Interaction design and emotional wellbeing

The World Health Organisation has concluded that emotional wellbeing is fundamental to our quality of life. It enables us to experience life as meaningful and is an essential component of social cohesion, peace and stability in the living environment [21]. This workshop will bring together a diverse community to consolidate existing knowledge and identify new opportunities for research on technologies designed to support emotional wellbeing. The workshop will examine uses of technology in mental health settings, but will also consider the importance of emotional needs in physical healthcare and wellbeing more generally. The design of technology to provide social support and to extend traditional care networks will be key workshop themes

The Relationship Between Reasoning, And Emotional Intelligence In Social Interaction With Mathematics Achievement

The objectives of this research are to determine the relationship between reasoning, and emotional intelligence in social interaction with mathematics achievement. The survey was conducted at SLTP 5 Yogyakarta, Indonesia with 90 respondents selected by random sampling. The study reveals that there are positive relationship between: (a) reasoning and mathematics achievement; (b) emotional intelligence in social interaction and mathematics achievement. Together, there is a positive relationship between reasoning, and emotional intelligence in the social interaction with mathematics achievement. Key words : Emotional Intelligence, Mathematics Achievemen

Towards the improvement of self-service systems via emotional virtual agents

Affective computing and emotional agents have been found to have a positive effect on human-computer interactions. In order to develop an acceptable emotional agent for use in a self-service interaction, two stages of research were identified and carried out; the first to determine which facial expressions are present in such an interaction and the second to determine which emotional agent behaviours are perceived as appropriate during a problematic self-service shopping task. In the first stage, facial expressions associated with negative affect were found to occur during self-service shopping interactions, indicating that facial expression detection is suitable for detecting negative affective states during self-service interactions. In the second stage, user perceptions of the emotional facial expressions displayed by an emotional agent during a problematic self-service interaction were gathered. Overall, the expression of disgust was found to be perceived as inappropriate while emotionally neutral behaviour was perceived as appropriate, however gender differences suggested that females perceived surprise as inappropriate. Results suggest that agents should change their behaviour and appearance based on user characteristics such as gender

Sex differences in emotional evaluation of film clips: interaction with five high arousal emotional categories

The present study aimed to investigate gender differences in the emotional evaluation of 18 film clips divided into six categories: Erotic, Scenery, Neutral, Sadness, Compassion, and Fear. 41 female and 40 male students rated all clips for valence-pleasantness, arousal, level of elicited distress, anxiety, jittery feelings, excitation, and embarrassment. Analysis of positive films revealed higher levels of arousal, pleasantness, and excitation to the Scenery clips in both genders, but lower pleasantness and greater embarrassment in women compared to men to Erotic clips. Concerning unpleasant stimuli, unlike men, women reported more unpleasantness to the Compassion, Sadness, and Fear compared to the Neutral clips and rated them also as more arousing than did men. They further differentiated the films by perceiving greater arousal to Fear than to Compassion clips. Women rated the Sadness and Fear clips with greater Distress and Jittery feelings than men did. Correlation analysis between arousal and the other emotional scales revealed that, although men looked less aroused than women to all unpleasant clips, they also showed a larger variance in their emotional responses as indicated by the high number of correlations and their relatively greater extent, an outcome pointing to a masked larger sensitivity of part of male sample to emotional clips. We propose a new perspective in which gender difference in emotional responses can be better evidenced by means of film clips selected and clustered in more homogeneous categories, controlled for arousal levels, as well as evaluated through a number of emotion focused adjectives

Improving Student’s Emotional Intelligence By Mathematics Learning

This paper aims to provide a description of realistic mathematics education in improving emotional intelligence. Mathematics is a tool that can be developed to foster thinking (reasoning) and attitudes (emotions) (Nelissen, 2007). Emotional intelligence is the ability to feel, understand and effectively apply the power and emotional sensitivity as an energy source and as a motivator. The models that emerged from students' mathematical activity can promote interaction in class, thus leading to the level of mathematical thinking and higher learning meaningful democracy. Thus, learning mathematics is a realistic learning actively involves students both physically and mentally (student centered learning), and be democratic, so as to have a better profile in the critical thinking skills and emotional intelligence of students. Keywords: emotional intelligence, learning, mathematics, constructive, interactive, reflective, realisti

Anatomy and computational modeling of networks underlying cognitive-emotional interaction

The classical dichotomy between cognition and emotion equated the first with rationality or logic and the second with irrational behaviors. The idea that cognition and emotion are separable, antagonistic forces competing for dominance of mind has been hard to displace despite abundant evidence to the contrary. For instance, it is now known that a pathological absence of emotion leads to profound impairment of decision making. Behavioral observations of this kind are corroborated at the mechanistic level: neuroanatomical studies reveal that brain areas typically described as underlying either cognitive or emotional processes are linked in ways that imply complex interactions that do not resemble a simple mutual antagonism. Instead, physiological studies and network simulations suggest that top-down signals from prefrontal cortex realize "cognitive control" in part by either suppressing or promoting emotional responses controlled by the amygdala, in a way that facilitates adaptation to changing task demands. Behavioral, anatomical, and physiological data suggest that emotion and cognition are equal partners in enabling a continuum or matrix of flexible behaviors that are subserved by multiple brain regions acting in concert. Here we focus on neuroanatomical data that highlight circuitry that structures cognitive-emotional interactions by directly or indirectly linking prefrontal areas with the amygdala. We also present an initial computational circuit model, based on anatomical, physiological, and behavioral data to explicitly frame the learning and performance mechanisms by which cognition and emotion interact to achieve flexible behavior.R01 MH057414 - NIMH NIH HHS; R01 NS024760 - NINDS NIH HH

Emotional intelligence buffers the effect of physiological arousal on dishonesty

We studied the emotional processes that allow people to balance two competing desires: benefitting from dishonesty and keeping a positive self-image. We recorded physiological arousal (skin conductance and heart rate) during a computer card game in which participants could cheat and fail to report a certain card when presented on the screen to avoid losing their money. We found that higher skin conductance corresponded to lower cheating rates. Importantly, emotional intelligence regulated this effect; participants with high emotional intelligence were less affected by their physiological reactions than those with low emotional intelligence. As a result, they were more likely to profit from dishonesty. However, no interaction emerged between heart rate and emotional intelligence. We suggest that the ability to manage and control emotions can allow people to overcome the tension between doing right or wrong and license them to bend the rules

Emotional persistence in online chatting communities

How do users behave in online chatrooms, where they instantaneously read and write posts? We analyzed about 2.5 million posts covering various topics in Internet relay channels, and found that user activity patterns follow known power-law and stretched exponential distributions, indicating that online chat activity is not different from other forms of communication. Analysing the emotional expressions (positive, negative, neutral) of users, we revealed a remarkable persistence both for individual users and channels. I.e. despite their anonymity, users tend to follow social norms in repeated interactions in online chats, which results in a specific emotional "tone" of the channels. We provide an agent-based model of emotional interaction, which recovers qualitatively both the activity patterns in chatrooms and the emotional persistence of users and channels. While our assumptions about agent's emotional expressions are rooted in psychology, the model allows to test different hypothesis regarding their emotional impact in online communication.Comment: 34 pages, 4 main and 12 supplementary figure

Getting the feel of therapy : understanding therapists' views and experiences regarding social-emotional skills in practice : a thesis presented in partial fulfilment of the requirements for the degree of Doctorate in Clinical Psychology at Massey University, Albany, New Zealand

Emotions are arguably at the heart of psychotherapy. While clients’ emotions in therapy have received a great deal of research attention, outside the realm of psychoanalytic and psychodynamic research, therapists’ emotions have largely been neglected. When applied to therapy, the concept of social-emotional skills describes therapists’ ability to be aware of their own and their clients’ emotions and then draw on that information to manage those emotions and in turn, the therapeutic interaction. As therapists’ social-emotional skills are a relatively new area of enquiry, this qualitative study sought to contribute to the literature by exploring therapists’ views and experiences regarding social-emotional skills in practice. Semi-structured interviews were carried out with ten practicing therapist participants between the ages of 31 and 62. Using Thematic Analysis, The Centrality of Emotions in Therapy was determined as a meta-theme and this was further organised into four main themes; Emotional Principles, Emotional Awareness Strategies, Emotional Practices as well as the Learning and Training of Social- Emotional Skills. The findings were visually represented using ‘The Tree of Therapists’ Social-Emotional Interactions’ model. Implications of the findings, limitations of the current study and future research directions are discussed

Spoken affect classification : algorithms and experimental implementation : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University, Palmerston North, New Zealand

Machine-based emotional intelligence is a requirement for natural interaction between humans and computer interfaces and a basic level of accurate emotion perception is needed for computer systems to respond adequately to human emotion. Humans convey emotional information both intentionally and unintentionally via speech patterns. These vocal patterns are perceived and understood by listeners during conversation. This research aims to improve the automatic perception of vocal emotion in two ways. First, we compare two emotional speech data sources: natural, spontaneous emotional speech and acted or portrayed emotional speech. This comparison demonstrates the advantages and disadvantages of both acquisition methods and how these methods affect the end application of vocal emotion recognition. Second, we look at two classification methods which have gone unexplored in this field: stacked generalisation and unweighted vote. We show how these techniques can yield an improvement over traditional classification methods