Linking Personality Traits to Emotional Intelligence: A Study on Psychological Characteristics of EFL Students Mania Nosratinia 1 , Elnaz Sarabchian 2 1 Department of Foreign Language Teaching, English Department, Islamic Azad University at Central Tehran, Tehran, Iran. 2 MA. Candidate at Department of Foreign Language Teaching, English Department, Islamic Azad University at Central Tehran, Tehran, Iran. The First National Conference in Teaching English, Literature and Translation (NCTLT) Kharazmi International Institute for Research & Education August 2013. Shiraz- Iran Introduction Learning can be defined as acquiring new or changing existing awareness, skills, behaviors, or values. In 21th century, researchers, teachers, and educators have examined and emphasized on some factors that can be important in learning, especially scholastic learning. In this domain personality factor and emotional intelligence are two concepts that have absorbed many attentions. In this regard. emotional intelligence is the capacity for recognizing our own feelings and those of others, for motivating ourselves, and for managing emotions well in ourselves and in our relationships (Goleman, 1995). Research indicates that emotional skills are associated with success in many areas, including effective teaching, student learning, and academic performance (Brackett & Salovey, 2004; Mayer, Salovey & Caruso, 2004; Sutton & Wheately, 2003). In addition to emotional intelligence, one of the most important factors in learning is personality. In this field, the five- factor model (FFM) of personality is a conceptualization of personality comprising behavioral, emotional and cognitive patterns, which comprehensively covers the five major traits that define human personality across cultures: Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness (Terracciano & McCrae, 2005). Big- Five Personality Traits The Big-five framework of personality traits (Costa & McCrae, 1992) has emerged as a robust and parsimonious model for understanding the relationship between personality and various academic behaviors (Poropat, 2009). Personality refers to internal factors such as dispositions and interpersonal strategies that explain individual behaviors and the unique and relatively stable patterns of behaviors, thoughts, and emotions shown by individuals (Hogan, Hogan, & Roberts, 1996). Many psychologists reached the agreement that a five-factor model, which was referred to as the “Big Five”, could describe personality. This model is based on adjectives, which describe the personality of an individual. The Big Five personality traits include Extraversion, Agreeableness, Conscientiousness, Emotional stability, Openness to experience (Robbins, Judge & Timothy 2008). Emotional Intelligence Emotional intelligence refers to “an ability to recognize the meanings of emotions and their relationships, and to reason and problem-solve on the basis of them” (Mayer, Caruso & Salovey, 2000). According to Goleman (1995), who was responsible to popularize the term, emotional intelligence is an important factor in determining personal success as a student, teacher, parent, manager, and leader. An alternative model proposed by Bar On (1997) has placed emotional intelligence in the context of personality theory. Recent debates on EI have focused largely on whether trait EI measured by self-report tests has predictive power over personality traits. In spite of the important role of emotional intelligence and personality traits in the learning process, little is known about the predictability of EI domains and clusters through BFPT. This study investigates the relationship between personality traits and emotional intelligence domains and clusters, with an emphasis on predictability of EI through personality traits. In line with the above purpose, this study tries to answer the following research questions: Is there any significance relationship among EFL learners’ EI domains and clusters with BFPT? Is there any significant difference in the predictability of EFL learners’ BFPT in terms of predicting their EI? References Bar-On, The Emotional Qoutient Inventory (EQ-i). Mulri-Health Systems, ed. T. Manual, Toronto, 1997. Costa P, & McCrae, R., Revised NEO personality inventory (NEO-PI-R) and NEO five-factor inventory (NEO-FFI) professional manual. FL: Psychological Assessment Resources Inc., ed. Odessa, 1992. Golman D, Emotional Intelligence: Why It Can Matter More Than IQ, New York: Bantam Books, 1995. McCrae RR, Terracciano, A, 78 Members of the Personality Profiles of Cultures Project. Universal features of personality traits from the observer's perspective: Data from 50 cultures. J Pers Soc Psychol, 2005; 88(547-561). Poropat AE, A meta-analysis of the five-factor model of personality and academic performance. Psychological Bulletin, 2009; 135,: 322–338. Robbins SP, Judge, Timothy. A,, Organizational Behaviour: Prentise Hall, 2008. Sutton RE, & Wheatley, K. F., Teachers' emotions and teaching: A review of the literature and directions for future research. Educational Psychology Review,, 2003; 15(4): 327–358. Abstract This study investigates the relationship among EFL learners’ personality characteristics and competencies of emotional intelligence (EI). Major emphasis was placed on the extent to which several EI competencies can be predicted by personality factors. A group of 211 male and female EFL students majoring in English Translation and English Literature, were randomly selected and given two questionnaires. The NEO-Five Factor Inventory was used to assess students’ personality traits. The EI of the students was assessed through Bar-On Emotional Quotient Inventory. Running multiple regressions revealed that Neuroticism was the best single predictor of EI and predicted 40 percent of EI. Conscientiousness was the second best predictor, which increased the predictive power to 48 percent. Extroversion as the third best predictor, enhanced the predictive power up to about 50 percent, and finally the last best predictor, openness to experience increased the predictive power to 51.8 percent. Also, running Pearson Product Moment correlation coefficient indicated that four of the components of BFPT –except for Openness to Experience– show significant correlations with EI (P < .05). As for subscales of EI, Neuroticism showed significant correlations with all of the subscales of EI, except for Interpersonal subscale. Extroversion, Agreeableness and Conscientiousness showed significant but negative correlations with subscales of EI. Finally, Openness to Experience showed non-significant correlations with components of EI. It can be concluded that five factor model of personality had strong influence on EI of EFL learners. Results and Discussion Correlation between Personality Traits and EI As displayed in Table 1 four of the components of BFPT – except for Openness to Experience – show significant correlations with EI (P < . 05). They range for a high of .63 (P = .000 < .05) for Neuroticism to -.03 (P = .663 > .05) for Openness to Experience. Pearson Correlations among the NEO-FFI Domains with the EI Clusters Table 2 displays the Pearson correlation between the components of EI and BFPT. Neuroticism shows significant and large correlations with all of the components of EI except for Interpersonal. Extroversion, Agreeableness and Conscientiousness show significant but negative correlations with subscales of EI. However, Openness to Experience shows non-significant correlations with components of EI. Predictability of EI through personality traits A multiple regression is run to probe the power of the components of BFPT in predicting EI. As displayed in Table 3, Neuroticism (R = .63, R 2 = .40) is the best predictor of EI. It can predict 40 percent of EI. Conscientiousness is the second best predictor, which increases the predictive power to 48 percent (R = .693, R 2 = .480). Extroversion is the third best predictor, which increases the predictive power to about 50 percent (R = .713, R 2 = .508). And finally the last best predictor, i.e. Openness to Experience increases the predictive power to 51.8 percent (R = .720, R 2 = .518). Agreeableness is not entered into the regression model despite its moderate correlation with EI. The results of the ANOVA test (P < .050) indicate that the regression models at the four above-mentioned steps enjoy statistical significance (Table 4). The Normal Probability-Probability (P-P) Plot 1 shows the assumption of linearity is met. All of the dots fall almost on diagonal. Conclusion It seems that English teachers can increase students' emotional intelligence capabilities and related skills like understanding personal feelings, sympathy and stress control. In doing so, English language teachers should first become familiar with the concept of emotional intelligence and try to improve their abilities and then try to develop learners' EI. Some of the effective factors in emotional intelligence are: class discussion, listening to light music, watching short emotional movies, self-expression, designing questionnaires and reading psychological and literal texts. Concerning emotional intelligence capabilities, using questionnaires or forming class discussion groups, for example, can contribute to emotional literacy. Class discussions that allow students express their feelings comfortably and share them with others can provide unstressful situation to know themselves and others better and thus create a better relationship with others in order to learn English. Considering that personality factor and emotional intelligence associated with academic success and the combination of EI and personality can be used as a stronger predictor of learning. It is advised that in teaching of the lessons and designing educational materials and methods should emphasize on personality traits and EI in an efficient and non-stress way for students. Methodology Participants Two hundred and eleven Iranian students, ranging between 20-30 years old, majoring in English Language Literature and English Language Teaching were randomly selected. The participants were almost evenly split between men (48.0%) and women (52.0%). Personality Questionnaire NEO-Five-Factor Inventory (NEO-FFI): The NEO-FFI is a shortened version of the Revised NEO Personality Inventory (NEO PI-R) and provides a measure of the five domains of adult personality using a 60-item form (Costa & McCrae, 1992). Sixty items are rated on a 5-point scale and require 10–15 minutes to complete. Emotional Intelligence Questionnaire To evaluate students’ EI, the researchers employed "Bar-On EQ-i test”. Bar-On EI test, called the emotional quotient inventory (EQ-i), is a self-report measure of emotionally and socially intelligent behavior that provides an estimate of emotional-social intelligence (Bar- On, 1997). The test includes 90 items in the form of short sentences, which measures five broad areas of skills and fifteen factorial components. It employs a five-point response scale with a textual response format ranging from 'very seldom' or 'not true of me' to 'very often' or 'true of me'. Each item has the value of 5 ranging to 1. EI Neuroticism Pearson Correlation .633 ** Sig. (2-tailed) .000 N 211 Extroversion Pearson Correlation -.502 ** Sig. (2-tailed) .000 N 211 Openness to experience Pearson Correlation -.030 Sig. (2-tailed) .663 N 211 Agreeableness Pearson Correlation -.413 ** Sig. (2-tailed) .000 N 211 Conscientiousness Pearson Correlation -.431 ** Sig. (2-tailed) .000 N 211 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). Table 1: Pearson Correlation between Big-Five Personality Traits and Emotional Intelligence Intrapersonal Interpersonal Adaptability Stress Management General Mood Neuroticism Pearson Correlation .621 ** .092 .549 ** .507 ** .515 ** Sig. (2-tailed) .000 .183 .000 .000 .000 N 211 211 211 211 211 Extroversion Pearson Correlation -.463 ** -.248 ** -.350 ** -.261 ** -.560 ** Sig. (2-tailed) .000 .000 .000 .000 .000 N 211 211 211 211 211 Openness To experience Pearson Correlation -.070 -.119 -.005 .085 .027 Sig. (2-tailed) .312 .084 .941 .217 .700 N 211 211 211 211 211 Agreeableness Pearson Correlation -.266 ** -.358 ** -.376 ** -.352 ** -.278 ** Sig. (2-tailed) .000 .000 .000 .000 .000 N 211 211 211 211 211 Conscientiousness Pearson Correlation -.347 ** -.298 ** -.413 ** -.266 ** -.317 ** Sig. (2-tailed) .000 .000 .000 .000 .000 N 211 211 211 211 211 **. Correlation is significant at the 0.01 level (2-tailed). Table 2: Pearson Correlation between Subscales of EI and BFPT Model R R Square Adjusted R Square Std. Error of the Estimate 1 .633 a .401 .398 28.065 2 .693 b .480 .475 26.225 3 .713 c .508 .501 25.557 4 .720 d .518 .509 25.352 a. Predictors: (Constant), Neuroticism b. Predictors: (Constant), Neuroticism, Conscientiousness c. Predictors: (Constant), Neuroticism, Conscientiousness, Extroversion d. Predictors: (Constant), Neuroticism, Conscientiousness, Extroversion, Openness to experience e. Dependent Variable: EI Table 3: Model Summary BFPT and EI Table (4): ANOVA Test of Significance of Regression Model BFPT and EI Model Sum of Squares df Mean Square F Sig. 1 Regression 110344.542 1 110344.542 140.098 .000 b Residual 164613.439 209 787.624 Total 274957.981 210 2 Regression 131909.151 2 65954.576 95.901 .000 c Residual 143048.830 208 687.735 Total 274957.981 210 3 Regression 139751.730 3 46583.910 71.320 .000 d Residual 135206.251 207 653.170 Total 274957.981 210 4 Regression 142561.428 4 35640.357 55.454 .000 e Residual 132396.553 206 642.702 Total 274957.981 210 a. Dependent Variable: EI b. Predictors: (Constant), Neuroticism c. Predictors: (Constant), Neuroticism, Conscientiousness d. Predictors: (Constant), Neuroticism, Conscientiousness, Extroversion e. Predictors: (Constant), Neuroticism, Conscientiousness, Extroversion, Openness to experience Normal P-P Plot 1: Linearity of Regression Model BFPT and EI