Psychological Reports: Relationships & Communications 2014, 115, 1, 261-275. © Psychological Reports 2014

FACTOR ANALYSIS OF THE FOREIGN LANGUAGE CLASSROOM ANXIETY SCALE IN KOREAN LEARNERS OF ENGLISH AS A FOREIGN LANGUAGE1, 2 GI-PYO PARK Soonchunhyang University, Republic of Korea Summary.—This study examined the latent constructs of the Foreign Language Classroom Anxiety Scale (FLCAS) using two different groups of Korean English as a foreign language (EFL) university students. Maximum likelihood exploratory factor analysis with direct oblimin rotation was performed among the first group of 217 participants and produced two meaningful latent components in the FLCAS. The two components of the FLCAS were closely examined among the second group of 244 participants to find the extent to which the two components of the FLCAS fit the data. The model fit indexes showed that the two-factor model in general adequately fit the data. Findings of this study were discussed with the focus on the two components of the FLCAS, followed by future study areas to be undertaken to shed further light on the role of foreign language anxiety in L2 acquisition.

Foreign language anxiety is defined as “the worry and negative emotional reaction aroused when learning or using a second language” (MacIntyre, 1998: p. 27). More specifically in classroom learning situations, it can be defined as “a distinct complex of self-perceptions, beliefs, feelings, and behaviors related to classroom language learning arising from the uniqueness of the language learning process” (Horwitz, Horwitz, & Cope, 1991: p. 31). Research on foreign language anxiety has burgeoned in the last three decades because anxiety is pervasive in second/foreign language (L2) acquisition both inside and outside the classroom, preventing language learners from achieving a high level of L2 acquisition and thus resulting in large individual differences in second/foreign language acquisition (Skehan, 1991; Horwitz, 2008). In a seminal study, Horwitz, Horwitz, and Cope (1986) developed the Foreign Language Classroom Anxiety Scale (FLCAS) to measure anxiety particular to foreign language learning in the classroom. The FLCAS items were developed through several procedures including student self reports, clinical experience, and a review of related instruments regarding communication apprehension, test anxiety, and fear of negative evaluaAddress correspondence to Gi-Pyo Park, Soonchunhyang University, Asan, Chungcheongnam-do, Republic of Korea or email ([email protected]). 2 This work was supported in part by the Soonchunhyang University research fund. The author expresses his deepest thanks to the reviewers for their insightful comments and helpful suggestions, and to Dr. Kyeung-Sook Kim and Ms. Mi-Soon Kwag for their assistance in data coding and analysis. 1

DOI 10.2466/28.11.PR0.115c10z2

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ISSN 0033-2941

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tion (Watson & Friend, 1969; McCroskey, 1970; Sarason, 1984). Since the development of the FLCAS, it has been used to investigate the reliability and validity of the measure, assess foreign language anxiety in the classroom, and explore the potential effect of anxiety on L2 acquisition (Horwitz, 1986; Aida, 1994; Cheng, Horwitz, & Schallert, 1999; Saito, Horwitz, & Garza, 1999; Zhang, 2000; Onwuegbuzie, Bailey, & Daley, 2000a; Kitano, 2001; Chen & Chang, 2004; Matsuda & Gobel, 2004; Elkhafaifi, 2005; Liu & Jackson, 2008; Tóth, 2008; Koul, Roy, Kaewkuekool, & Ploisawaschai, 2009; Cao, 2011; Mak, 2011; Park, 2012). Horwitz (1986), for instance, found that the relation of the FLCAS to students' final grade was −.49 for beginning Spanish classes, and −.54 for beginning French classes at a university. Aida (1994) found a significant negative influence of anxiety on course grades among university students learning Japanese in the United States: the course grades of the high anxiety group were significantly lower than those of the low anxiety group. Elkhafaifi (2005) found that among 233 university students enrolled in Arabic language programs in the United States, the correlations between the FLCAS and students' final course grades and listening comprehension grades were −.54 and −.53, respectively. Researchers have also examined the reliability and validity of the FLCAS. The reliability and concurrent validity of the FLCAS as measured by the Cronbach's α and correlations between anxiety measures was satisfactory, but the construct validity of the measure as assessed by exploratory factor analysis has varied across studies internationally (Horwitz, 1986; Aida, 1994; Cheng, et al., 1999; Kim, 2002; Matsuda & Gobel, 2004; Liu & Jackson, 2008; Tóth, 2008; Mak, 2011). In a leading paper on the constructs of the FLCAS, Aida (1994) investigated the constructs of the measure among 96 university students studying Japanese as a foreign language in the United States. The internal consistency reliability of the FLCAS as measured by Cronbach's α coefficient was .94. Principal component analysis with varimax rotation revealed seven factors, which reduced to four meaningful components in a rotated matrix: Speech Anxiety, Fear of Failing, Comfortableness with Japanese, and Negative Attitude. A part of the study by Cheng, et al. (1999) concerned the relationship of second language classroom anxiety measured by the FLCAS to second language writing anxiety assessed by the Daly and Miller's Writing Apprehension Test among 433 Taiwanese university students. Cronbach's α coefficient for the FLCAS was .95. The principal component analysis with varimax rotation produced two latent components in the 33 items of the FLCAS: Low Self-Confidence in Speaking English and General English Classroom Performance Anxiety. These two selected components explained 43.5% of the total variance.

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Matsuda and Gobel (2004) examined the links between the FLCAS and foreign language reading anxiety using 252 Japanese university students. Compared with other studies, Cronbach's α coefficient for the FLCAS was relatively low at .78. Matsuda and Gobel also found seven factors in the FLCAS by running principal component analysis using varimax rotation with eigenvalues greater than one, which was reduced to two meaningful components by using a scree plot test for interpretation: General English Classroom Performance Anxiety and Low Self-Confidence in Speaking English. Interestingly, these two latent factors were identical to the factors labeled by Cheng, et al. (1999), who studied Taiwanese university students. Liu and Jackson (2008) examined the relation of unwillingness to communicate and foreign language anxiety to self-related English proficiency using 547 university students learning English in China. The FLCAS was subjected to internal consistency reliability and factor analysis with varimax rotation, resulting in Cronbach's α coefficient of .92 and three latent components as speculated by several researchers (Aida, 1994; Liu & Jackson, 2008; Cao, 2011): Fear of Negative Evaluation (12 items), Communication Apprehension (seven items), and Test Anxiety (two items). In order to investigate the construct validity of the FLCAS, Tóth (2008) conducted a factor analysis on the data reported by 117 Hungarian university students. After examining the results of principal component analysis, Tóth reported eight underlying components in the 33 FLCAS items which could be reduced to four underlying factors: Global Foreign Language Ability, Fear of Inadequate Performance in English Classes, Attitudes to English Classes, and Teacher-related Anxieties. However, she reported that only the first two factors were important, accounting for 42.3% of the variance. Tóth also reported that Cronbach's α coefficient for the FLCAS was .93. More recently, Mak (2011) investigated the latent components of the FLCAS by performing exploratory factor analysis with varimax rotation among 313 Chinese students in Hong Kong. Mak adopted the four-point scale FLCAS to help the participants avoid responses at the midpoint. She found that the internal consistency of the adapted four-point FLCAS was .91 and that there were five latent components in the FLCAS: Speech Anxiety and Fear of Negative Evaluation, Uncomfortableness When Speaking with Native Speakers, Negative Attitudes towards the English Class, Negative Self-evaluation, and Fear of Failing the Class/Consequences of Personal Failure. As stated, most of the above studies utilized exploratory factor analysis, which is used to identify latent components that share common variance among observed variables. Only a few studies utilized confirmatory

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factor analysis to investigate whether a priori hypothetical models of the FLCAS fit the data (Cao, 2011; Park, 2012). For instance, Park closely examined the FLCAS items and tried to match each item with hypothetical one-, two-, three-, or four-factor models of the questionnaire using 918 university students in Korea. Using various fit indexes such as chi-square, the root mean square error of approximation, incremental fit index, and comparative fit index, he found that the four-factor model of the FLCAS fit the data better than the others. The potential problem with this study was that Park associated each item of the FLCAS with four hypothetical models on the basis of a subjective judgment. It is noteworthy that no studies to date have performed both exploratory and confirmatory factor analysis to understand the latent factor components of the FLCAS in one study, which is crucial because the components of the measure can be generated and confirmed among homogeneous sample groups. In sum, many researchers have attempted to find the underlying components of the FLCAS by performing factor analysis since the trailblazing attempt by Aida (1994). Three main reasons can be explained for different components of the FLCAS regardless of these continuous attempts across countries in the last two decades. First, Horwitz, et al. (1986) did not clarify the components of the FLCAS, leading subsequent researchers to misinterpret the aforementioned three components of the measure (Aida, 1994; Liu & Jackson, 2008; Tóth, 2008; Cao, 2011). Second, to find the underlying components of the FLCAS most researchers have used only exploratory factor analysis, which could be criticized for subjective judgment in factor rotation and labeling. Third, previous studies have used different versions of the FLCAS by translating the original version into the native language of the participants (Cheng, et al., 1999; Matsuda & Gobel, 2004; Tóth, 2008; Park, 2012). Understanding the components of the FLCAS through factor analysis is crucial because it will provide evidence to the construct validity of the scale and because the components can be used for subsequent analyses to further investigate the potential effects of anxiety on L2 acquisition (Thompson, 2004). The main purpose of the present study is to find the underlying components of the FLCAS by utilizing both exploratory factor analysis, which is used to generate theoretical components, and confirmatory factor analysis, which is used to examine whether a priori components generated by exploratory factor analysis adequately fit the data. Confirmatory factor analysis affirms hypothesized relations between observed variables and latent components, while allowing for associations among latent components (Bryant & Yarnold, 1995; Thompson, 2004). The internal consistency reliability of the FLCAS items were also examined as a necessary condition for test validity, affecting model fit indexes in confirmatory factor analysis (Kline, 2005; Salkind, 2012).

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METHOD Participants Two intact groups of students agreed to participate in this study: Group 1 was used for exploratory factor analysis and Group 2 was used for confirmatory factor analysis. For Group 1, cluster sampling was used because the participants consisted of 217 students taking an English conversation or composition course as required at a university in Korea. The sample size of 217 was chosen because the recommended ratio is five to 20 individuals to every measured variable for exploratory factor analysis (Thompson, 2004). Most of the participants in Group 1 (192) were majoring in either English or international cultural studies in the college of humanities, with 62 men and 155 women. Of the 217 students, 33 were freshmen, 83 were sophomores, 46 were juniors, and 55 were seniors, with an average age of about 21 yr. For Group 2, cluster and random sampling was used because a total of 244 participants were randomly chosen out of 948 university students who took English conversation as a required course and participated in the author's previous study, which investigated differential item functioning on the FLCAS (Park & French, 2013). Most of the participants in Group 2 were sophomores (n = 201), majoring in various academic fields in the college of humanities, social sciences, natural sciences, engineering, and medicine. They comprised 98 men and 146 women, with an average age of about 21 yr. Both groups of participants began to learn English in the third grade of elementary school as a required course. Since then, they had learned English for about two to four hours per week from elementary school to college, spending a great deal of time outside the classroom to improve their English proficiency. Their English proficiency ranged from beginning level to advanced level with the score ranges between 220 and 980, as determined by the Test of English for International Communication (TOEIC). These large individual score differences might be due to situational and trait variables such as foreign language anxiety, motivation for learning English, and language learning strategies employed by learners both inside and outside the classroom to facilitate English learning (Skehan, 1991; Horwitz, 2008). Measure The Foreign Language Classroom Anxiety Scale (FLCAS) consists of 33 Likert-scale items rated on a 5-point scale with anchors 1: Strongly disagree and 5: Strongly agree (see Appendix). These anxiety items are related to several components including communication apprehension associated with anxiety stemming from communicating with other people, test

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anxiety associated with a fear of failure in a test situation, and fear of negative evaluation derived from being evaluated negatively by other people. The Korean version of the FLCAS, which was translated by the author and effectively used to measure students' anxiety in previous studies, was used to minimize students' errors in comprehending the original English version (Park & French, 2013). In translation, the terms “language” and “foreign language” used in the original version were replaced with “English” to better suit Korean learners. For instance, the original item “I never feel quite sure of myself when I am speaking in my foreign language class” was revised as “I never feel quite sure of myself when I am speaking in my English class.” Caution must be taken in score interpretation because high scores on some items, or straightforward items, indicate high anxiety, whereas high scores on other items, or reverse-scored items, indicate low anxiety. The latter were Items 2, 5, 8, 11, 14, 18, 22, 28, and 32, the scores of which should be reversed for data analysis so that high scores on these items indicate high anxiety. In addition to the FLCAS, the participants' demographic information such as sex, school year, age, academic major, and the scores of Test of English for International Communication were obtained. Data Collection and Analysis The data for the students in Group 1 were collected in class by five native English-speaking teachers (three Americans, one Briton, and one Canadian) who taught English conversation and/or English composition. When collecting the data, the teachers briefly explained the nature of this study to students, followed by instructions on how to respond to the FLCAS items, which do not have either correct or wrong answers. Students were specifically asked to respond to the items carefully because high scores on some items represent high anxiety, whereas the reverse held true in other items. Students were encouraged to ask any questions when they did not understand the FLCAS items and to respond to each item sincerely and honestly. In a similar way, the data for the students in Group 2 were collected by eight native English-speaking teachers who taught English conversation: three Americans, three Canadians, one Briton, and one Australian. For data analysis, maximum likelihood exploratory factor analysis with direct oblimin rotation was performed to identify latent components of the FLCAS for the 217 participants in Group 1. Then confirmatory factor analysis was performed to examine whether the components identified in the exploratory factor analysis adequately fit the data, using 244 participants in Group 2. As per the recommendation of several researchers, the model fit indices used in confirmatory factor analysis were chi-square sta-

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tistic, the ratio of chi-square statistic to degrees of freedom, the root mean square error of approximation, incremental fit index, and comparative fit index (Browne & Cudeck, 1993; Hu & Bentler, 1995; Kline, 2005). In addition to exploratory and confirmatory factor analysis, internal consistency and split-half reliability of the FLCAS items was computed for the first group of 217 participants. The SPSS and AMOS statistical packages were used to perform exploratory and confirmatory factor analysis, respectively. RESULTS The values of skewness and kurtosis of the 33 FLCAS items for Groups 1 and 2 were within the range between 2 and −2, indicating that both of the datasets had generally normal distribution. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.90, while the chi-square of Bartlett's test for sphericity was 3059.06 (p < .001), indicating that the data were suitable for factor analysis. Maximum likelihood exploratory factor analysis with Direct Oblimin rotation was performed using the first group of 217 participants to find the latent components of the FLCAS. The result of factor analysis using eigenvalues greater than one and scree plot examination indicated three latent components in the FLCAS, which reduced to two meaningful components because the third component contained only two items and accounted for only 4.8% of the total variance. Thompson (2004) recommended that a factor should encompass at least three items for the factor to explain the total variance meaningfully. A factor loading of .5 and above was used as a cutoff for inclusion of an observed variable in interpreting each factor. The results are shown in Table 1, which includes observed variables (items in the FLCAS), the number of factors, factor loadings, communalities, and the total variance explained by each factor. The first factor, Communication Apprehension and Understanding, was related to apprehension or anxiety about communicating with other people in a second/foreign language, with the element of understanding or lack of understanding. This factor comprised Items 27, 26, 25, 12, 31, 33, 13, 29, 15, 16, 4, 19, and 20, accounting for 32.3% of the total variance. The second factor, Communication Apprehension and Confidence, comprised Items 28, 18, 9, 14, 32, 8, 1, 11, 3, and 2, explaining 6.38% of the total variance. The second factor was similar to the first factor because it was also related to apprehension or anxiety about communicating with other people in a second/foreign language, but with the element of confidence or lack of confidence in communicative situations. It should be noted that these two factors shared a common label of Communication Apprehension.

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G-P. PARK TABLE 1 TWO COMPONENTS OF THE FLCAS (N = 217) Item of the FLCAS

Factor 1

27

.76

0.67

26

.71

0.55

25

.67

0.44

12

.64

0.43

31

.64

0.42

33

.63

0.49

13

.60

0.37

29

.60

0.41

15

.58

0.34

16

.58

0.35

4

.58

0.38

19

.58

0.34

20

.58

Factor 2

h2

0.39

28

−.78

0.61

18

−.72

0.53

9

−.66

0.47

14

−.66

0.43

32

−.64

0.41

8

−.63

0.40

1

−.60

0.39

11

−.58

0.34

3

−.58

0.38

2

−.53

0.29

Variance explained

32.321

6.38

The internal consistency and split-half reliability of the FLCAS was computed using Cronbach's α coefficient and the Spearman-Brown formula. The Cronbach's α coefficients of all 33 items in the FLCAS, the 13 items of the first factor, and the 10 items of the second factor were .93, .90, and .87, respectively, whereas the Spearman-Brown correlations of the 33 items in the FLCAS, the 13 items of the first factor, and the 10 items of the second factor were .92, .90, and .86, respectively. In addition, the correlation between these two factors was .71 (p < .01). The significant and high correlations between the two underlying components supported the use of Direct Oblimin rotation in the present study rather than varimax rotation, because the former allows for the correlations between the latent components (Bryant & Yarnold, 1995; Thompson, 2004).

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Maximum likelihood exploratory factor analysis with Direct Oblimin rotation showed that there were two underlying components in the FLCAS which were distinct but statistically significantly related to each other. Based on this finding, confirmatory factor analysis was performed using the second group of 244 participants to examine to what extent the data adequately fit the a priori two-factor model of the FLCAS. The results of confirmatory factor analysis are shown in Table 2. TABLE 2 GOODNESS-OF-FIT INDEXES FOR INDEPENDENCE AND TWO-FACTOR MODELS (N = 244) Model Independence Two-factor

χ2

df

χ2/df

RMSEA

2781.86†

253

11.0

0.203

484.68†

229

2.12

0.068

IFI

CFI

0.900

0.899

†p < .01.

Table 2 shows two models: the independence model in which each item represented a factor, and the two-factor model found in the exploratory factor analysis. The chi-squares of the independence model and the two-factor model were statistically significant, indicating that the models did not fit the data. Since the chi-square statistic tends to increase its magnitude when the sample size exceeds 200 participants, as in the present study, other model fit indexes were examined (Schumaker & Lomax, 1996). The ratio of chi-square to degrees of freedom of the two-factor model indicated better fit to the data than that of the independence model. Some researchers recommended that the ratio of chi-square to degrees of freedom of 2.1 is declared adequate (Onwuegbuzie, Bailey, & Daley, 2000b). The root mean square error of approximation of the two-factor model fit the data better than that of the independence model, indicating a reasonable error of approximation (Browne & Cudeck, 1993). Even though Bentler's comparative fit index slightly fell short of a cutoff point of .90, Bollen's incremental fit index was acceptable. In short, even though the chi-square statistic of the two-factor model of the FLCAS was significant, other model fit indexes showed that the two-factor model in general was acceptable. DISCUSSION The present study examined the latent components of the FLCAS by performing exploratory and confirmatory factor analysis using two different groups of university students learning English in Korea. The internal consistency and split-half reliabilities of the 33 items of the FLCAS and the two underlying components of the FLCAS as determined by Cronbach's α coefficient and the Spearman-Brown formula ranged between .86 and .93. These high internal consistency reliabilities of the FLCAS in all the 33 items and in each component lent support to previous studies where al-

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pha coefficients of the FLCAS were satisfactory (Aida, 1994; Cheng, et al., 1999; Matsuda & Gobel, 2004; Elkhafaifi, 2005; Liu & Jackson, 2008; Cao, 2011). It should be noted that internal consistency reliability, which is a measure calculated from the correlations between items on the test instrument, is a necessary condition of validity, affecting the model fit indexes used in confirmatory factor analysis (Kline, 2005; Salkind, 2012). Two latent components of the FLCAS, Communication Apprehension and Understanding and Communication Apprehension and Confidence, were found after performing the maximum likelihood exploratory factor analysis with direct oblimin rotation. For the number of components, this finding supported some studies where two components, Low Self-Confidence in Speaking English and General English Classroom Performance Anxiety, were found previously in the FLCAS (Cheng, et al., 1999; Matsuda & Gobel, 2004), but conflicted with other studies where three, four, or five components were found (Aida, 1994; Kim, 2002; Liu & Jackson, 2008; Cao, 2011; Mak, 2011; Park, 2012). With a close look, however, the two components of this and two other studies encompassed quite different FLCAS items, as described below. Caution must be exercised in the interpretation of these findings as lack of construct validity of the FLCAS because researchers have lent support to the concurrent and construct validity of the scale (Horwitz, 1986; Onwuegbuzie, et al., 2000b; Park & French, 2013). The reason for different findings across studies regarding the components of the FLCAS might be due to the different versions of the FLCAS such as the English version, the Chinese version, and the Korean version according to the native language of the participants. Native speaking teachers who taught English conversation and collected the data in the present study might be a reason for the variation in the FLCAS responses. In addition, it might be due to the subjectiveness of exploratory factor analysis in terms of factor extraction, factor rotation, and factor labeling (Bryant & Yarnold, 1995; Thompson, 2004). For instance, most previous studies have used varimax rotation to make it easier to identify each variable with a factor, but the present study used Direct Oblimin rotation in which latent components were allowed to correlate at the expense of interpretability. In consideration of the statistically significant correlations between the two factors in the present study, Direct Oblimin rotation rather than varimax rotation should be the choice in extracting factor components from this scale. In addition, even though Cheng, et al. (1999) and Matsuda and Gobel (2004) found two identical components in the FLCAS, these two components contained different items than those found in the current study. For instance, the component of Low Self-Confidence in Speaking English contained 10 items including Items 1, 2, 7, 13, 14, 18, 23, 24, 27, and 31 in Cheng et al's study, but contained eight items including Items 1, 5, 7, 10,

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17, 18, 23, and 28 in Matsuda and Gobel's study. In the same vein, the component of General English Classroom Performance Anxiety encompassed Items 4, 10, 15, 19, 20, 21, 25, 29, 30, and 33 in Cheng, et al's study, but comprised Items 2, 3, 4, 9, 12, 14, 16, 19, 26, 27, 29, 31, and 33 in Matsuda and Gobel's study. Thus, discussion points should address that the present study found two underlying components in the FLCAS which were significantly correlated with each other: Communication Apprehension and Understanding and Communication Apprehension and Confidence. Interestingly, Communication Apprehension defined as apprehension in communicative situations in a second/foreign language was used in the labeling of these two factors in the present study, a point that was also discussed in other studies (Aida, 1994; Cheng, et al., 1999; Tóth, 2008). One interpretation of this finding was that the FLCAS consisted of 33 items reflective of two or several multidimensional components, but the core component might be Communication Apprehension to which other peripheral components were related. Another interpretation was that the FLCAS might consist of a unidimensional component measuring Communication Apprehension in the classroom, rather than multidimensional components. That might be why even though Horwitz, et al. (1986) claimed that the items were “reflective of communication apprehension, test anxiety, and fear of negative evaluation in the foreign language classroom,” they did not further match these potential components of the FLCAS with each item (Horwitz, et al., 1986: p. 129). That is, even though the FLCAS seemed to consist of several aforementioned components, it might measure the unidimensional component of Communication Apprehension. The latent components of the FLCAS found in the exploratory factor analysis were supported by subsequent confirmatory factor analysis through various fit indexes such as the ratio of chi-square to degrees of freedom, the root mean square error of approximation, incremental fit index, and comparative fit index (Browne & Cudeck, 1993; Hu & Bentler, 1995; Kline, 2005). Again, this finding proved that the FLCAS measured and reflected aforementioned two latent components, providing empirical evidence to build the construct validity of the scale. CONCLUSION This study produced several important findings regarding the latent components of the FLCAS developed by Horwitz, et al. (1986) by performing factor analysis in a two-group Korean sample. The present study provided evidence for the constructs and construct validity of the FLCAS. Since its development, the components of the FLCAS have attracted the interest of researchers, most of whom used exploratory factor analysis to

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find the components. In the present study, the components of the FLCAS were explored through exploratory factor analysis followed by confirmatory factor analysis to assess the model's fit to the data. Subsequent researchers could use these constructs in future studies including the investigation into the relationship between the components of the scale and L2 acquisition. Generalization of the findings of the present study should be made with caution because the participants were specific groups of university students learning English in Korea and because they were selected from intact groups. Thus, replications of the findings should be made among various second language learners in different language learning contexts with various ranges of sample sizes (Horwitz, 2008). In addition, the major construct of communication apprehension of the FLCAS should be investigated in depth with other constructs such as motivation, willingness to communicate, and learning styles quantitatively as well as qualitatively because these constructs seem to be intricately related to each other in L2 acquisition (Liu & Jackson, 2008). In consideration of the limitations of exploratory factor analysis, it is time to conduct confirmatory factor analysis to test the latent constructs of the FLCAS generated by theoretical speculations or exploratory factor analysis. In addition, studies on differential item functioning on the FLCAS across members of different subgroups such as sex of participants should be undertaken to build further validity evidence of the measure. REFERENCES

AIDA, Y. (1994) Examination of Horwitz, Horwitz, and Cope's construct of foreign language anxiety: the case of students of Japanese. Modern Language Journal, 78, 155168. BROWNE, M. W., & CUDECK, R. (1993) Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models. Newbury Park, CA: Sage. Pp. 136-162. BRYANT, F. B., & YARNOLD, P. R. (1995) Principal-components analysis and exploratory and confirmatory factor analysis. In L. G. Grimm & P. R. Yarnold (Eds.), Reading and understanding multivariate statistics. Washington, DC: American Psychological Association. Pp. 1-18. CAO, Y. (2011) Comparison of two models of Foreign Language Classroom Anxiety Scale. Philippine ESL Journal, 7, 73-93. CHEN, T-Y., & CHANG, G. B. Y. (2004) The relationship between foreign language anxiety and learning difficulties. Foreign Language Annals, 37, 279-289. CHENG, Y-S., HORWITZ, E. K., & SCHALLERT, D. L. (1999) Language anxiety: differentiating writing and speaking components. Language Learning, 49, 417-446. ELKHAFAIFI, H. (2005) Listening comprehension and anxiety in the Arabic language classroom. The Modern Language Journal, 89, 206-220. HORWITZ, E. K. (1986) Preliminary evidence for the reliability and validity of a foreign language anxiety scale. TESOL Quarterly, 20, 559-564.

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THOMPSON, B. (2004) Exploratory and confirmatory factor analysis. Washington, DC: American Psychological Association. TÓTH, Z. (2008) A foreign language anxiety scale for Hungarian learners of English. WoPaLP, 2, 55-78. WATSON, D., & FRIEND, R. (1969) Measurement of social-evaluative anxiety. Journal of Consulting and Clinical Psychology, 33, 448-457. ZHANG, L. J. (2000) Uncovering Chinese ESL students' reading anxiety in a study-abroad context. Asia Pacific Journal of Language in Education, 3, 31-56. Accepted March 25, 2014. APPENDIX FOREIGN LANGUAGE CLASSROOM ANXIETY SCALE Please read each item carefully and choose one of the options in the example below. Example:

(1) Strongly disagree (2) Disagree (4) Agree Korean (as administered)

1

(3) Neutral

(5) Strongly agree

나는 영어 수업 시간에 영어로 말을 할 때 자 신이 전혀 없다.

English I never feel quite sure of myself when I am speaking in my English class.

2R 나는 영어 수업 시간에 실수하는 것을 걱정하

I don’t worry about making mistakes in English class.

3

나는 영어 수업 시간에 교수님이 나에게 질문 하시려는 것을 알았을 때 떨린다.

I tremble when I know that I’m going to be called on in English class.

4

나는 교수님이 영어로 말씀하시는 것을 이해 하지 못할 때 불안해진다.

It frightens me when I don’t understand what the teacher is saying in English.

지 않는다.

5R 나는 영어 수업을 더 듣는다 해도 전혀 부담

It wouldn’t bother me at all to take more English classes.

6

영어 수업 시간에 수업과 관계 없는 것을 생 각하고 있는 나 자신을 발견한다.

During English class, I find myself thinking about things that have nothing to do with the course.

나는 다른 학생들이 나보다 영어 능력이 더욱 뛰어나다는 생각을 한다.

I keep thinking that the other students are better at English than I am.

되지 않을 것이다.

7

8R 나는 영어 수업 시간에 시험을 볼 때 보통 편 안하다.

I am usually at ease during tests in my English class.

나는 영어 수업 시간에 미리 준비하지 않고 말을 해야 할 때 매우 불안해진다.

I start to panic when I have to speak without preparation in English class.

10 나는 영어 수업 시간에 낙제 점수를 받을까

I worry about the consequences of failing my English class.

11R 나는 일부 사람들이 왜 영어 수업에 대해 초

I don’t understand why some people get so upset over English classes.

9

걱정한다.

조해하는지 이해할 수 없다.

12 나는 영어 수업 시간에 너무 긴장되어 내가 아는 것도 기억할 수 없다.

In English class, I can get so nervous I forget things I know. (continued on next page)

Note.—Superscript R indicates reverse scored items.

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FACTOR ANALYSIS OF FLCAS APPENDIX (CONT’D) FOREIGN LANGUAGE CLASSROOM ANXIETY SCALE Korean (as administered)

English

13 나는 영어 수업 시간에 자발적으로 질문에 답

It embarrasses me to volunteer answers in my English class.

14R 나는 원어민과 영어로 대화를 해도 불안하지

I would not be nervous speaking English with native speakers.

15 나는 교수님이 수정해주시는 것을 이해할 수

I get upset when I don’t understand what the teacher is correcting.

16 나는 비록 영어 수업을 잘 준비한다 해도 영

Even if I am well prepared for English class, I feel anxious about it.

17 나는 종종 영어 수업을 빠지고 싶은 생각이

I often feel like not going to my English class.

18R 나는 영어 수업 시간에 영어로 말을 할 때 자

I feel confident when I speak in English class.

19 나는 영어 교수님이 내가 실수할 때마다 수정

I am afraid that my English teacher is ready to correct every mistake I make.

20 나는 영어 수업 시간에 질문을 받으려 할 때

I can feel my heart pounding when I am going to be called on in English class.

21 나는 영어 시험 공부를 하면 할수록 더욱 혼

The more I study for an English test, the more confused I get.

22R 나는 영어 수업을 잘 준비해야 하는 부담감을

I don’t feel pressure to prepare very well for English class.

23 나는 늘 다른 학생들이 나보다 영어 회화를

I always feel that the other students speak English better than I do.

24 나는 다른 학생들 앞에서 영어로 말을 할 때

I feel very self-conscious about speaking English in front of other students.

25 나는 영어 수업의 진도가 빨라 따라가지 못할

English class moves so quickly, I worry about getting left behind.

26 나는 영어 수업이 다른 수업보다 더욱 긴장되

I feel more tense and nervous in my English class than in my other classes.

27 나는 영어 수업 시간에 영어로 말을 할 때 초

I get nervous and confused when I am speaking in my English class.

28R 나는 영어 수업을 들으러 갈 때 자신감과 여

When I’m on my way to English class, I feel very sure and relaxed.

29 나는 영어 교수님이 영어로 말씀하시는 모든

I get nervous when I don’t understand every word the English teacher says.

30 나는 영어로 말을 하기 위해 배워야 하는 문

I feel overwhelmed by the number of the rules that you have to learn to speak English.

하는 것이 창피하다. 않을 것이다.

없을 때 초조해진다. 어 수업이 걱정된다. 든다.

신감이 있다.

해주실까 걱정 된다.

심장이 두근거리는 것을 느낄 수 있다. 란스러워진다.

느끼지는 않는다.

더욱 잘 한다고 느낀다. 그들을 많이 의식한다. 까 걱정한다.

고 초조해지는 느낌이 든다. 조해지고 혼란스러워진다. 유가 있는 느낌이 든다.

단어를 이해할 수 없을 때 초조해진다. 법의 수량에 압도된다.

31 나는 영어로 말을 할 때 다른 학생들이 비웃

I am afraid that the other students will laugh at me when I speak English.

32R 나는 영어 원어민들이 주변에 있어도 불안하

I would probably feel comfortable around native speakers of English.

을까 두렵다.

지 않을 것이다.

33 나는 영어 교수님이 내가 미리 준비하지 않은

I get nervous when the English teacher asks questions which I haven't prepared in advance. Note.—Superscript R indicates reverse scored items. 것을 질문하실 때 초조해진다.

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Factor analysis of the Foreign Language Classroom Anxiety Scale in Korean learners of English as a foreign language.

This study examined the latent constructs of the Foreign Language Classroom Anxiety Scale (FLCAS) using two different groups of Korean English as a fo...
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