Effects of Emotional Intelligence on Attitudinal Learning in e-learning Environment

Effects of Emotional Intelligence on Attitudinal Learning in e-learning Environment Insook Lee inlee@sejong.ac.kr Professor Department of Education, Sejong University Seoul, Korea ABSTRACT This study intended to examine if emotional intelligence would be a significant variable in predicting attitudinal learning in e-learning context where learners were expected to develop better understanding about immigrant labors in Korea. Subjects were 30 undergraduate students undergraduate students enrolled in a university in Seoul, Korea. Participants were requested to participate in an intensive one week e-learning showcase, Introduction to Multicultural Understanding. Emotional intelligence was measured with Moon s 45-item questionnaire including perceiving emotions, expressing emotions, empathy, managing emotions, and using emotions. Attitude toward immigrant workers was collected with an 11-item questionnaire before and after learning. The findings support that emotional intelligence, especially empathy and perceiving emotion, can help to enhance learners positive attitude toward different cultures. The research result implicates that there is a need to support or educate people to develop emotional intelligence competencies in daily life or through learning opportunities in order to achieve more positive effects in attitudinal changes. Keywords: Emotional Intelligence, Attitude Change, Academic Achievement, e-learning INTRODUCTION Recent brain science has defined emotional and cognitive brains are connected to each other in a sense that decision or performance cannot be taken without working of emotional brain (Sparrow & Knight, 2006). In learning process, emotion along with cognition has been introduced with its critical role by various researches. Emotional intelligence as a sub-variable of emotion or emotional regulation has been recognized to be important in daily life, learning, and education. In learning process, emotional intelligence itself helps acquire new information (Graziano, Reavis, Keane, Calkins, 2007) and has a direct relation to learning achievement (Eisenberg, Sadovsky, & Spinrad, 2005; Hill, & Craft, 2003; Howse, Calkins, Anastopoulos, Keane, & Shelton, 2003). Pekrun (2006) identified the need for emotional intelligence in order to increase positive impact of emotion in learning situation; and Yang (2009) confirmed the effect of emotional regulation, which is how learners feel makes learning outcome different. However, there is still little research done about how emotional intelligences operate in learning achievement as an actual controller in e-learning environment. Considering sparse research on emotional intelligence in e-learning context, the current study tried to identify the academic effects on attitudinal learning of emotional intelligence in e-learning context in which learners' self-directed roles are emphasized. Definitions of Emotional Intelligences Different positions are observed in defining and measuring emotional intelligence. The most widely accepted definition among others might be the ability to monitor one s own and others' emotions, to discriminate among them, and to use the information to guide one's thinking and actions (Salovey & Mayer, 1990, 189). Mayer and Salovey (1997) suggest so to speak 'the four-branch model' that distinguishes the abilities and skills of emotional intelligences into ability to (1) perceive emotion, (2) use emotion to facilitate thought, (3) understand emotions, and (4) manage emotion. Moon (1997), based on

the Mayer-Caruso-Salovey Emotional Intelligence Test, has constructed a series of scales to measure EI for adult version. This test has five branches of emotional intelligence as follows: (1) Perceiving emotions involves the capacity to recognize and understand emotions in self and others. (2) Empathy involves the capacity of emotions to fully understand emotions in others and feel others' emotions like self's. (3) 'Expressing emotions involves the capacity to represent emotions in self or others with appropriate verbal, facial, or postural expressions. (4) Using emotions involves the capacity of emotions to apprehend the relationships among delicate emotions and enhance productive effects of performance through the facilitation of self's emotions. (5) 'Managing emotions' involves the capacity of emotion to analyze and control emotions in self, and manage and change emotions in others. Bar-On (1997) has defined emotional intelligence as an array of non-cognitive capabilities, competencies, and skills that influence one's ability to succeed in coping with environmental demands and pressures. Goleman (1995) views emotional intelligences as abilities such as being able to motivate oneself and persist in the face of frustrations; to control impulse and delay gratification; to regulate one's moods and keep distress from swamping the ability to think; and to empathize and to hope. EI and Academic Achievement Some research professed that emotional intelligence can be sometimes a more powerful predictor than cognitive intelligence to learning and performance (Goleman, 1995; Zins, Weissberg, Wang, & Walberg, 2004). Ability measures of emotional intelligence has been confirmed to be a significantly critical predictor for academic achievement even after controlling the factors of personality and cognitive abilities by various recent research such as Di Fabio & Palazzeschi (2009), MacCann, Fogarty, Zeider, & Roberts (2011), and Qualter, Gardner, Pope, Hutchinson & Whiteley (2012). Research further suggests that emotional intelligence may influence academic achievement through the ability to cope with stressors such as assessment, the dynamics of group collaboration, or the social and emotional demands of academic life; and mediate the relationship between cognitive abilities and GPA. (MacCann, Wang, Matthews, & Roberts, 2010; Petrides, Frederickson, & Furnham, 2004; Salovey, Bedell, Detweiller, & Mayer, 2000) A literature review (Lee, 2011) has concluded that emotional intelligence can facilitate positive attitudes in e-learning context. A recent study of Kang, Kim, & Chong (2011) identified through a survey of 217 students participating in distance education courses that innovative inclination, learning presence, and learning flow as part of emotional intelligence and regulation strategies have direct impacts on learning satisfaction. Vuorela and Nummenmaa (2004) produced the conclusion that emotional regulation (cognitive reappraisal and expressive suppression by Gross & John) affects learner participation in collaborative activities intensiveness; and learners who experienced more positive affects during the e-learning context were less aroused than those who experienced more negative affects. Kang & Goo (2007) demonstrated that emotional facilitation of thinking out of five sub types of emotional intelligences by Salovey and Mayer (1997) significantly predicts achievement in online team learning, but not online individual learning or offline learning. This finding implies that emotional facilitation of thinking would affect those abilities necessary for team learning and draw high academic achievement. METHOD Participants The total subject pool (N=30) was comprised of a sample of undergraduate students enrolled in a university in Seoul, Korea. Participants were taking an Introductory Educational Methodology and Technology offered as a teacher certificate course. They ranged in school years from sophomore to senior and their academic backgrounds were varied.

Research Instruments Self-Reported Emotional Intelligence (Moon's version) The level of emotional intelligence was measured with Moon s 45-item questionnaire including perceiving emotions, expressing emotions, empathy, managing emotions, e andd using emotions. Few examples of the statements are I clearly perceive my feeling or emotions ; I try to forget unpleasant feeling as soon as possible. Those items aree rated from 1 (strongly disagree) to 5 (strongly agree) and part of the statements are as Figure 1. A reliability test was performed on the questionnaires and Cronbach's alpha was 0.904. Figure 1. Part of self-reported emotional intelligence measures E-learning showcase Participants were requested to participate in an intensive one week e-learning showcase, Introduction to Multicultural Understanding. The e-learning contents include (1) definitions and current c situation of immigrant workers, (2) cases of discriminationn against immigrant workers, and (3) solutions to discrimination against immigrant workers. It has been delivered for individual i learning first followed by group discussions. The individual learning materials include facts,, laws and regulations, and case stories/news-clips/videos. The discussion activities were provided after each individual learning chapter c cover issues related to discrimination toward immigrant workers and solutions. Figure 2. Part of e-learning Showcase

Cultural Sensitivity Survey Attitude toward immigrant workers was collected with an 11-item questionnaire before and after learning in order to examine the attitude changes after learning. The items are rated from 1 (strongly disagree) to 5 (strongly agree) and the statements are as Table 1. A reliability test was performed on the questionnaires. Cronbach's alpha for pre-test was 0.90 and post-test was 0.92. Table 1. Attitude toward Immigrant Workers (pre- and post-test items) 1 I am concerned with immigrant workers. I might be uncomfortable with being with immigrant workers who look different and 2 can't speak in Korean well. I would like the chances to learn different cultures and traditions from them if I had 3 immigrant worker friends. 4 Immigrant workers might be fundamentally different from us Koreans. 5 I might be able to get along with an immigrant worker friend. 6 I feel a little awkward about immigrant workers who look different from us. 7 I'd like to treat them with respect if I work with them. 8 I get to avoid immigrant workers because I feel uncomfortable despite not knowing why. 9 I might be boasting about myself if I become a friend of immigrant workers. 10 I might be difficult to get to be a friend of immigrant workers. 11 I might be proud of myself if I become a friend of immigrant workers. RESULTS Descriptive statistics for attitude toward different cultures shows the mean of 66 points out of 100 for pre-test, and 76 points for post-test. A t-test was performed to show the effect of e-learning showcase and the result indicated that participants developed more positive attitude toward different cultures after learning (t= 5.99, p <.00). Results of multiple regression analyses revealed that emotional intelligence (R²=.183, p <.05), especially empathy (R²=.131, p <.05) and perceiving emotion (R²=.289, p<.00), predict improvement of positive attitude toward different cultures among the undergraduate students. Table 2. Summary of Regression Analysis for Variables Predicting Attitudinal Changes (n = 30) Variables R R² t p Perceiving emotion Expressing emotions Empathy Management of emotion Use of emotions Total.538.289 3.373.002.352.124 1.992.056.362.131 2.054.049.240.057 1.306.202.066.004.351.728.428.183 2.502.018

CONCLUSION Concerning attitude learning, the present result show that emotional intelligence predict its learning achievement, as most of the longitudinal research done in the international community. Another point of concern is that 'perceiving emotion' and 'empathy' are probably the best predictors of academic achievement. This result proposes the same vein as Roberts, Schulze, & MacCann (2008) s research identifying that perceiving emotions and empathy have very high relations with academic achievement, despite that managing emotions has very low relations with. The present study results implicate that there is a need to support or educate people to develop emotional intelligence competencies in daily life or through learning opportunities in order to achieve more positive effects in academic performances. Considering that emotional intelligences can be improved through external intervention (Pool & Qualter, 2012), the assertion for external help to improve EI seems quite convincing. Recently, various models which intend to improve EI have been increasingly suggested and researched (e.g. Mikolajczak, Petrides, Coumans, & Luminet, 2009; Nelis, Quoidbach, Mikolajczak, & Hansenne, 2009). REFERENCES Bar-On, R. (1997). The emotional intelligence inventory (EQ-i): Technical manual. Toronto: Multi- Healthsystems. Di Fabio, A., Palazzeschi, L. (2009). An in-depth look at scholastic success: Fluid intelligence, personality traits or emotional intelligence? Personality and Individual Differences, 46, 581 585. Eisenberg, N., Sadovsky, A., Spinrad, T. L. (2005). Associations of emotion-related regulation, language skills, emotion knowledge, and academic outcomes. New Directions in Child and Adolescent Development, 109, 103 118. Goleman, D. (1995). Emotional intelligence. New York: Bantam Books. Graziano, P., Reavis, R., Keane, S., Calkins (2007). The role of emotion regulation and the studentteacher relationship in children s academic success. Journal of School Psychology, 45, 3-19. Gross, J.J., John, O.P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85(2), 348-362. Hill, N. E., Craft, S. A. (2003). Parent-school involvement and school performance: mediated pathways among socioeconomically comparable African American and Euro-American families. Journal of Educational Psychology, 95, 74-83. Howse, R., Calkins, S., Anastopoulos, A., Keane, S., Shelton T. (2003). Regulatory contributors to children's kindergarten achievement. Early Education and Development, 14, 101-119. Kang, D-S., Kim, J-K., Chong, H-I. (2011). The structural relationship among affective characteristics, learning presence, learning flow, learning satisfaction in distance education. The Journal of Educational Information and Media, 17(1), 133-152. Kang, M. & Goo, N. (2007). Predictive validity of emotional intelligence on various achievements in blended learning environment. Korean Journal of Curriculum and Instruction, 11(1), 235-255. Lee, I. (2011). Emotion, emotional intelligence, and e-learning. Proceedings of the 9th ICoME 2011 of KAEIM & JAEMS (pp. 1-4), Seoul, Korea, August 26-28, 2011. MacCann, C., Fogarty, G. J., Zeidner, M., Roberts, R. D. (2011). Coping mediates the relationship between emotional intelligence (EI) and academic achievement. Contemporary Educational Psychology, 36, 60 70. MacCann, C., Wang, L., Matthews, G., Roberts, R. D. (2010). Emotional intelligence and the eye of the beholder: Comparing self- and parent-rated situational judgments in adolescents. Journal of Research in Personality, 44, 673-676.

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