on the basis of the chisquare difference tests, comparisons of CFI, and the low value of its RMSEA and SRMR, the bestfitting model was unambiguously the two factor (Worry & Emotionality) model with interrelations be tween them (Structural Model B2). Similarly to Model C of the first set of confirmatory factor analyses, this model also has the advantage of previous theoretical and empirical validation (see Benson & Tippets, 1990; Ware, Galassi, & Dew, 1990). Model B2 is displayed in Table 4. In conclusion, the comparison between the bestfitting model of the first set of confirmatory factor analyses, which were performed using the 20 TAI items (Model C: Threefactors: two firstorder and one secondorder latent factors), and the bestfitting model of the second set of confirmatory factor Table 2. The bestfitting model (Model C) in the structure of the 20item version of the Greek Test Anxiety Inventory (standardized solution). Factors Items TAIW (F1) TAIE (F2) TAIT (F3) E / D R2 TAI 3 .570 .821 .325 TAI 4 .766 .643 .586 TAI 5 .361 .933 .130 TAI 6 .342 .940 .117 TAI 7 .681 .732 .464 TAI 14 .691 .722 .478 TAI 17 .629 .777 .396 TAI 20 .615 .788 .379 TAI 2 .741 .672 .549 TAI 8 .844 .536 .713 TAI 9 .760 .650 .577 TAI 10 .727 .686 .529 TAI 11 .754 .657 .568 TAI 15 .819 .574 .671 TAI 16 .784 .621 .614 TAI 18 .799 .601 .639 TAI 1 .607 .795 .368 TAI 12 .744 .668 .554 TAI 13 .748 .664 .559 TAI 19 .533 .846 .284 F1 (TAIW) .942 .337 .887 F2 (TAIE) .966 .260 .933 Note: TAIW = The TAIWorry factor; TAIE = The TAIEmotionality factor; TAIT = The TAITotal factor.
G. PAPANTONIOU ET AL. 245 Table 3. Summary of fit tests for Confirmatory Factor Analysis Models with 16 ΤΑΙ items. Model (factor) χ2 P CFI χ2/df SRMR RMSEA Model A (Single factor) χ2(104, N = 231) = 255.52 < .001 .922 2.46 .054 .080 Model B1 (Twofactors: two firstorder latent factors) χ2(104, N = 231) = 450.68 < .001 .820 4.33 .292 .120 Model B2 (Two factors: two firstorder latent factors + interrelation between factors) χ2(103, N = 231) = 224.69 < .001 .937 2.18 .050 .072 Model C (Threefactors: two firstorder and one secondorder latent factors) Table 4. The bestfitting model (Model B2) in the structure of the 16item version of the Greek Test Anxiety Inventory (standardized solution). Factors Items TAIW (F1) TAIE (F2) E R2 TAI 3 .576 .817 .332 TAI 4 .775 .632 .601 TAI 5 .342 .940 .117 TAI 6 .335 .942 .112 TAI 7 .694 .720 .481 TAI 14 .675 .738 .456 TAI 17 .625 .781 .391 TAI 20 .611 .791 .374 TAI 2 .737 .676 .542 TAI 8 .853 .522 .727 TAI 9 .771 .637 .595 TAI 10 .713 .701 .509 TAI 11 .749 .662 .561 TAI 15 .812 .584 .659 TAI 16 .792 .610 .628 TAI 18 .798 .602 .637 Factor Correlations F2 (TAIE) – F1 (TAIW) .906 Note: TAIW = The TAIWorry factor; TAIE = The TAIEmotionality factor. analyses, which were performed using only the 16 TAI items (Model B2: Two factors: two firstorder latent factors + inter relation between factors), on the basis of their NC (χ2/df) (Model C: NC = 2.10, Model B2: NC = 2.18), CFI (Model C: CFI = .925, Model B2: CFI = .937), RMSEA (Model C: RMSEA = .069, Model B2: RMSEA = .072), and SRMR (Model C: SRMR = .050, Model B2: SRMR = .050), suggests a good fit for both of the two models. Reliability Internal consistency was estimated, for the twentyitem TAIT scale and for the eightitem worry and emotionality subscales, using Cronbach’s α coefficient. The values were .94, .81, and .92, respectively. Convergent Validity Pearson correlations between the GTAIT and its subscales TAIW and TAIE, on the one hand, and the CIQ, on the other, were computed. Moderate positive correlations were found. The values were .46, .40, and .46, respectively (p < .01). Discussion The main aim of this study was to examine the psychometric properties of the Greek long and short version of the TAI; namely, the factor structure, internal consistency, and concur rent validity. Overall, the results are promising and verified the well estab lished twofactor structure for the TAI. Furthermore, on the bases of the confirmatory factor analyses, using either the set of 20 items, or the set of 16 items, we found convincing support for the existing relationship between the two subscales of the Test Anxiety Inventory. More specifically, the bestfitting model of the first set of confirmatory factor analyses, which were performed using the 20 TAI items (Model C: Threefac tors: two firstorder and one secondorder latent factors), as sumed that the two subscales, Worry and Emotionality, were
G. PAPANTONIOU ET AL. 246 firstorder latent factors. Both these firstorder latent factors and the four items, that are not included in them, loaded on a secondorder latent factor called TAIT. Similarly, the best fitting model of the second set of confirmatory factor analyses, which were performed using only the 16 TAI items (Structural Model B2: Twofactors: two firstorder latent factors + interre lation between factors), assumed that the two subscales, Worry and Emotionality, were firstorder latent factors with covari ance between them. These findings confirm our Hypothesis 1, and they are consistent to previous work either on the original and revised English version (Benson & Tippets, 1990; Hedl, 1984; Spielberger et al., 1978, 1979; Ware, Galassi, & Dew, 1990) or on the original Canadian and German versions (Gierl & Rogers, 1996; Schwarzer, 1984) that assumed a positive correlation between the two subscales. However, the results from this study indicate that the first order latent factors loadings (.94 for the Worry and .97 for the Emotionality factor) on the secondorder latent factor called TAIT (Model C: Threefactors: two firstorder and one sec ondorder latent factors), as well as their interrelation (.91) (Structural Model B2: Twofactors: two firstorder latent fac tors + interrelation between factors) were higher than those typically reported in the literature (Everson, Millsap, & Rodri guez, 1991; Schwarzer, 1984; Spielberger et al., 1978, 1979; Van der Ploeg, 1983). This magnitude of the covariance be tween the latent Worry and Emotionality factors is comparable to that reported by Benson and Tippets (1990) and Ware, Ga lassi, and Dew (1990). According to them, the higher interrela tion might be attributed to the relatively higher age and greater heterogeneity of their samples as compared with other studies. Similarly to the aforementioned studies (Benson & Tippets, 1990; Ware, Galassi, & Dew, 1990), the current sample, which included undergraduate students from a variety of academic disciplines and class levels, was considerably older and more diverse than those used in the studies where moderate interrela tion between the Worry and Emotionality factors was reported. Hypothesis 2 regarded the internal consistency of the Greek version of the TAI. The results were consistent to previous work either on the original and revised English version (Benson & Tippets, 1990; Spielberger et al., 1979; Ware, Galassi, & Dew, 1990) or on the 20item Greek version (Hatzidimitriadou, 1995; Papantoniou & Efklides, 2004). In this study, as well as in previous studies, the internal consistency of the TAI total score and both subscales tend to be high (Cronbach’s α coeffi cients were ranged from .81 to .94). Hypothesis 3 regarded the concurrent validity of the GTAI. The results were in the predicted direction, with the TAIT, the Worry and the Emotionality factors associating positively with the measure of cognitive interference. This finding suggests that persons with high TAI Total, Worry and Emotionality scores are more disposed to report that they incurred taskori ented worries during performance of a recently completed task than persons with low scores on this measure. This is in accor dance with research on cognitive interference (Sarason, Pierce, & Sarason, 1996) and test anxiety (Spielberger et al., 1979; see Zeidner, 1998). In conclusion, our study showed that the GTAIT, and its subscales TAIW and TAIE are moderately related to cognitive interference. Future studies aiming to ex amine psychological properties of the GTAI should investigate further its convergent and divergent validity with other meas ures that are, or have already been, in the procedure of adapta tion in Greek population, like STAI (Fountoulakis, Papadopou lou, Kleanthous, Papadopoulou, Bizeli, Nimatoudis, Iakovides, & Kaprinis, 2006). Finally, given the inconsistencies with regard to gender differences in previous factor studies of the TAI (Benson & Tippets, 1990; Everson, Millsap, & Rodriguez, 1991; Gierl & Rogers, 1996; Hedl, 1984; Schwarzer, 1984; Spielberger et al., 1978, 1979; Van der Ploeg, 1984; Ware, Galassi, & Dew, 1990), the question arises as to whether the TAI measures the same construct to the same degree for both male and female participants. Therefore, future studies should also determine whether the two verified factor structures from this study are invariant across gender. Although more research is needed to further validate the GTAI and to replicate our current findings, the results of our study show that both the 20item version and the 16item ver sion of the GTAI are efficient instruments for measuring test anxiety in the Greek cultural context, as they are of equal psy chometric strength in confirmatory factor analyses. As such, the two versions of the GTAI provide an initial base in examining crosscultural differences in test anxiety which, as being one of the negative activating test emotions, contributes to the under standing of academic performance and selfregulated learning (see Efklides, 2011). Consequently, we recommend the 16item version of the GTAI, as an economical measure of worry and emotionality, and the 20item version of the GTAI, as a meas ure that can further provide with a total test anxiety score. In conclusion, the short version of the GTAI can be used for checking the impact of each test anxiety dimension on various cognitive, metacognitive, and volitional aspects of learning and achievement. In the same logic, the long version of the GTAI can be used for providing more information on this specific emotion of a learner’s affective profile. References Benson, J., & Tippets, E. (1990). Confirmatory factor analysis of the Test Anxiety Inventory. In C. D. Spielberger, & R. DiazGuerrero (Eds.), Crosscultural anxiety (pp. 149156). New York: Hemi sphere/TaylorFrancis Publishing. Bentler, P. M. (2005). EQS 6.1., Encino, CA: Multivariate Software, Inc. Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: Guilford. Chapell, M. S., Blanding, Z. B., Silverstein, M. E., Takahashi, M., Newman, B., Gubi, A., & McCann, N. (2005). Test anxiety and aca demic performance in undergraduate and graduate students. 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