2007 Achievement Emotions in Germany and China
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Transcript of 2007 Achievement Emotions in Germany and China
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302
ACHIEVEMENT EMOTIONS IN GERMANY AND CHINAA Cross-Cultural Validation of the Academic Emotions
QuestionnaireMathematics
ANNE C. FRENZELUniversity of MunichTODD M. THRASH
College of William & MaryREINHARD PEKRUN
THOMAS GOETZUniversity of Munich
The aim of this study was to establish the construct comparability and cross-cultural utility of the Germanand Chinese versions of the Academic Emotions QuestionnaireMathematics (AEQ-M). Based on datafrom 312 German and 579 Chinese eighth-grade students, mean and covariance structures analysisrevealed that the AEQ-M shows a high degree of measurement invariance across cultures. In addition, theemotions assessed by the AEQ-M showed similar patterns of relationships with self-reports of achieve-ment, parental achievement expectations, and attributions of success and failure across the German andChinese samples. Confirming earlier findings, Chinese students were found to experience higher levels ofanxiety in mathematics. They were also found to experience more enjoyment, pride, and shame, and lessanger, than German students. This research supports the use of the AEQ-M in cross-cultural research andprovides data about a broader range of achievement emotions than has been investigated previously.
Keywords: emotions; achievement; construct comparability; measurement invariance; mean and covari-ance structures analysis
The primary aim of this study was to establish the construct comparability of achieve-ment emotions across samples of German and Chinese students. Specifically, we com-pared the original German-language version and the new Chinese-language version of theAcademic Emotions QuestionnaireMathematics (AEQ-M; Pekrun, Goetz, & Frenzel,2005), an adapted version of the Academic Emotions Questionnaire (AEQ; Pekrun, Goetz,& Perry, 2005; Pekrun, Goetz, Titz, & Perry, 2002) that assesses enjoyment, pride, anxi-ety, anger, and shame in the context of learning mathematics.
Translating psychological content from one language to another poses many challenges,particularly with emotion-oriented content (e.g., Russel & Sato, 1995). However, as Schwarzerand Kim (1984) argued, In order to stimulate cross-cultural research these difficulties must beresolved in adapting inventories for assessment with different national groups (p. 277). Toexamine construct comparability, we used mean and covariance structures (MACS) analysis
AUTHORS NOTE: The Chinese version of the Academic Emotions QuestionnaireMathematics is available upon request fromthe first author, and the German and English versions are available from the third author. Thanks to Shijin He, Huizhen Ye, Y. T.Wan, and Rafael Buemia for their help with translation and data collection. Correspondence concerning this article should beaddressed to Anne C. Frenzel, University of Munich, Department of Psychology, Leopoldstr. 13, 80802 Munich, Germany, phone+49 89 2180 6047, fax +49 89 2180 5250; e-mail: [email protected].
JOURNAL OF CROSS-CULTURAL PSYCHOLOGY, Vol. 38 No. 3, May 2007 302-309DOI: 10.1177/0022022107300276 2007 Sage Publications
2007 SAGE Publications. All rights reserved. Not for commercial use or unauthorized distribution. at SWETS WISE ONLINE CONTENT on May 21, 2007 http://jcc.sagepub.comDownloaded from
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Frenzel et al. / ACHIEVEMENT EMOTIONS IN GERMANY AND CHINA 303
(Cheung & Rensvold, 1999; Little, 1997), a statistical technique that can detect psycho-metric problems that result from cultural biases in item content, translation errors, acqui-escence biases, and other factors (Little, 1997).
If successful in establishing construct comparability, we sought to further establishthe utility of the AEQ-M by examining convergent validity and mean differences in achieve-ment emotions. Regarding convergent validity, we examined relationships between achieve-ment emotions and several other achievement-relevant variables, including school achievementand attributions for success and failure (see Pekrun et al., 2002). Similar patterns of relation-ships across German and Chinese samples would support the utility of the AEQ-M in cross-cultural research. Regarding mean levels of achievement emotions, differences across cultureswere expected. Theory and empirical research suggest that there are differences in mean levelsof achievement motivation and other achievement-related constructs across Eastern andWestern countries (e.g., Chen & Stevenson, 1995; Salili, 1994). Concerning achievementemotions in particular, studies indicate that students from Eastern countries tend to experi-ence higher levels of achievement anxiety than do students from Western countries (e.g.,OECD, 2004). However, little is known about differences in achievement emotions otherthan anxiety. Our research extends past research by examining mean differences in a rangeof achievement emotions.
METHOD
PARTICIPANTS AND PROCEDURE
A total of 891 students participated in the study. Care was taken to maximize the com-parability of the German and Chinese samples. The German sample consisted of 312eighth-grade students (143 female, 165 male, and 4 unspecified) from three schools nearMunich, comprising a mix of socioeconomic backgrounds. The Chinese sample consistedof 579 eighth-grade students (282 female, 263 male, and 34 unspecified) from four mid-dle schools in Quanzhou and Xiangtan, also from diverse socioeconomic backgrounds.Mean ages in these samples were 14.99 (SD = .64) and 14.34 (SD = 1.01) years, respec-tively. Although students from both countries were in the eighth grade, the Chinesestudents were significantly younger than the German students (t = 10.14; p < .01).However, data from our previous studies indicate that there are no substantial changes inachievement-related emotions beyond the age of 13 (grade 7), at least in Germany (Pekrunet al., 2004). Therefore, the age difference is unlikely to pose a substantive threat to thevalidity of our findings. Participation was voluntary, and assessment occurred during reg-ular class hours under the supervision of students mathematics teachers and with the con-sent of school principals.
MEASUREMENT OF EMOTIONS
The AEQ-M (Pekrun et al., 2005) was used to assess mathematics-related enjoyment(9 items), pride (6 items), anxiety (6 items), anger (8 items), and shame (8 items). For eachemotion, the AEQ-M includes items related to three different situationsinstruction,homework/studying, and testingeach rated using a 5-point Likert-type scale rangingfrom strongly disagree to strongly agree. Sample items are as follows: enjoyment, I enjoymy math classes; pride, After doing my math homework, I am proud of myself;
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304 JOURNAL OF CROSS-CULTURAL PSYCHOLOGY
anxiety, During a math test, I worry that I will get a bad grade; anger, I am so angryduring my math classes that Id like to quit; and shame, I am ashamed that I cannotanswer my math teachers questions well.
For the present adaptation of the AEQ-M into Chinese, both the English and Germanversions were used as the basis for translation by three trilingual students of educationalpsychology. The translations were then blindly back-translated into German by a bilingualChinese educational psychologist, and the wording of the items was further polished toreach the closest possible equivalence across language versions. In the current investiga-tion, each emotion scale was found to be internally consistent in both the German andChinese samples (enjoyment, = .89/.87; pride, = .85/.83; anxiety, = 80/.78; anger, = 85/.85; shame, = .85/.76).
VALIDITY MEASURES
Six validity variables were assessed using single items: achievement, What was your mid-term grade in mathematics?; parental achievement expectations, My parents believe that I canachieve the following grade in mathematics; attributions of success and failure to ability, If Isucceed [fail] in mathematics, it is usually because I am simply [not] talented in mathematics;and attributions of success and failure to effort, . . . because I have put in a lot of [not enough]effort. Achievement and parental expectations were rated on country-specific grading scales,and the attribution variables were rated using 5-point Likert-type agreement scales. These itemswere translated using the same translation procedures as described above. We did not examinethe measurement invariance of these measures because that would have required the use ofmultiple-item measures. However, due to their straightforward content, the validity measuresare likely to have similar measurement properties across cultures.
RESULTS
GERMAN-CHINESE MEASUREMENT INVARIANCE AND CONSTRUCT COMPARABILITY
We conducted MACS analyses using maximum likelihood estimation. For each emotion,we specified a baseline model (Model 1) that is identical in form across samples. The baselinemodel was a modified three-factor confirmatory factor analysis model. Instruction, home-work/studying, and testing items were specified to load on separate first-order latent variables.Each first-order latent variable was specified to be fully determined by a phantom second-order latent variable (see Little, 1997), and covariances were modeled among second-orderlatent variables. With this type of model, second-order latent variables may be rescaled into thestandardized metric needed for the testing of equality of correlations across samples (see thefollowing section, Convergent Validity), while allowing the variances of first-order latent vari-ables to accurately reflect any differences in variance that exist between samples. Each base-line model was identified by standardizing the second-order latent variables in both groups,setting item uniqueness means to 0 and item uniqueness variances to 1 in both groups, settingthe intercepts of the first-order latent variables to 0 and their loadings on the second-order latentvariables to 1 in the German sample, and constraining the loading and intercept of one item perfirst-order latent variable to be equal across samples. The baseline model (Model 1) had goodfit for all five emotions, indicating invariance of model form (see Table 1). This implies that thelatent variables were comparable in a qualitative sense across samples.
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Frenzel et al. / ACHIEVEMENT EMOTIONS IN GERMANY AND CHINA 305
Next we tested whether the latent variables had comparable metrics by examining invari-ance of item loadings (slopes, i.e., the expected change in an item given a one-unit increasein the latent variable) and intercepts (i.e., the expected value of an item when the latent vari-able equals zero). As recommended by Little (1997), we examined invariance of measure-ment model parameters using a modeling rationale (i.e., indexes of practical fit). Loss of fitassociated with the addition of equality constraints was considered negligible if CFI(Comparative Fit Index) and MNCI (McDonalds Non-Centrality Index) were less than orequal to .02 (Cheung & Rensvold, 1999). We used a statistical rationale (i.e., LikelihoodRatio Test) to examine invariance of latent variable parameters. Because we conducted sep-arate analyses for each of the five emotions, we used an adjusted alpha level of .01.
Constraining item loadings to be equal across groups (Model 2) was found not to decreasefit for any emotion. Additionally constraining item intercepts (Model 3) yielded a loss of fitfor enjoyment and pride but not for anxiety, anger, or shame. To isolate the source of nonin-variance for enjoyment, we examined three alternatives to Model 3, each with the interceptconstraints for one latent variable removed. As a result, for enjoyment, Model 3 was rejectedin favor of Model 3E, a partial-invariance model in which intercepts of the manifest variablesrepresenting the homework enjoyment latent variable were free to vary across samples. Wefollowed the same procedure to isolate the source of noninvariance for pride. As a result,Model 3 was rejected in favor of Model 3P, a partial-invariance model in which intercepts ofthe manifest variables representing the testing pride latent variable were free to vary acrosssamples. Models 3E and 3P fit as well as their corresponding models in Model 2. Fitindexes for all models are shown in Table 1.
TABLE 1Tests of Invariance of the Measurement Model
and Latent Means: Model Fit Indexes
Model
(1) (2) (3) (3E) and (3P) (4)
Invariance of Invariance of Invariance of Loadings and Partial Invariance of
Emotion Index Model Form Loadings Intercepts Invariance Latent Means
Enjoyment 2 / df 143.11/48 162.77/54 237.19/60 174.85/58 300/60CFI .97 .97 .95 .97 .93
MNCI .95 .94 .91 .95 .74Pride 2 / df 20.77/12 29.27/15 130.83/18 33.18/17 142/19
CFI 1.00 .99 .94 .99 .94MNCI 1.00 .99 .94 .99 .93
Anxiety 2 / df 20.08/12 32.97/15 61.36/18 143/21CFI .99 .99 .97 .90
MNCI 1.00 .98 .98 .93Anger 2 / df 119.73/34 124.17/39 149.73/44 194/47
CFI .96 .96 .95 .94MNCI .95 .95 .94 .92
Shame 2 / df 106.32/34 111.57/39 155.98/44 426/47CFI .96 .96 .94 .78
MNCI .96 .96 .94 .81
NOTE: CFI = Comparative Fit Index; MNCI = McDonalds Non-Centrality Index. The partial invariance modelfor enjoyment (Model 3E) includes cross-group equality constraints on instruction and testing (but not home-work) intercepts, and the partial invariance model for pride (Model 3P) includes cross-group equality constraintson instruction and homework (but not testing) intercepts.
2007 SAGE Publications. All rights reserved. Not for commercial use or unauthorized distribution. at SWETS WISE ONLINE CONTENT on May 21, 2007 http://jcc.sagepub.comDownloaded from
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306 JOURNAL OF CROSS-CULTURAL PSYCHOLOGY
CONVERGENT VALIDITY
To examine convergent validity, the six validity variables were added to the full or partialmeasurement invariance models as single-item indicators of latent variables without unique-nesses. This portion of the model was identified by standardizing the latent variables in bothsamples. Validity variable loadings and intercepts were unconstrained. All pairwise covari-ances among second-order emotion latent variables and validity latent variables were modeledand were scaled to the correlation metric as a result of our method of identification.
Consistent with previous theory and research on achievement emotions (see Pekrunet al., 2002), we observed the following pattern of significant relationships, which held inboth countries (except where noted) and for all situations (see Table 2). The positive emo-tions were positively related to mathematics grade, parental expectations, and success attri-butions to ability, whereas the negative emotions were negatively related to these variables.Failure attributions to lack of ability showed the opposite pattern. The positive emotionswere positively related to success attributions to effort, whereas the negative emotionswere not systematically related to this variable. None of the emotions except anxiety andshame among Chinese participants were related to failure attributions to lack of effort.
Constraining all correlations between emotion latent variables and the validity latentvariables to be equal across samples yielded a loss of fit for anxiety (2(18) = 49.74,p < .01), anger (2(18) = 47.98, p < .01), and shame (2(18) = 44.33, p < .01) but notfor enjoyment or pride. Analyses of the source of noninvariance for anxiety, anger, andshame revealed that each of these emotions experienced in the homework/studying context(i.e., at home) was more negatively related to mathematics grade and parental expectationsin China than in Germany. In addition, anxiety and shame, regardless of situation, weremore positively related to failure attributions to lack of effort in China than in Germany.When constraints on these correlations were excluded, the constrained models fit as wellas the unconstrained models.
DIFFERENCES IN THE MEAN LEVELS OF ACHIEVEMENT EMOTIONS
To examine differences in mean levels of each emotion, we used the full or partial mea-surement invariance models as baseline models. For anxiety, anger, and shame, means ofall three latent variables (instruction, homework, and testing situations) were constrainedequal across samples. For enjoyment and pride, only the means of the two latent variableshaving invariant intercepts were constrained equal across samples.
The constraints on latent means yielded significant decrements in fit for all five emo-tions (p < .01; see Table 1, Model 4). Follow-up tests revealed that these overall differenceswere attributable to significant differences for each situation tested. Regardless of situa-tion, Chinese students experienced higher levels of enjoyment, pride, anxiety, and shame,whereas German students experienced higher levels of anger.
DISCUSSION
In this study, the AEQ-M, which assesses mathematics-related enjoyment, pride, anxiety,anger, and shame, was translated from German to Chinese and tested for measurementinvariance across the two language versions. A high degree of measurement invariance acrossthe German and Chinese versions of the AEQ-M was demonstrated, thus supporting thecross-cultural comparability of the emotion constructs assessed by the AEQ-M.
2007 SAGE Publications. All rights reserved. Not for commercial use or unauthorized distribution. at SWETS WISE ONLINE CONTENT on May 21, 2007 http://jcc.sagepub.comDownloaded from
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307
TABL
E 2
Cor
rela
tions
Bet
wee
n A
chie
vem
ent E
mot
ions
and
Ach
ievem
ent,
Pare
nta
l Exp
ecta
tions
,an
d A
ttrib
utio
ns W
ithin
Ger
man
and
Chi
nese
Sam
ples
Late
nt E
mot
ion
Enjoy
ment
Prid
eAn
xiet
yAn
ger
Sham
eVa
lidat
ing
Subc
onstr
uct
Cons
truct
(Situa
tion)
Ger
man
Chin
ese
Ger
man
Chin
ese
Ger
man
Chin
ese
Ger
man
Chin
ese
Ger
man
Chin
ese
Mat
hem
atic
s Te
st.66
**
.62
**
.53
**
.64
**
.50
**
.46
**
.51
**
.50
**
.34
**
.44
**
grad
eIn
stru
ctio
n.53
**
.39
**
.53
**
.45
**
.60
**
.54
**
.60
**
.50
**
.16
**
.11
*H
omew
ork
.54
**
.48
**
.41
**
.45
**
.32
**
.55
**
.40
**
.54
**
.27
**
.65
**
Pare
nta
l Te
st.62
**
.54
**
.49
**
.61
**
.47
**
.39
**
.53
**
.45
**
.32
**
.41
**
expe
ctat
ions
Inst
ruct
ion
.43
**
.35
**
.52
**
.44
**
.62
**
.52
**
.54
**
.45
**
.18
**
.08
Hom
ework
.51
**
.44
**
.36
**
.42
**
.34
**
.50
**
.34
**
.49
**
.34
**
.59
**
Failu
re
Test
.58
**
.52
**
.55
**
.40
**
.53
**
.41
**
.51
**
.37
**
.33
**
.38
**
attr
ibutio
n:In
stru
ctio
n.55
**
.42
**
.60
**
.43
**
.70
**
.58
**
.70
**
.42
**
.27
**
.26
**
abili
tyH
omew
ork
.53
**
.40
**
.40
**
.27
**
.51
**
.49
**
.47
**
.36
**
.33
**
.47
**
Failu
re
Test
.07
.06
.08
.04
.02
.19
**
.08
.09
.05
.12
*at
trib
utio
n:In
stru
ctio
n.09
.09
*.11
.06
.08
.11
*.04
.06
.05
.15
**
effo
rtH
omew
ork
.00
.00
.03
.01
.08
.21
**
.05
.01
.02
.17
*Su
cces
s Te
st.67
**
.65
**
.56
**
.51
**
.49
**
.41
**
.49
**
.37
**
.21
**
.37
**
attr
ibutio
n:In
stru
ctio
n.60
**
.39
**
.62
**
.44
**
.57
**
.53
**
.63
**
.39
**
-.11
.19
**
abili
tyH
omew
ork
.53
**
.38
**
.46
**
.38
**
.42
**
.44
**
.39
**
.28
**
-.17
*.51
**
Succ
ess
Test
.06
.13
*.15
*.16
**
.05
.22
**
.09
.08
-.08
.03
attr
ibutio
n:In
stru
ctio
n.18
**
.26
**
.20
**
.26
**
.14
.03
.02
.15
**
.13
*.17
**
effo
rtH
omew
ork
.14
*.19
**
.27
**
.20
**
.13
*.03
.09
.21
**
.07
.04
*p
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