Improving Emotion Perception and Emotion Regulation Through a Web-Based Emotional Intelligence Training (WEIT) Program for Future Leaders
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Emotional Intelligence and Acquisition of English Language Oral Communication Skills9
Advanced Education Issue 15, 2020 ISSN: 2409-3351 EMOTIONAL INTELLIGENCE AND ACQUISITION OF ENGLISH LANGUAGE ORAL COMMUNICATION SKILLS9 Тetiana Andrienko Kyiv International University, Kyiv, Ukraine [email protected] Nataliia Chumak Taras Shevchenko National University of Kyiv, Kyiv, Ukraine [email protected] Vlad Genin UOPX, Silicon Valley-Bay Area Campus, San Francisco, California, USA [email protected] Studying the factors of successful acquisition of ESL speaking skills in Ukrainian adult learners, the authors focused on the correlation between emotional intelligence and development of oral communication skills, and, on the other hand, on the growth of these indicators as a result of purposeful inclusion of content-related emotions into activities aimed at the development of speaking and listening skills. Theoretically based on the ideas of emotional intelligence as an important factor in human interaction and guided by the hypothesis that content-related emotions intensify emotional involvement and have a positive influence on the acquisition of oral communication skills, the researchers applied Mayer-Salovey-Caruso Emotional Intelligence Test and the English Language Oral Communication Skills Test developed by the authors, to measure the key oral communication skills indicators against a 100 point scale. Experimental teaching of 124 undergraduate students of International Relations during September 2018 – May 2019 proved a beneficial influence of including emotions in the learning activities on the acquisition of ESL oral communication skills, as well as on student motivation and overall quality of student experiences. Significant increments in Emotional Intelligence and ESL oral communication skills in the experimental group compared to insignificant growth of the same indicators in the Reference group allow to establish a positive correlation between the growth of emotional intelligence and acquisition of the ESL speaking skills pursuant to inclusion of content-related emotions into the ESL learning in Ukrainian students. -
What Is Emotional Intelligence (EQ)?
What is Emotional Intelligence (EQ)? By Michael Akers & Grover Porter – available online at: http://psychcentral.com/lib/what-is-emotional-intelligence-eq/ ~ 2 min read For most people, emotional intelligence (EQ) is more important than one’s intelligence (IQ) in attaining success in their lives and careers. As individuals our success and the success of the profession today depend on our ability to read other people’s signals and react appropriately to them. Therefore, each one of us must develop the mature emotional intelligence skills required to better understand, empathize and negotiate with other people — particularly as the economy has become more global. Otherwise, success will elude us in our lives and careers. “Your EQ is the level of your ability to understand other people, what motivates them and how to work cooperatively with them,” says Howard Gardner, the influential Harvard theorist. Five major categories of emotional intelligence skills are recognized by researchers in this area. Understanding the Five Categories of Emotional Intelligence (EQ) 1. Self-awareness. The ability to recognize an emotion as it “happens” is the key to your EQ. Developing self-awareness requires tuning in to your true feelings. If you evaluate your emotions, you can manage them. The major elements of self-awareness are: § Emotional awareness. Your ability to recognize your own emotions and their effects. § Self-confidence. Sureness about your self-worth and capabilities. 2. Self-regulation. You often have little control over when you experience emotions. You can, however, have some say in how long an emotion will last by using a number of techniques to alleviate negative emotions such as anger, anxiety or depression. -
UNDERSTANDING DEPRESSION Managing Your Emotions
UNDERSTANDING DEPRESSION Managing Your Emotions STUDENT WELLNESS CENTRE ■ What are Emotions? ■ Effectively Managing Anger ■ What is Emotional Intelligence? ■ Effectively Managing Grief ■ Identifying Feelings ■ Managing Mood Shifts ■ Coping with Strong Emotion What Are Emotions? Emotions are a natural and healthy part of being human. In fact, they are vital to survival. Emotions motivate us, help us to adapt to our environment, prioritize, connect with others, and focus on finding solutions to problems. An emotion is a complex psychological event that involves a mixture of at least three reactions: ■ A physiological response: such as a change in heart rate, muscles tension, blood pressure and respiration rate. ■ A subjective experience: internal thoughts and feelings about the response. This includes what you tell yourself, and how you label the experience (e.g., “good” or “bad”). ■ An expressive reaction: such as a distinctive facial expression or body posture. Because culture plays an important role here, this may include the learned or habitual reactions that you associate with the emotion. The experience of emotions is subjective. Nobody truly knows how another person experiences an emotion. Some emotions are experienced as strong and others as a mild. What you tell yourself about an emotion is also an important part of how you experience it. Similarly, what others tell you, and how the world around you handles and labels emotions is an important aspect of your experience. People vary greatly in their overall general level of emotional reactivity. A person who is “less reactive” might generally be calm, easy going, and take a slow pace. A person who is “more reactive” may be excitable, have stronger reactions to experiences and go at a faster pace. -
Emotion Perception in Habitual Players of Action Video Games Swann Pichon, Benoit Bediou, Lia Antico, Rachael Jack, Oliver Garrod, Chris Sims, C
Emotion Emotion Perception in Habitual Players of Action Video Games Swann Pichon, Benoit Bediou, Lia Antico, Rachael Jack, Oliver Garrod, Chris Sims, C. Shawn Green, Philippe Schyns, and Daphne Bavelier Online First Publication, July 6, 2020. http://dx.doi.org/10.1037/emo0000740 CITATION Pichon, S., Bediou, B., Antico, L., Jack, R., Garrod, O., Sims, C., Green, C. S., Schyns, P., & Bavelier, D. (2020, July 6). Emotion Perception in Habitual Players of Action Video Games. Emotion. Advance online publication. http://dx.doi.org/10.1037/emo0000740 Emotion © 2020 American Psychological Association 2020, Vol. 2, No. 999, 000 ISSN: 1528-3542 http://dx.doi.org/10.1037/emo0000740 Emotion Perception in Habitual Players of Action Video Games Swann Pichon, Benoit Bediou, and Lia Antico Rachael Jack and Oliver Garrod University of Geneva, Campus Biotech Glasgow University Chris Sims C. Shawn Green Rensselaer Polytechnic Institute University of Wisconsin–Madison Philippe Schyns Daphne Bavelier Glasgow University University of Geneva, Campus Biotech Action video game players (AVGPs) display superior performance in various aspects of cognition, especially in perception and top-down attention. The existing literature has examined these performance almost exclusively with stimuli and tasks devoid of any emotional content. Thus, whether the superior performance documented in the cognitive domain extend to the emotional domain remains unknown. We present 2 cross-sectional studies contrasting AVGPs and nonvideo game players (NVGPs) in their ability to perceive facial emotions. Under an enhanced perception account, AVGPs should outperform NVGPs when processing facial emotion. Yet, alternative accounts exist. For instance, under some social accounts, exposure to action video games, which often contain violence, may lower sensitivity for empathy-related expressions such as sadness, happiness, and pain while increasing sensitivity to aggression signals. -
How Multidimensional Is Emotional Intelligence? Bifactor Modeling of Global and Broad Emotional Abilities of the Geneva Emotional Competence Test
Journal of Intelligence Article How Multidimensional Is Emotional Intelligence? Bifactor Modeling of Global and Broad Emotional Abilities of the Geneva Emotional Competence Test Daniel V. Simonet 1,*, Katherine E. Miller 2 , Kevin L. Askew 1, Kenneth E. Sumner 1, Marcello Mortillaro 3 and Katja Schlegel 4 1 Department of Psychology, Montclair State University, Montclair, NJ 07043, USA; [email protected] (K.L.A.); [email protected] (K.E.S.) 2 Mental Illness Research, Education and Clinical Center, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA 19104, USA; [email protected] 3 Swiss Center for Affective Sciences, University of Geneva, 1205 Geneva, Switzerland; [email protected] 4 Institute of Psychology, University of Bern, 3012 Bern, Switzerland; [email protected] * Correspondence: [email protected] Abstract: Drawing upon multidimensional theories of intelligence, the current paper evaluates if the Geneva Emotional Competence Test (GECo) fits within a higher-order intelligence space and if emotional intelligence (EI) branches predict distinct criteria related to adjustment and motivation. Using a combination of classical and S-1 bifactor models, we find that (a) a first-order oblique and bifactor model provide excellent and comparably fitting representation of an EI structure with self-regulatory skills operating independent of general ability, (b) residualized EI abilities uniquely Citation: Simonet, Daniel V., predict criteria over general cognitive ability as referenced by fluid intelligence, and (c) emotion Katherine E. Miller, Kevin L. Askew, recognition and regulation incrementally predict grade point average (GPA) and affective engagement Kenneth E. Sumner, Marcello Mortillaro, and Katja Schlegel. 2021. in opposing directions, after controlling for fluid general ability and the Big Five personality traits. -
Emotion Classification Using Physiological Signals
Emotion Classification Using Physiological Signals Byoung-Jun Park1, Eun-Hye Jang1, Myoung Ae Chung1, Sang-Hyeob Kim1*, Jin Hun Sohn2* 1IT Convergence Technology Research Laboratory, Electronics and Telecommunications Research Institute, Daejeon, 305-700 2Department of Psychology/Brain Research Institute, Chungnam National University, Daejeon, 305-765 ABSTRACT Objective: The aim of this study is to discriminate negative emotions, such as sadness, fear, surprise, and stress using physiological signals. Background: Recently, the main topic of emotion classification research is to recognize human’s feeling or emotion using various physiological signals. It is one of the core processes to implement emotional intelligence in human computer interaction (HCI) research. Method: Electrodermal activity (EDA), electrocardiogram (ECG), skin temperature (SKT), and photoplethysmography (PPG) are recorded and analyzed as physiological signals. And emotional stimuli are audio-visual film clips which have examined for their appropriateness and effectiveness through preliminary experiment. For classification of negative emotions, five machine learning algorithms, i.e., LDF, CART, SOM, and Naïve Bayes are used. Results: Result of emotion classification shows that an accuracy of emotion classification by CART (84.0%) was the highest and by LDA (50.7%) was the lowest. SOM showed emotion classification accuracy of 51.2% and Naïve Bayes was 76.2%. Conclusion: We could identify that CART was the optimal emotion classification algorithm for classifying 4 negative emotions (sadness, fear, surprise, and stress). Application: This result can be helpful to provide the basis for the emotion recognition technique in HCI. Keywords: Emotion classification, Negative emotion, Machine learning algorithm, Physiological signal 1. Introduction Nasoz, Alvarez, Lisetti, and Finkelstein, 2003). -
Resilience, Character Strengths and Flourishing: a Positive Education Workshop for Singapore Teachers
University of Pennsylvania ScholarlyCommons Master of Applied Positive Psychology (MAPP) Master of Applied Positive Psychology (MAPP) Capstone Projects Capstones 8-1-2011 Resilience, Character Strengths and Flourishing: A Positive Education Workshop for Singapore Teachers Sha-En Yeo [email protected] Follow this and additional works at: https://repository.upenn.edu/mapp_capstone Part of the Junior High, Intermediate, Middle School Education and Teaching Commons, Other Psychology Commons, and the Secondary Education and Teaching Commons Yeo, Sha-En, "Resilience, Character Strengths and Flourishing: A Positive Education Workshop for Singapore Teachers" (2011). Master of Applied Positive Psychology (MAPP) Capstone Projects. 25. https://repository.upenn.edu/mapp_capstone/25 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/mapp_capstone/25 For more information, please contact [email protected]. Resilience, Character Strengths and Flourishing: A Positive Education Workshop for Singapore Teachers Abstract Positive education, or teaching the skills of well-being through direct instruction and the curriculum, aims to teach children the skills to build resilience, capitalize on strengths and systematically build the pillars for a flourishing life. Positive education can succeed amidst a supportive school environment and well- equipped teachers that inculcate the right values and character. Given that school-going children spend more than fifty percent of their time in school, it is thus imperative that teachers be trained with the skills of well-being. This paper provides an introduction to positive psychology (the foundation for positive education), describes the need for positive education in Singapore schools and proposes a workshop to equip secondary/high-school teachers with the skills and knowledge of resilience, character strengths and a flourishing life – the elements of which are summarized as PERMA (positive emotions, engagement, relationships, meaning & achievement) (Seligman, 2011). -
1 Automated Face Analysis for Affective Computing Jeffrey F. Cohn & Fernando De La Torre Abstract Facial Expression
Please do not quote. In press, Handbook of affective computing. New York, NY: Oxford Automated Face Analysis for Affective Computing Jeffrey F. Cohn & Fernando De la Torre Abstract Facial expression communicates emotion, intention, and physical state, and regulates interpersonal behavior. Automated Face Analysis (AFA) for detection, synthesis, and understanding of facial expression is a vital focus of basic research. While open research questions remain, the field has become sufficiently mature to support initial applications in a variety of areas. We review 1) human-observer based approaches to measurement that inform AFA; 2) advances in face detection and tracking, feature extraction, registration, and supervised learning; and 3) applications in action unit and intensity detection, physical pain, psychological distress and depression, detection of deception, interpersonal coordination, expression transfer, and other applications. We consider user-in-the-loop as well as fully automated systems and discuss open questions in basic and applied research. Keywords Automated Face Analysis and Synthesis, Facial Action Coding System (FACS), Continuous Measurement, Emotion, Nonverbal Communication, Synchrony 1. Introduction The face conveys information about a person’s age, sex, background, and identity, what they are feeling, or thinking (Darwin, 1872/1998; Ekman & Rosenberg, 2005). Facial expression regulates face-to-face interactions, indicates reciprocity and interpersonal attraction or repulsion, and enables inter-subjectivity between members of different cultures (Bråten, 2006; Fridlund, 1994; Tronick, 1989). Facial expression reveals comparative evolution, social and emotional development, neurological and psychiatric functioning, and personality processes (Burrows & Cohn, In press; Campos, Barrett, Lamb, Goldsmith, & Stenberg, 1983; Girard, Cohn, Mahoor, Mavadati, & Rosenwald, 2013; Schmidt & Cohn, 2001). Not surprisingly, the face has been of keen interest to behavioral scientists. -
A Review of Alexithymia and Emotion Perception in Music, Odor, Taste, and Touch
MINI REVIEW published: 30 July 2021 doi: 10.3389/fpsyg.2021.707599 Beyond Face and Voice: A Review of Alexithymia and Emotion Perception in Music, Odor, Taste, and Touch Thomas Suslow* and Anette Kersting Department of Psychosomatic Medicine and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany Alexithymia is a clinically relevant personality trait characterized by deficits in recognizing and verbalizing one’s emotions. It has been shown that alexithymia is related to an impaired perception of external emotional stimuli, but previous research focused on emotion perception from faces and voices. Since sensory modalities represent rather distinct input channels it is important to know whether alexithymia also affects emotion perception in other modalities and expressive domains. The objective of our review was to summarize and systematically assess the literature on the impact of alexithymia on the perception of emotional (or hedonic) stimuli in music, odor, taste, and touch. Eleven relevant studies were identified. On the basis of the reviewed research, it can be preliminary concluded that alexithymia might be associated with deficits Edited by: in the perception of primarily negative but also positive emotions in music and a Mathias Weymar, University of Potsdam, Germany reduced perception of aversive taste. The data available on olfaction and touch are Reviewed by: inconsistent or ambiguous and do not allow to draw conclusions. Future investigations Khatereh Borhani, would benefit from a multimethod assessment of alexithymia and control of negative Shahid Beheshti University, Iran Kristen Paula Morie, affect. Multimodal research seems necessary to advance our understanding of emotion Yale University, United States perception deficits in alexithymia and clarify the contribution of modality-specific and Jan Terock, supramodal processing impairments. -
The Empathy Connection
The Empathy Connection Creating Caring Communities through the Human-Animal Relationship The Doris Day Animal Foundation (DDAF) is a national nonprofit organization working to create caring communities. Thanks to a generous grant from the Claire Giannini Fund, we are pleased to present “The Empathy Connection,” a publication designed to help parents, teachers, and other adults instill the important skill of empathy in our youth. As a mother of two school-age children, president of the parent teacher’s association of a middle school, and as the Executive Director of the Doris Day Animal Foundation, I know how important empathy is in children’s development. Empathy is an important skill, related to success in many areas of development—social, academic, and personal. Learning how to respond empathetically is also the best antidote to violence, bullying, and other unwanted, aggressive behavior in children. The basic tenet of DDAF’s “creating caring communities” mission is that the protection of, and respect for, animals is closely linked to human welfare. The development of empathy is a case in point: one of the best—and probably one of the most enjoyable—ways to teach children empathy is through the human-animal relationship. The Doris Day Animal Foundation offers training workshops and materials designed to help professional and lay communities address the problem of violence and promote positive development in children, families, and communities. We do this by demonstrating how paying attention to the animal-human welfare link builds safer, more creative communities for all living creatures. We hope you will let us know how you used “The Empathy Connection,” or other DDAF materials. -
Positive Psychology
7 WAYS TO APPLY POSITIVE PSYCHOLOGY Learn practical, proven strategies to live a happier, more engaged and more meaningful life. We all want to live happier, more engaging and more meaningful lives. The science of positive psychology contributes new Introduction insights and proven strategies to increase wellbeing in individuals, workplaces and communities. After years classifying and repairing the worst of human experience, positive psychology emerged to help us flourish and learn from the best. This rich and varied field now spans many areas, building on philosophies and practices from Aristotle to Maslow. This eBook introduces you to some of the most practical and research-backed ways to apply positive psychology to increase happiness, wellbeing and effectiveness—in your life, at work, at home and with the people you care for, help and lead. You will learn: • How to maximise the power of positivity to create sustainable pathways to happiness and success. • Seven positive psychology practices - “[Positive Psychology is] the from optimism to mindfullness. scientific study of positive • Tips to apply these practices at work, at human functioning and home and when helping people. flourishing on multiple levels.” We look forward to inspiring you and others to live a Martin Seligman &Mihaly Csikszentmihalyi happier, more engaged and fulfilling life! The Langley Group team © 2015 Langley Group. All rights reserved 2 Positive psychology 7 POSITIVE PRACTICES Positive emotion 1 Generating positive emotions helps broaden and build our resources and moves us toward greater wellbeing. Spearheaded by Martin Seligman and Mindset Mihaly Csikszentmihalyi in 1998, positive 2 psychology focuses on exploring and Adopting a positive attitude and Growth Mindset enhances learning and opens our expanding what makes life worthwhile, mind to new ways to raise happiness levels. -
Emotion Classification Based on Biophysical Signals and Machine Learning Techniques
S S symmetry Article Emotion Classification Based on Biophysical Signals and Machine Learning Techniques Oana Bălan 1,* , Gabriela Moise 2 , Livia Petrescu 3 , Alin Moldoveanu 1 , Marius Leordeanu 1 and Florica Moldoveanu 1 1 Faculty of Automatic Control and Computers, University POLITEHNICA of Bucharest, Bucharest 060042, Romania; [email protected] (A.M.); [email protected] (M.L.); fl[email protected] (F.M.) 2 Department of Computer Science, Information Technology, Mathematics and Physics (ITIMF), Petroleum-Gas University of Ploiesti, Ploiesti 100680, Romania; [email protected] 3 Faculty of Biology, University of Bucharest, Bucharest 030014, Romania; [email protected] * Correspondence: [email protected]; Tel.: +40722276571 Received: 12 November 2019; Accepted: 18 December 2019; Published: 20 December 2019 Abstract: Emotions constitute an indispensable component of our everyday life. They consist of conscious mental reactions towards objects or situations and are associated with various physiological, behavioral, and cognitive changes. In this paper, we propose a comparative analysis between different machine learning and deep learning techniques, with and without feature selection, for binarily classifying the six basic emotions, namely anger, disgust, fear, joy, sadness, and surprise, into two symmetrical categorical classes (emotion and no emotion), using the physiological recordings and subjective ratings of valence, arousal, and dominance from the DEAP (Dataset for Emotion Analysis using EEG, Physiological and Video Signals) database. The results showed that the maximum classification accuracies for each emotion were: anger: 98.02%, joy:100%, surprise: 96%, disgust: 95%, fear: 90.75%, and sadness: 90.08%. In the case of four emotions (anger, disgust, fear, and sadness), the classification accuracies were higher without feature selection.