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CURRENT RESEARCH IN SOCIAL PSYCHOLOGY


Volume 7, Number 15
Submitted: July 3, 2002
Resubmitted: July 16, 2002
Accepted: July 16, 2002
Publication date: July 23, 2002

ASSESSING THE MOTIVATIONAL GOAL ORIENTATIONS OF INTERNATIONAL ENGLISH FOR ACADEMIC PURPOSES (EAP) STUDENTS

Lindy Woodrow
The University of Sydney

Elaine Chapman
The University of Sydney

ABSTRACT

There is some question about the applicability of Western paradigms of learning across different cultures. This study compared the motivational goal orientations of international students of English for academic purposes (EAP) studying in Australia. Participants (N = 275) completed the task, performance approach, and performance avoid goal subscales of the Patterns of Adaptive Learning Survey (Midgley et al. 1997). Results confirmed the validity and reliability of the subscales within this sample. However, multivariate analysis of variance (MANOVA) indicated that learners from Confucian heritage cultures (Chinese speaking countries, Korea and Japan) had different motivational profiles from their European and South American counterparts. Implications for the use of these scales with Confucian heritage students are discussed.

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INTRODUCTION

There is a tendency in language learning research not to take full advantage of research conducted in other disciplines. This is possibly due to the uniqueness of the processes involved in language learning, particularly in a second language rather than a foreign language environment. In this situation, language is more than just another academic subject: Learners rely on their second language expertise to communicate their needs and to express their personality. Whilst language learning research has undergone a revolution in recent years with the application of motivational constructs from different theoretical viewpoints (Dörnyei, 2001; MacIntyre, MacMaster and Baker 2001; Noels 2001), to date there has been little published research on scales that assess achievement goal orientations in language learning.

Research has indicated differences in the learning behaviors of different cultural groups, with contrasts between collectivist cultures (e.g., China, Japan, Korea) and individualistic cultures (e.g., North America, Europe, Australia) providing the most striking differences. There are similarities in the cultural heritage of China and Chinese speaking countries, Japan and Korea, these countries are often referred to as Confucian heritage cultures (CHC). It is important to note that this refers to historical underpinnings and general societal practices rather than a strict adherence to Confucianist principles by individuals. There are similarities in the educational environments of these countries, classes tend to be very large, the teacher is viewed as an authoritarian figure and teaching is often focused on examinations (Biggs 1996).

International students represent a substantial proportion of university students in Australia The majority of these students come from neighboring Asian countries and Chinese speaking countries. It is important that educators are aware of cultural variations that may influence learning behaviors. This study aimed to address this issue and to explore differences in the goal orientations of students from Western and Confucian heritage cultures (CHCs). The study focused specifically on the goal orientations of English for Academic Purposes (EAP) learners in Australia.

Situated in a social cognitive perspective, motivational goal theory focuses on aims and purposes in learning, and concerns how learners think about themselves, about tasks and about performance. Purpose is viewed as the energizing force behind task engagement. The types of goal orientations vary in terminology but basically refer to three orientations; task (learning, mastery), performance approach (ego, ability) (Ames and Archer 1988) and more recently, performance avoid (Elliot and Sheldon 1997).

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A task goal orientation is characterized by a desire to develop ability with an emphasis on learning for its own sake; value is placed on effort, challenging tasks are attempted, and errors are viewed as part of the learning process (Anderman and Maehr 1994). A task goal orientation is viewed as a construct of adaptive learning and is typically correlated with high performance (e.g., Middleton and Midgely 1997).

Performance goals are characterized by a focus on one’s self with an emphasis on performance relative to others and errors are viewed as failure. Generally, this construct is classed as less adaptive than a task goal orientation. A performance avoid goal orientation relates to the need to avoid appearing incompetent or performing worse than classmates (Elliot and Sheldon, 1997; Middleton and Midgely, 1997; Skaalvik, 1997). This goal orientation is generally classed as maladaptive. Both task and performance are considered approach orientations, supported by a need for achievement, whereas an avoid orientation is supported by fear of failure (Elliot and McGregor 1999).

In most of the studies reported in the literature, performance approach and avoid goal orientations are related to each other. A task goal orientation is occasionally reported as having a low correlation with performance approach, but is either not related or negatively related to performance avoid (Elliot and Church 1997; Elliot, McGregor, and Gable 1999; Middleton and Midgely 1997).

As goal theory is concerned with how learners think about themselves, tasks, and performance, it seems logical that cultural differences would occur in the adoption and relevance of goal orientations. Studies have found that CHC learners make different learning attributions than their Western counterparts (Biggs 1996). CHCs tend to attribute success and failure to effort, while Western learners tend to attribute success to ability and failure to lack of effort. Dweck and Leggert (2000) refer to the adoption of personal goals as being dependent upon beliefs about intelligence, with those who view intelligence as fixed being more likely to adopt a performance goal, and those who view intelligence as not fixed (i.e., affected by effort) more likely to adopt a mastery (task) goal. Therefore, it would seem logical that CHC learners should display more predominant task than performance goal orientations.

There is limited research in the application of goal theory across cultures. Shi and colleagues found that the Patterns of Adaptive Learning Survey (PALS) (Midgley et al. 1997), as a whole, was an appropriate measurement tool for Chinese students and the Chinese school system (Shi et al. 2001). On the other hand, Shalili, Chiu and Lai (2001) found a significant effect of group on goal orientation with Hong Kong students displaying both task and performance goals (r = .26, p <.0001). McInerney (1995) also found a positive relationship between competition and striving for excellence in Navajo students, whom he classed as belonging to a collectivist culture. Both of these studies focused on the differences between task and performance goal orientations. The difference between performance avoid and approach orientations was not considered.

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RESEARCH QUESTIONS

The purpose of this study is to assess the applicability of personal goal orientations to language learners from various cultural backgrounds. There were two primary research questions:

  1. Is the PALS an appropriate instrument to use with language learners?
  2. Do learners from different ethnic groups differ in their motivational goal orientations?

METHOD

Participants
Participants were 275 (136 female, 139 male) EAP learners studying at accredited language centers in Australia. They studied on intensive advanced EAP courses for on average 20 hours per week and almost all of the participants planned to study at Australian universities subsequent to completing their current English course. Participants had between 3 to 10 weeks of English instruction remaining. Most of the participants were in their early 20s and over half the participants planned to study at postgraduate level. They had been in Australia between 1 – 42 months (Mean = 5.4 months, SD = 5.4) and had spent between 1 – 12 months studying at their language center (M=-3.78, SD = 2.47). Participants originated from different countries, Table 1 indicates the number of participants within each ethnic group.

Table 1. Ethnic Backgrounds of Participants

Nationality n
Chinese 69
Taiwan 15
Hong Kong 7
Korean 37
Thai 33
European 27
Indonesian 25
Japanese 20
Vietnamese 18
S.American 14
Others 8
Missing 2
Total 275

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As one of the study goals was to compare orientations across cultures, participants from ethnic groups with less than 5 members were excluded in the statistical analysis, 8 participants in the category ‘others’ in table 1 were excluded from the analysis. There were two missing cases where participants had not entered their nationality, thus leaving a final sample of 265.

Australian universities require that international students achieve a specific score on the International English Language Testing Service (IELTS) prior to entry. Bandings for this test range from 1 (for non-user) to 9 (for an expert user). Almost all of participants were interviewed using an adaptation of the International English Language Testing Service (IELTS) oral test conducted by a qualified IELTS examiner, shortly after completing the goal orientations questionnaire. Scores ranged from Band 3 (Extremely limited user of English) to Band 8 (Very good user of English).

Instrumentation
Three subscales (5 items per subscale) measuring personal achievement goal orientations from the Patterns of Adaptive Learning Survey (PALS) developed by Midgley and colleagues (1997) were adapted for adult non-native speakers of English. The three subscales are designed to assess students’ task goal orientation (e.g., " I do my English work because I am interested in it"), performance approach goal orientation ("doing better than other students in this class is important to me"), and performance avoid goal orientation ("the reason I do my English work is so others won’t think I’m poor at English"). Two items were removed from the original subscales because a pilot study had indicated these items were inappropriate to the participants (Woodrow 2001). These subscales represented one section of an overall survey used to assess adaptive language learning.

Descriptive statistics and alpha reliabilities of each subscale, along with corresponding estimates reported in the PALS manual (Midgely et al. 1997), are presented in Table 2. As indicated, the means and standard deviations of these subscales were remarkably similar to those obtained from the original validation sample. The subscales also showed acceptable internal consistency within this sample.

Table 2. Means, Standard Deviations and Alpha Reliabilities for Motivational Goals Sub-Scales

Goal Present Study PALS
  M SD alpha M SD alpha
Task goal 3.86 .66 .68 3.98 .89 .78
Approach goal 2.65 1.01 .86 2.68 1.08 .86
Avoid goal 2.61 .86 .77 2.41 .91 .75
IELTS 6.01 .96        

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Factor Structure of the PALS in EAP Learner Sample
To assess the robustness of the three-factor model of goal orientations in this particular sample, a confirmatory factor analysis (CFA) using Lisrel 8.5 (Jöreskog and Sörbom 1996) was conducted. All screening procedures used to assess conformity to underlying assumptions produced satisfactory results, although Mahalanobis distances indicated six multivariate outliers (p < 0.001) in the initial data set. These cases were removed in the final CFA model.

Evidence to support the applicability of a trichotomous conceptualization of goal orientations was obtained from CFA. A three-factor confirmatory model corresponding to task, performance- approach, and performance-avoid goals indicated a moderate to good fit to the data. The fit indices are reported in Table 3. Factor loadings were between .48 - .85 with four factors below .60, supporting the validity of the factor structure in this sample. Factor loadings and error covariances are provided in Table 4. These indices were also very similar to those reported by Midgley and colleagues (1998). These results indicate that the PALS subscales measuring personal goal orientations are relevant to the present sample of international language learners.

Table 3. Fit Indices for Confirmatory Factor Analyses

  Chi-square p Chi-square/df RMR RMSEA GFI AGFI CFI NFI NNFI
Motivation Goals 193.96 .00 2.22 .06 .07 .91 .87 .90 .84 .88

 

Table 4. Factor Loadings and Error Covariances of Confirmatory Factor Analysis for Goal Orientations

Subscale Item Factor Loading Error Variance
Task Goal Learn from mistakes .60 .64
Interested in work .66 .56
Get better .48 .77
Really think .49 .76
Learn new things .58 .66
Performance Approach Doing better important .68 .53
Others think good .71 .50
Do better .75 .44
Show teacher .84 .29
Only one answer .72 .48
Performance Avoid Others not think poor .63 .60
Avoid looking unable .72 .48
Not look stupid .50 .75
Not embarrass myself .63 .60
Look can’t speak English .67 .55

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The correlations between the latent constructs did, however, reveal a somewhat unusual pattern of results. Most previous studies (e.g., Midgely et al. 1998) have indicated an orthogonal or a negative relationship between task goals and performance avoidance. In this sample, as can be seen in Table 5, there was a positive correlation between task goal orientation and both performance goal orientations. This suggests that the sample used in this study tended to adopt all of the motivational goals rather than one in particular. A task goal is the only goal orientation to be positively related to achievement (IELTS test performance) indicating support for the notion that the task goal orientation is the most desirable.

Table 5. Correlations between Motivational Goals and Oral Performance

Variable 1 2 3 4
1. Task 1.00      
2. Approach .15* 1.00    
3. Avoid .25** .48** 1.00  
4. IELTS .24** -.00 -.21** 1.00

* Correlation is significant at the 0.05 level; ** Correlation is significant at the 0.01 level

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Differences in Goal Orientations Across Ethnic Groups
To determine whether goal orientations differed across ethnic groups, a multivariate analysis of variance (MANOVA) was performed on scores for the performance avoidance, performance approach, and task subscales. Further, to assess whether any effects for ethnic group differed across males and females, sex was entered as a second independent variable in the MANOVA, creating a 10 by 2 factorial design. Univariate ANOVAs were used to assess the effects of these two factors on individual dependent measures, followed by stepdown analyses. All univariate and stepdown Fs were tested for significance at Bonferroni-adjusted a levels to maintain nominal familywise a at or below 0.05 for each set . Significant univariate outcomes are accompanied by effect size estimates based on the partial eta squared statistic (h 2).

Descriptive statistics for these results are shown in Table 6. The 10 (ethnicity) by 2 (sex) MANOVA indicated no significant sex by ethnic group interaction effect (V = .11, F(3, 27) = 1.06, p =.38). There were, however, significant main effects both for sex (V = 0.07, F(3,241) = 5.87, p < 0.001) and for ethnic group (V = 0.35, F(27,729) = 3.59, p < 0.0001). As there were significant correlations between scores on the three subscales (task and approach r = .25, p = 01, task and avoid, r = .14, p = .05, approach and avoid, r = .48, p = .01), both univariate ANOVAs and stepdown analyses were used to determine which of the subscales contributed significantly to this multivariate effect.

Table 6. Descriptive Statistics for Ethnicity and Goal Orientation

  Ethnicity M SD N
Performance Approach Chinese 3.05 .90 69
Taiwan 2.84 .87 15
Hong Kong 3.16 .98 7
Korean 2.97 .99 37
Indonesian 2.62 1.14 25
Japanese 2.43 1.05 19
Thai 2.38 .86 32
Vietnamese 2.16 1.11 18
European 2.19 .92 27
South American 1.89 .81 14
Performance Avoid Thai 3.09 .76 32
Indonesian 2.77 .87 25
Korean 2.77 .80 37
Chinese 2.64 .77 69
Taiwan 2.88 .73 15
Hong Kong 2.77 .72 7
Japanese 2.37 .83 19
South American 2.30 1.00 14
Vietnamese 2.29 .85 18
European 1.97 .85 27

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The univariate ANOVAs indicated significant main effects of ethnic group on performance avoidance (F(9,243) = 4.76, p < 0.0001, partial eta squared = 0.15) and on performance approach (F(9,243) = 4.27, p < 0.0001, partial eta squared = 0.14). The latter effect remained significant at stepdown (F(9,242) = 4.02, p < 0.0001), indicating that the effect on this subscale was independent of that found on the avoidance scale. The univariate effect on task goals was not significant, however (F(9,243) < 1), indicating that the ethnic groups differed primarily on the two performance goal orientations. Figures 1 and 2 display the estimated means for the two dependent variables and ethnicity.

Figure 1. Graph of Performance Approach Goal Orientation According to Ethnicity

 

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Figure 2. Graph of Performance Avoid Goal Orientation According to Ethnicity

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The pattern of means shown in Figures 1 and 2 indicate that participants from Chinese cultures (China, Hong Kong and Taiwan) scored higher on performance approach than South American, European, and surprisingly, Vietnamese participants. Other Asian participants’ scores were in between. The results for performance avoid goals indicate that participants from Chinese cultures, together with Thai and Indonesian participants, scored highest overall on the performance avoid subscale; participants from Europe scored the lowest; and the scores of Vietnamese South American and Japanese participants were in between.

Using a significance level of 0.05, Tukey’s HSD post-hoc tests indicated minimal differences amongst Confucian heritage learners, and minimal differences between South American and European learners. For performance avoidance, however, there were significant differences between European participants and learners from Chinese, Korean, Indonesian, Thai, and Taiwanese backgrounds. For performance approach, there were significant differences between European and Chinese, and European and Korean students. Significant differences were also found between South American and Chinese and South American and Korean learners. These analyses indicate that in general, learners from Confucian heritage cultures tend to differ in their motivational goal orientations from European and South American EAP learners.

Descriptive statistics for gender and performance avoid and task goals are displayed in Table 7.

Table 7. Descriptive Statistics for Motivational Goals and Gender

Goal Gender M SD N
Task male 3.71 .64 133
female 4.01 .64 132
Performance Avoid male 2.50 .82 133
female 2.72 .88 132

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DISCUSSION

The results of the confirmatory factor analysis provided support for the applicability of the PALS with EAP language learners from different cultural backgrounds. The significant effect found for task goal orientation on oral performance in English also provides supportive evidence for the relevance and utility of personal goal orientations in the specific domain of language learning within a second language environment.

The results of this study replicated those found in the pilot study using a similar sample (The overall correlation between performance avoid and task goal orientation was r= .206, p = 01, N=249,the significant effects for the MANOVA were F(39,684) = 3.24) and for subsequent ANOVAs: performance avoid: F(13,228) = 3.828, and performance approach: F(13,228) = 2.85). (Woodrow 2001).

These results provide preliminary evidence of differences in motivational patterns for different ethnic groups. Participants from Europe and South America showed similar motivational profiles to those reported in other research with Western participants. Participants from Chinese cultures (China, Hong Kong and Taiwan), however, scored higher on performance approach than South American, European and surprisingly Vietnamese participants. Other Asian participants’ scores were in between. The results for performance avoid goals indicate that participants from Chinese cultures, together with Thai and Indonesian participants, scored higher on the performance avoid subscale than participants from Europe, with Vietnamese, South American and Japanese participants scoring in between these groups.

It is conceivable that other factors could be responsible for these patterns, notably learning context. This would be evident in differences in responses between language centers. In addition length of time spent in Australia and length of time studying English in Australia could possible influence these profiles. Analysis of the data did not indicate significant effects for center, length of time in Australia, nor length of time spent studying English at the language center.

Generally, participants from Confucian heritage cultures: Chinese speaking countries, Korea and Japan, displayed similar profiles with higher performance approach and performance avoid means than European and South American counterparts. Confucian heritage cultures greatly value education, and in collectivist cultures the family is extremely important (Salili 1996). Many of these participants are supported financially by their families. In follow-up interviews, some reported following career paths chosen for them by their families. This is highlighted by the background data regarding subject choice with 82% of Chinese participants opting for Information Technology/engineering or commerce subjects. Seventy-eight percent of Chinese students studied at a graduate level. Thus, it is conceivable that family pressure and the external pressure of achieving specified scores on the IELTS test, could result in greater pressure to succeed. This could manifest itself through the adoption of both performance avoid goals and task goals.

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Generally Asian and European results followed the expected trends with the exception of Vietnamese participants. Their scores were similar to those of the Europeans and South Americans. One possible explanation for this could be the high occurrence of Australian aid scholarship students and the low occurrence of privately funded individuals amongst the Vietnamese sample. Scholarship students are selected in their home country on the basis of merit and competition is fierce. These students already have an adequate IELTS score and a confirmed place at university. It could be expected that this would reduce negative affect due to the absence of pressure to succeed and fulfil family expectations.

There are many examples of differences between East and West in terms of educational issues (see Watkins and Biggs 1996, 2001) and these results provide preliminary evidence for differences in achievement goal orientations for a important group of adult learners in Australia. However, further research is needed to investigate in the similarities between the beliefs of learners from CHCs and the relationship of these variables to variables of motivation.

In general, the results of this study confirmed both the validity and the utility of the PALS for assessing the motivational goal orientations of language learners. Language educators would benefit from further research into the goal orientations of learners from diverse cultural backgrounds.

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APPENDIX

Correlation Matrix for Confirmatory Factor Analysis of Motivation Goal Orientation

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Task 1 1.00                            
Avoid 1 .313 1.00                          
Appr 1 .071 .258 1.00                        
Task 2 .449 .113 .087 1.00                      
Avoid 2 .047 .507 .323 .079 1.00                    
Task 3 .218 .194 .147 .274 .207 1.00                  
Task 4 .302 .138 .017 .421 .017 .364 1.00                
Avoid 3 .027 .311 .103 -.076 .391 .143 .005 1.00              
Appr 2 .013 .251 .502 .093 .383 .108 .141 .302 1.00            
Task 5 .325 .173 .083 .292 .149 .267 .222 .134 .075 1.00          
Appr 3 .135 .211 .610 .059 .344 .165 .101 .136 .509 .262 1.00        
Avoid 4 .115 .377 .269 .061 .418 .187 .149 .337 .309 .274 .314 1.00      
Avoid 5 .128 .386 .268 .074 .476 .150 .107 .341 .405 .176 .309 .450 1.00    
Appr 4 .038 .286 .550 .040 .306 .116 .105 .165 .621 .076 .586 .312 .358 1.00  
Appr 5 .015 .261 .413 -.069 .245 .092 .009 .184 .429 .080 .565 .307 .302 .671 1.00

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Variable Names With Item Decriptions

Variable Name Item
1. Task 1 I like English language learning tasks that I’ll learn from even if I make a lot of mistakes.
2. Avoid 1 The reason I do my English work is so others won’t think I’m poor at English.
3. Approach 1 Doing better than other students in this class is important to me.
4. Task 2 I do my English work because I am interested in it.
5. Avoid 2 One of my main goals is to avoid looking like I can’t do my English language learning tasks.
6. Task 3 I like English learning tasks best when I really have to think.
7. Task 4 An important reason why I study English is because I like to learn new things.
8. Avoid 3 One reason I would not participate in my English class activities is to avoid looking stupid.
9. Approach 2 It’s important to me that other students in my English class think I’m good at English.
10. Task 5 An important reason why I do my English work is because I want to get better at it.
11. Approach 3 I would feel successful if I did better than most of the other students in my English class.
12. Avoid 4 An important reason why I do my English work is so I don’t embarrass myself.
13. Avoid 5 It’s very important to me that I don’t look as though I can’t speak English in my class.
14. Approach 4 I’d like to show my English teacher that I’m better at English than other students in my class.
15. Approach 5 I would feel really good if I were the only one who could answer the teacher’s questions in my class.

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AUTHORS’ BIOGRAPHIES

Lindy Woodrow (Dip. Teach., M.A.) is a Ph.D. student in the School of Development and Learning at the University of Sydney. She is currently conducting research on adaptive learning of English for academic purposes students. She has more than 20 years experience teaching ESL to adults in Australia, Asia and Europe. E-mail: l.woodrow@edfac.usyd.edu.au.

Elaine Chapman (B.A.Hons., Ph.D.) is a lecturer in the School of Development and Learning at the University of Sydney, where she teaches and researches in the areas of research methodology, assessment, and educational psychology. E-mail: e.chapman@edfac.usyd.edu.au.

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