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The Relationship between Personality, Emotional Intelligence,Learning Motivation and Learning Strategies of University Students in Hong KongCecilia Nga-tak Li, Hong Kong Shue Yan University, [email protected] Leung, Hong Kong Shue Yan University, [email protected] research have been conducted to investigate the relationshipbetween learning motivation and learning strategies (Chang, 2005; Pintrich, 1989; 1995;1999). Pintrich (1995) suggested that intrinsically motivated students would applycognitive learning strategies and deeper processing in the task. The roles of personalityin relation to learning motivation have also been investigated by many researchers.Müller, Palekčić, Beck and Wanninger (2006) suggested that the big five personalityfactors were related to a continuum of motivational orientation, with six regulatory stylesof self-determination located at points of amotivation, extrinsic motivation and intrinsicmotivation. Besides personality traits, people usually neglect emotional aspects which areunconscious but important for sustaining and determining the motivational orientation(Müller et al.). Christie, Jordon, Troth and Lawrence (2007) suggested that emotionalintelligence and motivation should be separate factors as proposed by Mayer andSalovey (1990). In contrast, Goleman (1995; 1998) argued that self-motivation is one ofthe subsets of emotional intelligence (as cited in Christie et al., 2007). In this study, therelationship between big five personality (Goldberg, 1990; John, 1990; McCrae & Costa,1989), emotional intelligence theory (Goleman, 1995), self-determined motivation theory(Deci & Ryan, 1985), and self-regulated learning strategies (Pintrich, 1989) wereinvestigated by structural equation analyses.Two hundred and three Hong Kong university students participated in the presentstudy. Four questionnaires which measure personality, emotional intelligence, learningmotivation and learning strategies, were administrated to the participants. Personality andemotional intelligence were found to be significant predictors of learning motivation andlearning strategies. This study has implications for reminding teachers, educators andeducational psychologists the  importance  of  students’  personality  and  emotionalintelligence in order to encourage the development of intrinsic motivation andmeta-cognitive self-regulated learning strategies in students.IntroductionThere is no doubt learning motivation has being spotlighted in educationalresearch throughout the recent decades. Learning motivation is one of the crucial factors1

that determine the academic success of students and their learning behaviors (Deci,Vallerand, Pelletier, & Ryan, 1991). In order to promote students academic success,teachers and educators put much effort in fostering students’  development of higherlevels of learning motivation and more effective learning strategies. As a consequence,there is a growing interest to study the individual aspects like personality and emotionalintelligence in affecting students’  motivation.  Everyone  acts  and  thinks  differently  as  wepossess unique types of personality. Müller et al. (2006) stated that students with differentpersonality show different motivational orientations. Just like  one’s  trait, emotionalintelligence is one of the individual competences which vary among individuals. Somepeople are more  capable  to  handle  own  feelings  and  understand  others’  emotion whilesome are not. Therefore, it is worthwhile to  see  how  students’  emotional  intelligence andpersonality are related to their learning motivation and use of learning strategies. Topromote the use of effective learning styles, teachers and educators can help students tolearn of their own personal interests and gain knowledge of what they really want to knowby understanding their personality and emotional intelligence.Literature ReviewsPersonality and learning motivationIn Müller et al. (2006)’s  study  of  personality  and  self-determined learning motivation,the five personality factors (Big Five) were found to be related to different levels ofperceived self-determination (as shown by Self-determination Index, SDI; Vallerand,1997;as cited in Müller et al.,2006). For students who are conscientious, they set clear goalsand establish skills to create person-environment interaction. They tend to beself-motivated and intrinsically motivated to learn. Extraversion was found to be related toexternal and interest-related motives. Similar to the results of extraversion,agreeableness is correlated with social as well as personal motives. Neurotic individualswere found to have lower motivation for personal interest. Those who scored high inopenness would like to try new activities with their own needs and incentives. In overall,students who scored high in conscientiousness, agreeableness and openness were moreself-determined motivated in their learning (Müller et al., 2006).Moreover, the  role  of  big  five  in  prediction  of  undergraduates’  academic  motivationwas investigated by Komarraju, Karau and Schmeck (2009). Similar to the results ofMüller et al. (2006) s’ study, Komarraju et al. (2009) suggested that conscientiousstudents were more self-motivated to engage in tasks and study. Students who scored2

high in openness were comparatively more intrinsically motivated and they found thatlearning was interesting. On the other hand, extroverted and emotionally unstablestudents were extrinsically motivated only for pursuing a college degree and disagreeablestudents were less likely to engage in the classroom activities and would displayantisocial behaviors (Komarraju et al., 2009).Emotionally intelligent and learning motivationIt is argued that self-motivation is one of the competencies of emotional intelligence(Goleman, 1995). This view includes motivation as the factor of emotional intelligence.Other researchers stated that motivation only links to emotional intelligence rather than afactor of it (Christie, 2007; Mayer & Salovey, 1990). In Christie et al. (2007)’s  study,they investigated  the  relationship  between  Mayer  and  Salovey  (1990)’s  conceptualizationof  emotional  intelligence  and  McClelland  (1961)’s  theory  of  motivation  (the  motivationalneeds of achievement, affiliation and power). The results supported Mayer and Salovey(1990)’s  views  that  motivation  only  co-varied with emotional intelligence and did not forma sub-component  of  emotional  intelligence.  This  contradicted  with  Goleman’sconceptualization of personal drive to be a subset of emotional intelligence. As there arestill controversies in the relationship between emotional intelligence and motivation, thesestudies encourage further research to confirm the link between the two constructs byusing different measures of motivation like goal-attainment model or self-determinationperspective, and other self-reporting measures of emotional intelligence.Learning Motivation and Learning StrategiesMotivation links closely with the use of strategies in a task. Students who areintrinsically motivated students would apply more cognitive strategies and deeperprocessing in the task (Pintrich, 1995). Pintrich (1999) suggested that self-regulation issustained by combining both motivation and cognition in learning. Self-regulatorystrategies can be facilitated by promoting the mastery goals (Pintrich, 1999). Studentswho focused on mastering the tasks by self-improvement would adopt more cognitivestrategies and self-regulatory strategies. On the other hand, students who focus ongetting high marks and pleasing others (extrinsic goals) were found to use less cognitivestrategies and self-regulatory strategies (Pintrich, 1999).Chang (2005)’s  study  also  stated  that  motivation  is  one  of  the  factors  that  affect  theuses of learning skills. The study showed significant relationship between the qualities ofmotivation and the use of learning strategies. Intrinsic motivation was significantly3

correlated with cognitive strategies (Chang, 2005). External motivation was found to benegatively correlated with cognitive strategies. This showed that students who focus onexternal rewards in learning are less likely to pay effort and time in deep-processingstrategies, especially engaging in cognitive processes like elaboration and organization,rather they would apply skills like note-taking or outlining to achieve academic success(Chang, 2005). On the other hand, intrinsically motivated students are more likely toevaluate and plan their learning with the use of deeper mental processing (Chang, 2005).The study of learning motivation and learning strategies were consistent by showingthe strong linkage between them. The authors especially highlighted the relationshipbetween intrinsic motivation and the two types of learning strategies, cognitive andmetacognitive strategies. Their works contributes to promote environment which cancultivate more intrinsic regulation in students and help them to develop higher order oflearning strategies.HypothesesThe present study intends to investigate the relationship between personality,emotional intelligence, learning motivation and learning strategies amongundergraduates in Hong Kong. The present study hypothesized that:H1: There were significant relationships between personality and learning motivationat the p .05 level. Particularly, openness, conscientious, extraversion, agreeablenessand neuroticism would have significant relationship with intrinsic motivation to know,intrinsic motivation to accomplish, intrinsic motivation to experience stimulation, extrinsicmotivation identified regulation, extrinsic motivation introjected regulation, extrinsicmotivation external regulation, and amotivation.H2: There were significant relationships between emotional intelligence and learningmotivation at the p .05 level. Particularly, knowing ones emotion, managing emotions,motivating oneself, recognizing emotions in others and handling relationships would havesignificant relationship with intrinsic motivation to know, intrinsic motivation to accomplish,intrinsic motivation to experience stimulation, extrinsic motivation identified regulation,extrinsic motivation introjected regulation, extrinsic motivation external regulation, andamotivation.H3 and H4: There were significant relationships between learning motivation andlearning strategies at the p .05 level. Particularly, intrinsic motivation to know, intrinsic4

motivation to accomplish, intrinsic motivation to experience stimulation would havepositive significant relationship with rehearsal, elaboration, organization, critical thinkingand metacognitive self-regulation (H3). Extrinsic motivation identified regulation, extrinsicmotivation introjected regulation, extrinsic motivation external regulation and amotivationwould have negative significant relationship with rehearsal, elaboration, organization,critical thinking and metacognitive self-regulation (H4).MethodParticipantsThe questionnaires were administrated to 203 undergraduates in Hong Kong. Theaverage age was 20.8 years (SD 1.53), and 37.9 % (N 77) were male and 62.1% (N 126) were female. Samples were drawn from the universities and institutions in HongKong including a number of majors, covering arts, sciences, and social sciences.ProcedureData collection was started from October 2010 to March 2011. A pilot study (N 63) was conducted in December 2010. Participants in the pilot study were drawn fromone Hong Kong private university studying Introductory Psychology in winter 2010. Othersamples were collected by sampling from other tertiary institutes in Hong Kong. Allparticipants were informed that their participation was voluntary and their responseswould be confidential. Participants were given a consent form and a debriefing sectionrespectively before and after the study.MeasuresAll questionnaires were translated from English to Chinese. The whole set ofquestionnaires was divided into five parts: demographic information (age, sex, name ofinstitution, level of study, and faculty of study), learning motivation questionnaire, learningstrategy questionnaire, emotional intelligence questionnaire and personalityquestionnaire.Big Five Inventory (BFI). This scale measures the five personality types which includeOpenness ( .76), Conscientiousness ( .70), Extraversion ( .79), Agreeableness( .55), and Neuroticism ( .75) (John, Donahue, & Kentle, 1991). The questionnairecontains 44 items on a 5-point Likert  Scale  (1  represents  “Strongly  disagree”  and  55

represents  “Strongly  agree”).Emotional Intelligence Scale of Adolescent (EIS). This scale was developed by Sun(2004) and based  on  Goleman  (1995)’s  five  domains  of  emotional  intelligence:  “Knowingone’s  emotion”  ( .35),  “managing  emotions”  ( .56),  “motivating  oneself”  ( .66),“recognizing  emotions  in  others”  ( .74)  and  “handling  relationships”  ( .69). TheChinese version of questionnaire has 27 items on a 4-point  Likert  Scale  (1  represents  “Inever  do  that”  and  4  represents  “I  always  do  that”).Academic Motivation Scale (AMS). This scale was used to measure the learningmotivation of students based on SDT (Vallerand et al., 1992). There are seven subscaleson the AMS: Amotivation (AMOT) ( .82), External Regulation (EMER) ( .88),Introjected Regulation (EMIN) ( .72), Identified Regulation (EMID) ( .82), IntrinsicMotivation to Experience Stimulation (IMES) ( .83), Intrinsic Motivation to Accomplish(IMTA) ( .79) and Intrinsic Motivation to Know (IMTK) ( .73). AMS contains 28 itemson a 5-point  Likert  Scale  (1  represents  “Does  not  correspond  at  all”  and  5  represents“corresponds  exactly”).Motivated Strategies for Learning Questionnaire (MSLQ). This scale comprises of twoparts--motivation scales and learning strategies scales, which measures the two broaddimensions of self-regulation: Motivation and learning strategies (Pintrich & De Groot,1990). The present study only adapted the Learning Strategies Scale regarding thecognitive and metacognitive strategies. The cognitive and metacognitive strategiessection contains 35 items on a 7-point  Likert  Scale  (1  represents  “not  at  all  true  of  me”and 7 represents  “very  true  of  me”)  ( .87). The five strategies include rehearsal,elaboration, organization, critical thinking and metacognitive self-regulation.ResultsDescriptive Statistics and Correlational AnalysisThe mean, standard deviations and correlations for personality, emotionalintelligence, learning motivation and learning strategies are indicated in Table 1 below.Table 16

Means, Standard Deviation, Intercorrelations for Personality, Emotional Intelligence,Learning Motivation and Learning Strategies.Reliability AnalysisTable 2 shows the reliabilities of the four constructs under studied. The internalconsistencies of the five subscales of personality were satisfactory to good, rangingfrom .56 to .80. Whereas the internal consistencies of the five subscales of emotionalintelligence were ranging from .53 to .77. For learning motivation, the internalconsistencies of the seven subscales were good and satisfactory, ranging from .77 to .84.The internal consistencies of the five subscales of learning strategies were rangingfrom .54 to .77.Table 2Reliability Coefficient Alphas for Personality, Emotional Intelligence, Learning Motivation7

and Learning Strategies.ScalesCoefficientAlphasPersonality1. Openness0.802. Conscientiousness0.723. Extraversion0.774. Agreeableness0.565. Neuroticism0.72Overall0.71Emotional Intelligence1.  Knowing  one’s  emotion0.532. Managing emotions0.653. Motivating oneself0.764. Recognizing emotions in others0.755. Handling relationships0.77Overall0.81Learning Motivation1.Intrinsic Motivation to Know (IMTK)0.812.Intrinsic Motivation to Accomplish (IMTA)0.803.Intrinsic Motivation to Experience Stimulation (IMES)0.774.Extrinsic Motivation Identified Regulation (EMID)0.785.Extrinsic Motivation Introjected Regulation (EMIN)0.786.Extrinsic Motivation External Regulation (EMER)0.817.Amotivation (AMOT)0.84Overall0.81Learning zation0.644.Critical Thinking0.735. Metacognitive self-regulation0.72Overall0.89Path Analyses8

Analyses of observed and latent variables in this study were conducted by usingstructural equation modeling (SEM) generated by LISREL 8.51. Path analysis models inSEM hypothesized the predictive relations between variables (observed or latent) withtheoretical grounding (Shipley, 2000; as cited in Pugesek, Tomer, & Eye, 2003). The pathmodels indicate the direct or indirect effect of independent variables on dependentvariables. Also, SEM concerns more on the confirmatory aspect of the proposedtheoretical models (Raykov & Marcoulides, 2000; as cited in Pugesek, Tomer, & Eye,2003). As shown in Model 1 and 2, the five factors of personality and emotionalintelligence respectively act as the antecedents in predicting learning strategies withmediator learning motivation. There were quite a number of significant findings in the twomodels.The results showed that openness, conscientiousness and neuroticism hadsignificant relationships with the factors of learning motivation (see Model 1) in predictinglearning strategies. From the second level (learning motivation) to the third level (learningstrategies) of the path diagram, the factors IMTK, IMES, EMID, EMIN and AMOT weresignificantly related to learning strategies. In the correlation among the antecedents,neuroticism had negative correlation with the other four factors, whereas openness,conscientiousness, extraversion and agreeableness correlated positively with oneanother.For  the  domain  “motivating oneself”  of  emotional  intelligence,  it was found to bepositively related to IMTK, IMTA, IMES, EMID and negatively related to AMOT withstatistically significances (see Model 2). The relationships between second level and thethird level of Model 2 were similar to that of Model 1. Among the correlation between thefive antecedents, only “managing emotion” was found to be correlated negatively with“recognizing emotion in others” and “handling relationship”, whereas other factorscorrelated positively with one another.Model 3 and 4 show the predictive relation of personality and emotionalintelligence with learning motivation and learning strategies. A satisfactory goodness of fitindex of personality model was obtained ( 2 (52) 211.41, GFI .85, CFI .78, RMSEA .12) (see Model 3). This fairly confirmed that openness and conscientiousness weresignificant indicators of personality to predict learning strategies with mediator learningmotivation.For the emotional intelligence model, a satisfactory goodness of fit index was also9

obtained ( 2(63) 198.74, GFI .87, CFI .83, RMSEA .09) (see Model 4). Thisconfirmed that “knowing one’s emotion”, “motivating oneself” and “recognizing emotion inothers” were significant indicators of emotional intelligence to predict learning strategieswith mediator learning motivation.10

Model 1. The path model showing the effects of personality on learning motivation and learningstrategies.Note: *p 0.05, **p 0.01; IMTK Intrinsic motivation to know; IMTA Intrinsic motivation to accomplish;IMES Intrinsic motivation to experience stimulation; EMID Extrinsic motivation identified regulation;EMIN Extrinsic motivation introjected regulation; EMER Extrinsic motivation external regulation;AMOT Amotivation.11

Model 2. The path model showing the effects of emotional intelligence on learning motivation andlearning strategies.Note: *p 0.05, **p 0.01; IMTK Intrinsic motivation to know; IMTA Intrinsic motivation toaccomplish; IMES Intrinsic motivation to experience stimulation; EMID Extrinsic motivationidentified regulation; EMIN Extrinsic motivation introjected regulation; EMER

intrinsic motivation to accomplish, intrinsic motivation to experience stimulation, extrinsic motivation identified regulation, extrinsic motivation introjected regulation, extrinsic motivation external regulation, and amotivation. H2: There were significant relationships between emotional intelligence and learni