Learning and Individual Differences 27 (2013) 97–101

Contents lists available at SciVerse ScienceDirect

Learning and Individual Differences

j ourna l homepage: www.e lsev ie r .com/ locate / l ind i f

Are two achievement goals better than one? Filipino students'achievement goals, deep learning strategies and affect☆

Elmer D. Dela Rosa a, Allan B.I. Bernardo b,⁎a College of Education, Central Luzon State University, Science City of Muñoz, Nueva Ecija, Philippinesb University of Macau, Macau

☆ This researchwas supported by a Faculty Developmenawarded to the first author by the Commission on Higher⁎ Corresponding author at: PGL334 Pearl Jubilee Build

University of Macau, Avenida Padre Tomas Pereira, Taipafax: +853 28838312.

E-mail addresses: edelarosa.clsu@yahoo.com (E.D. Delallanbibernardo@umac.mo, allanbibernardo@yahoo.com (

1041-6080/$ – see front matter © 2013 Elsevier Inc. All rihttp://dx.doi.org/10.1016/j.lindif.2013.07.005

a b s t r a c t

a r t i c l e i n f o

Article history:Received 1 August 2012Received in revised form 22 June 2013Accepted 12 July 2013Available online xxxx

Keywords:Achievement goalsLearning strategiesEmotionsMultiple-goals perspectiveMotivation

Themultiple-goals perspective assumes that adopting bothmastery and performance goals is better for students.But there has been very little evidence for themultiple-goals perspective in Asian students. A cluster analysiswasconducted to identify groups of Filipino students who endorse different goal combinations, revealing four groupscomprised of those who adopted (a) predominantly performance goals, (b) predominantly mastery goals,(c) multiple goals or (d) low levels of both goals. Comparisons of cognitive and affective learning variables indi-cated that reported use of deep learning strategies, enjoyment of learning and less anxiety were associated withthe multiple goals group. Although the study did not assess actual learning outcomes, the study shows resultsconsistent with the multiple-goals perspective, as it shows enhanced use of cognitive strategies and more posi-tive affective experiences in the learning processes, adding to the scant evidence on multiple-goals perspectiveamong Asian students.

© 2013 Elsevier Inc. All rights reserved.

1. Achievement goals and learning

The type of achievement goals pursued by students is a significantpredictor of student learning. Research has focused attention on therelative importance of mastery goals (striving to improve one's com-petence) and performance goals (striving to outperform others)(Ames, 1992). However, scholars still debate whether one particulargoal or a combination of goals is the most adaptive for student learning(Daniels et al., 2008; Linnenbrink, 2005). Some theorists (Kaplan &Middleton, 2002) advocate the mastery-goal perspective, which as-sumes thatmastery goals are adaptive in academic contexts and that per-formance goals are less so. Other theorists (e.g., Harackiewicz, Barron,Pintrich, Elliot, & Trash, 2002) support the multiple-goals perspective,which asserts that performance-approach goals are beneficial, especiallywhen mastery goals are also endorsed; this perspective assumes thatmultiple goals lead to the best learning outcomes (Pintrich, 2000).

The influence of achievement goals can be seen in various facets ofthe learning process. For example, achievement goals are related to stu-dents' cognitive strategies and research has consistently shown thatmastery goals are positively related to deep learning strategies (Ames,1992). The effect is attributed to how the self-improvement motivationin the mastery goal orientation makes students think of and use more

t Grant and a Dissertation GrantEducation, Philippines.ing, Department of Psychology,, Macau. Tel.: +853 83978394;

a Rosa),A.B.I. Bernardo).

ghts reserved.

complex strategies to complete learning tasks. The relationship be-tween achievement goals and the affective dimensions of learning arenot as consistent. Achievement goals are presumed to facilitate differ-ent kinds of motivation-relevant processes, which in turn contributeto the activation of different kinds of emotions. Research indicates apositive relationship between mastery goals and students' positiveaffect (Pekrun, Elliot, & Maier, 2006) — a pattern predicted by boththe mastery- and multiple-goals perspectives (Harackiewicz &Linnenbrink, 2005; Linnenbrink, 2005). But the mastery-goal perspec-tive suggests that performance-approach goals are associated withhigher negative affect and test anxiety; the multiple-goals perspec-tive makes no such assumption (Harackiewicz & Linnenbrink, 2005;Linnenbrink, 2005).

1.1. Cultural aspects

The cultural dimension of achievement goals has been suggested asan important aspect of achievement goal research (Dekker & Fischer,2008). For example, research shows that endorsement of mastery andperformance goals generally tend to be positive correlated, but thesecorrelations tend to be higher in Asian samples compared to NorthAmerican samples (Hulleman, Schrager, Bodmann, & Harackiewicz,2010). Hau and Ho (2008) also noted how Asian research on achieve-ment goals seems to implicate the social dimensions of these goalsand how the meanings of these goals among Asian students might beshaped by collectivistic orientations and interdependent self-construals.In this regard, various studies also showdifferent sets of cultural variables(e.g., values, orientations) related to the two achievement goals in differ-ent Asian students (e.g., Liem & Nie, 2008; Luo, Hogan, & Paris, 2011).

98 E.D. Dela Rosa, A.B.I. Bernardo / Learning and Individual Differences 27 (2013) 97–101

Although the basic differences regarding the correlates of masteryand performance goals are found with Asian students, there are incon-sistencies particularly as they relate to the correlates of performancegoals. For example, consistentwithmost previous research, stronger in-terest, engagement, and reported use of deep learning strategies wereassociated with mastery goals but not with performance goals in somestudies (e.g., Chan & Lai, 2007; Chan, Wong, & Lo, 2012; Ho & Hau,2008). But other studies also show a positive relationship between re-ported use of deep learning strategies and performance goals (Lau,Liem, & Nie, 2008; Liem, Lau, & Nie, 2008; Shih, 2005). Again consistentwith the previous research, Asian students also report greater levels ofanxiety with performance goals, but not mastery goals (e.g., Chan &Lai, 2007; Chang & Wong, 2008); but there are other studies thatshow, that performance goals are negatively associated with anxiety(Luo, Paris, Hogan, & Luo, 2011; Shih, 2005). Some have tried to explainthe inconsistency in terms of cultural meanings associated with eachgoal in different Asian educational contexts (Chang & Wong, 2008;Hau & Ho, 2008), and with performance goal, in particular. But someof the findings could be explained by contrasting whether the per-formance goals are defined in terms of the approach or avoidancedimensions. In which case the positive outcomes associated withperformance-approach goals can be understood in terms of themultiple-goals perspective; that is, the positive outcomes associatedwith performance-approach goals may be observed when the stu-dents are also adopting mastery goals.

However, most of the previous studies adopt a mastery-goals per-spective, and the multiple-goals perspective has only been recentlystudied with Asian students. Studying Singaporean students and alsousing cluster analysis, Luo et al. (2011) found that some studentsadopt multiple goals, and the adoption of multiple approach goals wasassociated with better learning and achievement. They argued thatSingaporean students adoptmultiple goals for reasons that are differentcompared to North American students. They refer to a confluence ofvarious sociocultural values in Singapore's multicultural society andcharacteristics of the Singaporean educational system. As such theywere careful to state that their findings may generate only to otherEast Asian countries similar to Singapore.

In this study, we sought to provide additional evidence for themultiple-goals perspective using a sample of Southeast Asian students.We studied students from the Philippines, a country which is notamong the Confucian heritage countries with predominantly Chineseethnic populations. The Philippines, belongs to the Southeast Asian re-gion, where most countries (e.g., Indonesia, Malaysia) have a predomi-nantly Malay ethnic population. Moreover, unlike East Asian countriesthat have very rigid educational testing systems (which accordingto Luo et al., 2011, is associated with the adoption of multiple goalsin East Asian countries), the Philippines and other Southeast Asiancountries have less structured and rigid testing systems. We believe,that providing data from another type of non-Western, Asian samplewould serve to further support the multiple-goals perspective.

1.2. The present study

This study uses cluster analysis with a sample of Filipino college stu-dents learning algebra; cluster analysis was used to identify studentswho endorse either mastery goals only, performance goals only, com-bined goals, or low levels of the two goals. Daniels et al. (2008) observedthat the divergent results regarding the mastery- and multiple-goalsperspectives might be accounted for by differences in the methodolo-gies like the use ofmedian split (Wentzel, 1993) and regression analysis(Elliot & Church, 1997). Daniels et al. (2008) suggest the use of clusteranalysis (Luo et al., 2011; Meece & Holt, 1993; Riveiro, Cabanach, &Arias, 2001; Valle et al., 2003) because the approach allows for an in-ductive empirical means of determining whether there are studentswho adopt the two goals together and who adopt single goals. Unlikethe othermethods, cluster analysis could identify subgroups of students

who are similar within-group and different between-groups. We limitthe cluster analysis to the mastery-approach and performance-approach goals; we do not consider the mastery-avoidance andperformance-avoidance goals, as these are consistently shown to bemaladaptive in learning. For outcomes, we focus on reported use ofdeep cognitive strategies in learning, and on reported affect of enjoy-ment and anxiety.

We hypothesize that consistentwith themultiple-goals perspective,performance goals would also be associated with positive outcomes, ei-ther when adopted singly or in combinationwithmastery goals. But thepositive outcomes of performance goals would be specific to the moti-vational aspects of learning, not in the cognitive processes (Danielset al., 2008; Linnenbrink, 2005). Earlier we noted the inconsistent re-sults regardingwhether performance goals are associatedwith reporteduse of deep learning strategies. This inconsistency in the literature isreflected in two studies involving Filipino students, similar to the cur-rent study, where one study (Bernardo, 2004) found a relationshipbetween performance goals and reported use of deep learning strate-gies (i.e., critical thinking and metacognitive strategies), while anotherstudy (Bernardo, 2003) did not show the same pattern. Given the incon-sistency of the evidence on this point, for the present study, perfor-mance goal is not predicted to be associated with the use of deeplearning strategies. There are also inconsistencies in the literature re-garding whether performance goals is associated with affective out-comes, but we argue that these differences are probably related towhether the approach or avoidance dimensions are emphasized (Luoet al., 2011). Thus, performance (approach) goal is predicted to be asso-ciated with affective variables (more enjoyment and less anxiety)that are activated by motivational processes in learning. On the otherhand, mastery goals should promote both positive affect and reporteduse of deep cognitive strategies (Linnenbrink, 2005; Pintrich, 2000).As regards the endorsement of multiple goals, there should be an addi-tive effect of endorsing both goals on positive affect (i.e., higher enjoy-ment, less anxiety), but not on reported use of deep cognitive strategies.

To summarize, we tested two hypotheses. First, endorsement ofmultiple goals would be associated with reported use of deep cognitivestrategies compared to endorsement of performance goals alone or lowendorsement of both goals, but not when compared to endorsement ofmastery goals only. Second, endorsement ofmultiple goals would be as-sociated with more enjoyment (and less anxiety) compared to the en-dorsement of either goal singly, which in turn should be associatedwithmore enjoyment (and less anxiety) compared to low endorsementof both goals.

2. Methods

2.1. Participants

Participants were 900 (605 females, 295 males, Mage = 16.48,SD = 1.36) freshman students from twouniversities enrolled in variousalgebra classes. There were no differences found between the masterygoals [t(898) = − .35, n.s.] and performance goals [t(898) = .60, n.s.]of students from the two universities, so the data were combined forall the analyses. All participants provided their informed consent to par-ticipate in the study.

2.2. Instruments

The participants were enrolled in universities where Englishwas themedium of instruction. In line with this, all the research instrumentswere administered in English.

2.2.1. Achievement goalsSix items measuring mastery goals (for current sample, α = .79;

sample item: “The most important thing for me in this course is tryingto understand the content as thoroughly as possible”) and sixmeasuring

99E.D. Dela Rosa, A.B.I. Bernardo / Learning and Individual Differences 27 (2013) 97–101

performance goals (α = .87, “My goal in this class is to get a bettergrade thanmost of the other students”) were derived from the achieve-ment goals scales of Harackiewicz, Barron, Carter, Lehto, and Elliot(1997). Participants responded using a scale from 1 (not at all true ofme) to 5 (very true of me). The within-construct validity of the scalewas assessed by conducting a confirmatory factor analysis of the two-factor model (with six items under each factor). The results of sev-eral indexes indicate an adequate fit between the data and the two-factor model (χ2(53) = 380.85; RMSEA = .07; AGFI = .90; CFI =.92; NNFI = .91).

2.2.2. Deep learning strategyThe deep strategy subscale of Biggs' Revised Two-factor Study

Process Questionnaire (Biggs, Kember, & Leung, 2001)was used tomea-sure use of deep strategy (5 items, α = .81; “I find that I have to doenough work on a topic so that I can form my own conclusions beforeI am satisfied”). The questionnaire also assessed the use of surface learn-ing strategy, but because it was not pertinent to testing the predictionsof multiple-goals perspective, the surface learning scores were not in-cluded in the analysis. Respondents indicated their response using ascale from 1 (not at all true of me) to 5 (very true of me). The within-structure validity of the questionnaire was also assessed using confir-matory factor analysis, and the results also indicated an adequate fit be-tween the one-factor model and the data (χ2(5) = 56.62; RMSEA =.08; AGFI = .92; CFI = .96; NNFI = .93).

2.2.3. Affective outcomesThe enjoyment of learning scale (10 items, α = .89; “I look forward

to mymath class”) and anxiety scale (15 items,α = .90; “When I thinkabout my math class, I get nervous”) of the Achievement EmotionsQuestionnaire-Math (Pekrun, Goetz, & Frenzel, 2005) were used to as-sess the student's emotions when studying for their math class. Partici-pants responded using a scale from 1 (strongly disagree) to 5 (stronglyagree). Confirmatory factor analysis of the two scales also indicated ad-equate fit between the two-factor model and the data [χ2(126) =346.91; RMSEA = .04; AGFI = .93; CFI = .98; NNFI = .95].

3. Results

Table 1 shows the descriptive statistics for the scores for the keyvariables. Although the study did not focus on gender as a variable, weshould note that there we no gender differences found in the masterygoals, performance goals, and deep learning strategies. We wereexpecting gender differences in the academic emotions as previous re-search (Frenzel, Pekrun, & Goetz, 2007) suggests that women experi-ence higher levels of anxiety and less enjoyment in mathematics.However, we did not observe significant differences in anxiety, andonly found significant gender differences in enjoyment [F(3,895) =34.96, p b .001, η2 = .11], where the men reported more enjoyment.

Table 1Basic statistics for key variables.

Variables M SD Correlations (r)

(a) (b) (c) (d)

(a) Mastery goals 3.64 .71 –

(b) Performance goals 4.17 .59 .47⁎⁎ –

(c) Deep learning strategies 3.24 .72 .19⁎⁎ .26⁎⁎ –

(d) Enjoyment of learning 3.48 .73 .22⁎⁎ .30⁎⁎ .61⁎⁎ –

(e) Anxiety 2.71 .78 − .09⁎ − .13⁎⁎ − .14⁎⁎ − .38⁎⁎

⁎ p b .05.⁎⁎ p b .001.

3.1. Cluster analysis

For the cluster analysis, the mastery and performance goal scoreswere first standardized using Z-transformation (Huberty, Jordan, &Brandt, 2005). A four-cluster solution was chosen as it provided amore complete assessment of likely goal combination (Daniels et al.,2008; Dela Rosa & Bernardo, 2013). Descriptive statistics for eachachievement goal cluster are shown in Table 2.

The first cluster (n = 273) is composed of students who endorsemainly performance goals,whereas the second cluster 2 (n = 191) sug-gested a group of students who endorsemainlymastery goals. The thirdcluster (n = 301) is composed of students who reported high masteryand high performance goals, and was labeled the multiple goals group.The fourth cluster (n = 135) comprised of students who reported lowmastery and low performance goals, and was labeled the low motiva-tion group.

Two ANOVAs showed that there were significant difference amongthe four clusters in terms of mastery goals, F(3,896) = 665.8, p b .001,η2 = .69, and in terms of performance goals, F(3,896) = 623.22,p b .001, η2 = .68. Post-hoc comparisons of mean using the Bonferroniadjusted level of significance show that the multiple-goal cluster hasmastery goal scores higher than the mastery goal cluster, which hashigher mastery goal scores than the performance and low achievementgoal clusters. Similarly, the multiple goals cluster has performance goalscores higher than the performance goal cluster, which has higherscores than the mastery and low achievement clusters. The pattern ofresult is consistent with the cluster labels.

There is a possibility that the students in multiple goals and lowachievement goals clusters are not actually distinguishing betweenmastery and performance goals. To explore this possibility, we con-ducted confirmatory factor analysis for the achievement goals scale forthe two groups (even if the sample size for the low achievement goalcluster was rather small) to show within-construct validity of thetwo-factor model for each group. The results of the analysis weremixed. For both groups, the absolute fit indexes indicated adequatefit (cluster 3: χ2(53) = 80.78; RMSEA = .02, AGFI = .93; cluster 4:χ2(53) = 110.34; RMSEA = .06, AGFI = .82), but the incremental fitindexes did not (cluster 3: CFI = .80; NNFI = .75; cluster 4: CFI =.79; NNFI = .79). Note that a few guidelines have suggested a lowerlimit of .80 for CFI and NNFI (e.g., Byrne, 1994; Garson, 2004), whichwould suggest that the incremental fit indexes are not extremely inad-equate. Taking into consideration the various indexes, we believe thatthere is some indication that there is a distinction between the twogoal orientation among the participants in the multiple goals and lowachievement goals clusters.

3.2. Cluster differences

A series of ANOVAs was conducted to compare the different goalgroups in terms of the outcome measures. For all significant main ef-fects, the Bonferroni adjusted significance level {α = .05 ÷ 6 (numberof pairwise comparisons)} = .008 was used in the post-hoc analysis.Means and standard deviations of the outcomemeasures for the differ-ent clusters are shown in Table 3.

3.2.1. Deep learning strategyThere was a significant main effect of goals across the clusters in

terms of deep learning, F(3,896) = 23.21, p b .001, η2 = .072, with asmall effect size (Cohen, 1988). The multiple goals group reportedmore use of deep learning strategies than the students from themasterygroup, performance group, and low motivation group.

3.2.2. AffectCluster differences were observed in enjoyment of learning,

F(3,896) = 34.37, p b .001, η2 = .103. In line with the predictions,the multiple goals group scored higher than the performance, mastery

Table 2Cluster centroids, means and standard deviation of the clusters.

Achievement goal Cluster 1: performance(n = 273)

Cluster 2: mastery(n = 191)

Cluster 3: multiple goals(n = 301)

Cluster 4: low achievement goals(n = 135)

Centroid M SD Centroid M SD Centroid M SD Centroid M SD

Mastery − .32 3.59c .27 .27 4.33b .34 .91 4.67a .23 −1.04 3.21d .54Performance .22 3.79b .30 −1.03 2.91c .49 .85 4.28a .37 −1.63 2.92c .51

Note: Centroids computed using standardized (Z-transformation) scale scores to facilitate the interpretation of the clusters.Means and standard deviation computed using the actual scalescores. Means in the same row that do not share the same subscripts differ at p b .008 in the post hoc comparisons with Bonferroni adjustment.

100 E.D. Dela Rosa, A.B.I. Bernardo / Learning and Individual Differences 27 (2013) 97–101

and the lowmotivation group. The difference betweenmastery and per-formance group was not significant. The clusters also differed signifi-cantly in terms of anxiety, F(3,896) = 6.56, p b .001, η2 = .02. Thelow motivation group reported the highest levels of anxiety, while themultiple goals group scored the lowest. The multiple goals group sig-nificantly scored lower than the performance group but not than themastery group. No difference was found between the mastery and per-formance groups. Note that the effect sizes for both variables are also inthe low to medium range (Cohen, 1988).

4. Discussion

The current study was undertaken to validate the assumptions ofthe multiple-goals perspective in an Asian sample. Cluster analysis in-dicated that Filipino students differentiate between mastery and per-formance goals and that they may adopt either one dominant goal,combined goals or low levels of both goals. Although the study doesnot directly measure learning achievement in the students' class (andthis is a limitation of the present study), the results provide informationabout important achievement-related variables — the cognitive strate-gies and affective experiences of students who endorse differentachievement goals. The results were strongly supportive of the multi-ple-goals perspective, with students in themultiple goals group report-ed more use of deep learning strategies, more enjoyment of learning,and less anxiety. The learning strategies and affective experiences ofthose who adopt the mastery and performance goals singly have betterstrategy and affective profiles compared to those who adopt neithergoal, but what was interesting was that for most of the learning vari-ables, these two groups of students did not differ significantly, whichis certainly problematic for themastery-goal perspective, but quite con-sistent with the multiple-goals perspective.

The results also do not indicate any dampening or reduction ofthe effects combining performance with mastery goals. Instead, the re-sults indicate an enhancement of the learning processes. Consistentwith previous suggestion (Riveiro et al., 2001), themost desirable orien-tation for achievement behavior in the sample of Filipino studentsseems to be characterized by the combination of interest in attainingmastery, knowledge, and understanding with interest in obtaininggood grades and superiority over others. In this regard, our results addto the rather scant evidence for the multiple-goals perspective amongAsian students (Luo et al., 2011; Luo et al., 2011), and suggest that thetwo achievement goals orientations should not be seen as opposing in-dividual difference constructs. Instead, mastery and performance goals

Table 3Means and standard deviations of the dependent variables by clusters.

Dependent variables Cluster 1Performance(n = 273)

Cluster 2Mastery(n = 191)

M SD M

• Deep learning strategy 3.26b .67 3.23b

• Enjoyment of learning 3.41b .70 3.40b

• Anxiety 2.82a,b .77 2.68a,b,c

Note: Means in the same row that do not share the same subscripts differ at p b .008 in the po

should be understood as individual difference variables that are bestwhen interacting together.

While it is good to show that the multiple-goals perspective seemsto also apply to Filipino students, we should not neglect the fact thatthere are still unexplained differences in achievement goals betweenAsian students and students from other parts of the world (Hullemanet al., 2010). Research should try to understand why these differencesexist; and not just the differences involving Asian students. In this re-gard, it is not be safe to assume that the enhancing effect of multiplegoals works the same way for students from all cultures. For example,in the case of Filipino students, adopting performance-related goalsmay not be a maladaptive goal orientation because the demonstrationof learning achievement to significant others may be a component oftheir socially-oriented achievement motivation (Bernardo, 2008), andmay even be socially perceived as a positive behavior among someAsian cultures (Bernardo & Ismail, 2010). Although our results are con-sistentwith themultiple-goals perspective, we reiterate previous asser-tions that the specific meanings of these goals constructs might besomewhat different in different cultures (Dekker & Fischer, 2008; Luoet al., 2011). One recent attempt to understand how mastery and per-formance goals may be combined in a meaningful construct can beseen in the work on “academic personal best” (Liem, Ginns, Martin,Stone, & Herrett, 2012; Martin & Liem, 2010). Thus, future research onthe multiple-goals perspective among different groups of Asian stu-dents should continue to focus on similar efforts to understand the spe-cific meanings and mechanisms associated with how performance andmastery goals work together to bring about effective learning strategies,positive affective experiences, and higher learning achievement.

References

Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educa-tional Psychology, 84, 261–271.

Bernardo, A. B. I. (2003). Do Filipino youth really value education? Exploring Filipino ado-lescents' beliefs about the abstract and pragmatic value of education and its relation-ship to achievement goals and learning strategies. Philippine Journal of Psychology,36(2), 49–67.

Bernardo, A. B. I. (2004). Culturally-rooted beliefs and learning: Exploring the relation-ships among social axioms, achievement goals, and learning strategies of Filipino col-lege students. Philippine Journal of Psychology, 37(2), 79–100.

Bernardo, A. B. I. (2008). Individual and social dimensions of Filipino students' achieve-ment goals. International Journal of Psychology, 43, 886–891.

Bernardo, A.B.I., & Ismail, R. (2010). Social perceptions of achieving students and achieve-ment goals of students inMalaysia and the Philippines. Social Psychology of Education,13, 385–407.

Biggs, J., Kember, D., & Leung, D. (2001). The revised two-factor Study Process Question-naire: R-SPQ-2F. British Journal of Educational Psychology, 71, 133–149.

Cluster 3Multiple goals(n = 301)

Cluster 4Low motivation(n = 135)

SD M SD M SD

.70 3.57a .71 3.02c .69

.73 3.77a .66 3.07c .71

.84 2.58c .75 2.87a .76

st hoc comparisons (Bonferroni test).

101E.D. Dela Rosa, A.B.I. Bernardo / Learning and Individual Differences 27 (2013) 97–101

Byrne, B. M. (1994). Structural equation modeling with EQS and EQS/Windows: Basic con-cepts, applications, and programming. Thousand Oaks, CA: Sage.

Chan, K.W., & Lai, P. (2007). Revisiting the trichotomous achievement goal framework forHong Kong secondary students: A structural model analysis. The Asia-Pacific Educa-tion Researcher, 16, 11–22.

Chan, K.W., Wong, A. K. Y., & Lo, E. S. C. (2012). Relational analysis of intrinsic motivation,achievement goals, learning strategies, and academic achievement for Hong Kongsecondary students. The Asia-Pacific Education Researcher, 21, 230–243.

Chang, W. C., & Wong, K. (2008). Socially oriented achievement goals of Chinese univer-sity students in Singapore: structure and relationships with achievement motives,goals, and affective outcomes. International Journal of Psychology, 43, 880–885.

Cohen, J. (1988). Statistical power analysis for the behavior sciences (2nd ed.). London:Routledge.

Daniels, L., Haynes, T., Stupnisky, R., Perry, R., Newall, N., & Pekrun, R. (2008). Individualdifferences in achievement goals: A longitudinal study of cognitive, emotional, andachievement outcomes. Contemporary Educational Psychology, 33, 584–608.

Dekker, S., & Fischer, R. (2008). Cultural differences in academic motivation goals: Ameta-analysis across 13 societies. The Journal of Educational Research, 102(2), 99–110.

Dela Rosa, E. D., & Bernardo, A. B. I. (2013). Testing multiple goals theory in an Asian con-text: Filipino students' motivation and academic achievement. International Journal ofSchool and Educational Psychology, 1, 47–57.

Elliot, A., & Church, M. (1997). A hierarchical model of approach and avoidance achieve-ment motivation. Journal of Personality and Social Psychology, 72, 218–232.

Frenzel, A. C., Pekrun, R., & Goetz, T. (2007). Perceived learning environment and stu-dents’ emotional experiences: A multilevel analysis of mathematics classrooms.Learning and Instruction, 17, 478–493.

Garson, G. D. (2004). Multivariate analysis for applied social science. Retrieved from.http://www2.chass.ncsu.edu/garson/pa765/structur.htm

Harackiewicz, J. M., Barron, K. E., Carter, S. M., Lehto, A. L., & Elliot, A. J. (1997). Predictorsand consequences of achievement goals in the college classroom: Maintaining inter-est and making the grade. Journal of Personality and Social Psychology, 73, 1284–1295.

Harackiewicz, J. M., Barron, K., Pintrich, P., Elliot, A., & Trash, T. (2002). Revision of achieve-ment goal theory: Necessary and illuminating. Journal of Educational Psychology, 94,638–645.

Harackiewicz, J. M., & Linnenbrink (2005). Multiple achievement goals and multiplepatheways for learning: The agenda and impact of Paul R. Pintrich. Educational Psy-chologist, 40, 75–84.

Hau, K. T., & Ho, I. T. (2008). Editorial: Insights from research on Asian students' achieve-ment motivation. International Journal of Psychology, 43, 865–869.

Ho, I. T., & Hau, K. (2008). Academic achievement in the Chinese context: The role ofgoals, strategies, and effort. International Journal of Psychology, 43, 892–897.

Huberty, C., Jordan, E., & Brandt, W. (2005). Cluster analysis in higher education re-search. In J. C. Smart (Ed.), Higher education: Handbook of theory and research, Vol.20. (pp. 437–457)Dordrecht, Netherlands: Springer.

Hulleman, C. S., Schrager, S. M., Bodmann, S. M., & Harackiewicz, J. M. (2010). A meta-analytic review of achievement goal measures: Different labels for the same con-structs or different constructswith similar labels? Psychological Bulletin, 136, 422–449.

Kaplan, A., & Middleton, M. J. (2002). Should childhood be a journey or a race? Aresponse to Harackiewicz et al., (2002). Journal of Educational Psychology, 94,646–648.

Lau, S., Liem, A. D., & Nie, Y. (2008). Task- and self-related pathways to deep learning: Themediating role of achievement goals, classroom attentiveness, and group participa-tion. British Journal of Educational Psychology, 79, 639–662.

Liem, G. A. D., Ginns, P., Martin, A. J., Stone, B., & Herrett, M. (2012). Personal best goalsand academic and social functioning: A longitudinal perspective. Learning and Instruc-tion, 22, 222–230.

Liem, A.D., Lau, S., & Nie, Y. (2008). The role of self-efficacy, task value, and achieve-ment goals in predicting learning strategies, task disengagement, peer relation-ship and English achievement outcome. Contemporary Educational Psychology,33, 486–512.

Liem, A. D., & Nie, Y. (2008). Values, achievement goals, individual-oriented and social-oriented achievement motivations among Chinese and Indonesian secondary schoolstudents. International Journal of Psychology, 43, 898–903.

Linnenbrink, E. A. (2005). The dilemma of performance-approach goals: The use of mul-tiple goal contexts to promote students' motivation and learning. Journal of Educa-tional Psychology, 97, 197–213.

Luo, W., Hogan, D., & Paris, S. G. (2011). Predicting Singaporean students' achievementgoals in their English study: Self-construal and classroom goal structure. Learningand Individual Differences, 21, 526–535.

Luo, W., Paris, S. G., Hogan, D., & Luo, Z. (2011). Do performance goals promote learning?A pattern analysis of Singaporean students' achievement goals. Contemporary Educa-tional Psychology, 36, 165–176.

Martin, A. J., & Liem, G. A. D. (2010). Academic personal bests (PBs), engagement, andachievement: A cross-lagged panel analysis. Learning and Individual Differences, 20,265–270.

Meece, J., & Holt, K. (1993). A pattern analysis of students' achievement goals. Journal ofEducational Psychology, 85, 582–590.

Pekrun, R., Elliot, A., & Maier, M. (2006). Achievement goals and discrete academic emo-tions: A theoretical model and prospective test. Journal of Educational Psychology, 98,583–597.

Pekrun, R., Goetz, T., & Frenzel, A. (2005). Achievement Emotions Questionnaire (AEQ).User's manual. : Department of Psychology, University of Munich.

Pintrich, P. (2000). Multiple goals, multiple pathways: The role of goal orientation inlearning and achievement. Journal of Educational Psychology, 3, 544–555.

Riveiro, J., Cabanach, R., & Arias, A. (2001). Multiple-goal pursuit and its relation to cogni-tive, self-regulatory, andmotivational strategies. British Journal of Educational Psychol-ogy, 71, 561–572.

Shih, S. S. (2005). Role of achievement goals in children's learning in Taiwan. The Journalof Educational Research, 98(5), 310–319.

Valle, A., Cabanach, R. G., Nuñez, J. C., Gonzalez-Pienda, J., Rodriguez, S., & Piñeiro, I.(2003). Multiple goals, motivation and academic learning. British Journal of Education-al Psychology, 73, 71–87.

Wentzel, K. (1993). Motivation and achievement in early adolescence: The role of multi-ple classroom goals. Journal of Early Adolescence, 13(1), 4–20.