Search results for: learning emotion

Authors: Tomasz Sapiński, Dorota Kamińska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari

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People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.

Keywords: body movement, emotion recognition, emotional corpus, facial expressions, gestures, multimodal database, speech

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Authors: Neha Singh, Ananya Arora

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Facial expression measurement plays a crucial role in the identification of emotion. Facial expression plays a key role in psychophysiology, neural bases, and emotional disorder, to name a few. The Facial Action Coding System (FACS) has proven to be the most efficient and widely used of the various systems used to describe facial expressions. Coders can manually code facial expressions with FACS and, by viewing video-recorded facial behaviour at a specified frame rate and slow motion, can decompose into action units (AUs). Action units are the most minor visually discriminable facial movements. FACS explicitly differentiates between facial actions and inferences about what the actions mean. Action units are the fundamental unit of FACS methodology. It is regarded as the standard measure for facial behaviour and finds its application in various fields of study beyond emotion science. These include facial neuromuscular disorders, neuroscience, computer vision, computer graphics and animation, and face encoding for digital processing. This paper discusses the conceptual basis for FACS, a numerical listing of discrete facial movements identified by the system, the system's psychometric evaluation, and the software's recommended training requirements.

Keywords: facial action, action units, coding, machine learning

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Authors: Selin Kara-Bahçekapılı, Bengisu Nehir Aydın

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Objective: In this study, it is aimed to examine the relationship between childhood traumas (overprotection-control, emotional/physical/sexual abuse, emotional/physical neglect), age, emotional regulation difficulties, and the tendency of violence in adults. In the study, the direct and indirect effects of 6 sub-factors of childhood traumas, emotion regulation difficulties, and age on tendency to violence are evaluated on a model that theoretically reveals. Method: The population of this cross-sectional study consists of individuals between the ages of 18-65 living in Turkey. The data from 527 participants were obtained by online surveys and convenience sampling method within the scope of the study. As a result of exclusion criteria and then outlier data analysis, the data of 443 participants were included in the analysis. Data were collected by demographic information form, childhood trauma scale, emotion regulation difficulty scale, and violence tendency scale. Research data were analyzed by SPSS and AMOS using correlation, path analysis, direct and indirect effects. Results: According to the research findings, the variables in the model explained 28.2% of the variance of the mean scores of the individuals' tendency to violence. Emotion regulation difficulties have the most direct effect on the tendency to violence (d=.387; p<.01). The effects of excessive protection and control, emotional neglect, and physical neglect variables on the tendency to violence are not significant. When the significant and indirect effects of the variables on tendency to violence over emotion regulation difficulties are examined, age has a negative effect, emotional neglect has a positive effect, emotional abuse has a positive effect, and overprotection-control has a positive effect. The indirect effects of sexual abuse, physical neglect, and physical abuse on tendency to violence are not significant. Childhood traumas and age variables in the model explained 24.1% of the variance of the mean scores of the individuals’ emotion regulation difficulties. The variable that most affects emotion regulation difficulties is age (d=-.268; p<.001). The direct effects of sexual abuse, physical neglect, and physical abuse on emotion regulation difficulties are not significant. Conclusion: The results of the research emphasize the critical role of difficulty in emotion regulation on the tendency to violence. Difficulty in emotion regulation affects the tendency to violence both directly and by mediating different variables. In addition, it is seen that some sub-factors of childhood traumas have direct and/or indirect effects on the tendency to violence. Emotional abuse and age have both direct and indirect effects on the tendency to violence over emotion regulation difficulties.

Keywords: childhood trauma, emotion regulation difficulties, tendency to violence, path analysis

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Tang, Yun-Chia, Chiu, Hung-Chang

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Authenticity in advertising, is the cornerstone of modern marketing. Despite research advances related to the role of authenticity in marketing, it remains unclear why customers respond to authentic brand stories. This study shows that different personality traits moderate the influence of various types of authenticity on people’s levels of emotion. Both indexical and iconic authenticity advertising evoke more positive emotions among extroverts and open and agreeable people. When neurotic people and conscientious people read iconic authenticity advertisements, rather than indexical authenticity ones, they produce more negative emotions. The emotion evoked by advertising in turn has a positive impact on brand attitude. These findings provide managerial implications and directions for practitioners.

Keywords: advertising, authenticity, emotion, personality traits

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Authors: Yungeng Xie, Cong Liu, Yi Liu, Xuanao Wan

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The study aims to explore microblog users’ emotion expression and sharing behaviors on the Chinese microblog (Weibo). The first theme of study analyzed whether microblog emotions impact readers’ message sharing behaviors, specifically, how the strength of emotion (positive and negative) in microblog messages facilitate/inhibit readers’ sharing behaviors. The second theme compared the differences among the three types of microblog users (i.e., verified enterprise users, verified individual users and unverified users) in terms of their profiles and microblog behaviors. A total of 7114 microblog messages about 24 hot public events in China were sampled from Sina Weibo. The first study results show that strength of negative emotions that microblog messages carry significantly increase the possibility of the message being shared. The second study results indicate that there are significant differences across the three types of users in terms of their emotion expression and its influence on microblog behaviors.

Keywords: emotion expression, information diffusion, microblog, sharing

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Authors: Pacharaporn Lekyan

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The purpose of this study is to explore the conflict management affecting the workplace and analyze the ability of the prediction of leadership of the headman and the methods to handle the conflict in an organization. The quantitative research and developed the questionnaire in order to collect information from the respondents from 200 samples from leader or manager who worked in frozen food factories in Thailand. The result analysis shows about the problem of the relationship between conflict management factors, leadership, and the confliction in organization. The emotion of the leader in the organization is not the only factor that can affect conflict management but also the emotion of surrounding people which this factor can happen all the time and shows that four out of five factors of interpersonal conflict management have affected on emotion intelligence and also shows that the behaviors of leadership have an influence on conflict management.

Keywords: conflict management, emotional intelligence, leadership, factories' employee

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Authors: A. N. Paithane, D. S. Bormane, S. D. Shirbahadurkar

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It has been seen that emotion recognition is an important research topic in the field of Human and computer interface. A novel technique for Feature Extraction (FE) has been presented here, further a new method has been used for human emotion recognition which is based on HHT method. This method is feasible for analyzing the nonlinear and non-stationary signals. Each signal has been decomposed into the IMF using the EMD. These functions are used to extract the features using fission and fusion process. The decomposition technique which we adopt is a new technique for adaptively decomposing signals. In this perspective, we have reported here potential usefulness of EMD based techniques.We evaluated the algorithm on Augsburg University Database; the manually annotated database.

Keywords: intrinsic mode function (IMF), Hilbert-Huang transform (HHT), empirical mode decomposition (EMD), emotion detection, electrocardiogram (ECG)

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Authors: Sofia Nilsson, Alicia Ohlsson, Linda-Marie Lundqvist, Aida Alvinius, Peder Hyllengren, Gerry Larsson

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In irregular warfare contexts, military personnel are often presented with morally ambiguous situations where they are aware of the morally correct choice but may feel prevented to follow through with it due to organizational demands. Moral stress and/or injury can be the outcome of the individual’s experienced dissonance. These types of challenges put a large demand on the individual to manage their own emotions and the emotions of others, particularly in the case of a leader. Both the ability and inability for emotional regulation can result in different combinations of short and long term reactions after morally stressful events, which can be either positive or negative. Our study analyzed the combination of these reactions based upon the types of morally challenging events that were described by the subjects. 1)What institutionalized norms concerning emotion regulation are favorable in short-and long-term perspectives after a morally stressful event? 2)What individual emotion-focused coping strategies are favorable in short-and long-perspectives after a morally stressful? To address these questions, we conducted a quantitative study in military contexts in Sweden and Norway on upcoming or current military officers (n=331). We tested a theoretical model built upon a recently developed qualitative study. The data was analyzed using factor analysis, multiple regression analysis and subgroup analyses. The results indicated that an individual’s restriction of emotion in order to achieve an organizational goal, which results in emotional dissonance, can be an effective short term strategy for both the individual and the organization; however, it appears to be unfavorable in a long-term perspective which can result in negative reactions. Our results are intriguing because they showed an increased percentage of reported negative long term reactions (13%), which indicated PTSD-related symptoms in comparison to previous Swedish studies which indicated lower PTSD symptomology.

Keywords: emotion culture, emotion coping, emotion management, military

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Authors: Aliyah Dosani, Kerri Alderson

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Two different simulations using standardized patients were developed to reinforce content and foster undergraduate nursing students’ practice and development of interpersonal skills in difficult clinical situations in the classroom. The live actor simulations focused on fostering interpersonal skills, traditionally considered by students to be simple and easy. However, seemingly straightforward interactions can be very stressful, particularly in women’s complex social/emotional situations. Supporting patients in these contexts is fraught with complexity and high emotion, requiring skillful support, assessment and intervention by a registered nurse. In this presentation, the personal and professional perspectives of the development, incorporation, and execution of the live actor simulations will be discussed, as well as the inclusion of student perceptions, and the learning gained by the involved faculty.

Keywords: adult learning, interpersonal skill development, simulation learning, teaching and learning

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Authors: Sakkaphat T. Ngamake, Arunya Tuicomepee, Panrapee Suttiwan, Rewadee Watakakosol, Sompoch Iamsupasit

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Generally, 'positive' emotion regulation strategies such as cognitive reappraisal have linked to desirable outcomes while 'negative' strategies such as behavioral suppression have linked to undesirable outcomes. These trends have been found in both the elderly and professional practitioners. Hence, this study sought to investigate these trends further by examining the relationship between two dominant emotion regulation strategies in the literature (i.e., cognitive reappraisal and behavioral suppression) and well-being outcomes among the elderly (i.e., successful aging) and their caregivers (i.e., satisfaction with life), using the actor-partner interdependence model. A total of 150 elderly-caregiver dyads participated in the study. The elderly responded to two measures assessing the two emotion regulation strategies and successful aging while their caregivers responded to the same emotion regulation measure and a measure of satisfaction with life. Two criterion variables (i.e., successful aging and satisfaction with life) were specified as latent variables whereas four predictors (i.e., two strategies for the elderly and two strategies for their caregivers) were specified as observed variables in the model. Results have shown that, for the actor effect, the cognitive reappraisal strategy yielded positive relationships with the well-being outcomes for both the elderly and their caregivers. For the partner effect, a positive relationship between caregivers’ cognitive reappraisal strategy and the elderly’s successful aging was observed. The behavioral suppression strategy has not related to any well-being outcomes, within and across individual agents. This study has contributed to the literature by empirically showing that the mental activity of the elderly’s immediate environment such as their family members or close friends could affect their quality of life.

Keywords: emotion regulation, caregiver, older adult, well-being

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Authors: Jadisha Cornejo, Helio Pedrini

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Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Esther Burkitt

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Background: Evidence is mounting that mixed emotions can be experienced simultaneously in different ways across the lifespan. Four types of patterns of simultaneously mixed emotions (sequential, prevalent, highly parallel, and inverse types) have been identified in middle childhood and adolescence. Moreover, the recognition of these experiences tends to develop firstly when children consider peers rather than the self. This evidence from children and adolescents is based on examining the presence of experiences specified in adulthood. The present study, therefore, applied an exhaustive coding scheme to investigate whether children experience types of previously unidentified simultaneous mixed emotional experiences. Methodology: One hundred and twenty children (60 girls) aged 7 years 1 month - 9 years 2 months (X=8 years 1 month; SD = 10 months) were recruited from mainstream schools across the UK. Two age groups were formed (youngest, n = 61, 7 years 1 month- 8 years 1 months: oldest, n = 59, 8 years 2 months – 9 years 2 months) and allocated to one of two conditions hearing vignettes describing happy and sad mixed emotion events in age and gender-matched protagonist or themselves. Results: Loglinear analyses identified new types of flexuous, vertical, and other experiences along with established sequential, prevalent, highly parallel, and inverse types of experience. Older children recognised more complex experiences other than the self-condition. Conclusion: Several additional types of simultaneously mixed emotions are recognised in middle childhood. The theoretical relevance of simultaneous mixed emotion processing in childhood is considered, and the potential utility of the findings in emotion assessments is discussed.

Keywords: emotion, childhood, self, other

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms

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Authors: Hossein Ilanloo, Sedigheh Ahmadi, Kianoosh Zahrakar

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The present study aims at investigating the effectiveness of group counseling of mindfulness-based cognitive therapy on cognitive emotion regulation in high school students. The research design was quasi-experimental and pre-test-post-test type and a two-month follow-up with a control group. The statistical population of the study consisted of all-male high school students in Takestan city in the Academic Year 2020-2021. The sample comprised 30 high school male students selected through the convenience sampling method and randomly assigned to experimental (n=15) and control (n=15) groups. The experimental group then received ten sessions of 90-minute group counseling of mindfulness-based cognitive therapy, and the control group did not receive any intervention. In order to collect data, the author used the Cognitive Emotion Regulation Questionnaire (CERQ). The researcher also used multivariate analysis of covariance, repeated measures, LSD post hoc test, and SPSS-26 software for data analysis.

Keywords: mindfulness-based cognitive therapy, cognitive emotion regulation, students, high schools

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Authors: Pui-Lai To, Yi-Jing Tsai

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As the advance of e-commerce technologies, the consumers buying behavior have changed. The focus on consumer buying behavior has already shifted from physical space to the cyberspace, which impulse buying is a major issue of concern. This study examines the stimulus effect of web environment on the consumer's emotional states, and in turn, affecting the urge of impulse buying based on a stimulus-organism-response (S-O-R) theory. Website ambiance and website service quality are the two stimulus variables. The study also explores the effects and the moderator effects of contextual variables and individual characteristic variables on the web environment, the emotional states and the urge of impulse buying. A total of 328 valid questionnaires were collected. Structural equation modeling was used to test the research hypothesis. This study found that both website ambiance and website service quality have a positive effect on consumer emotion, which in turn positively affect the urge of impulse buying. Consumer’s trait of impulse buying has a positive effect on the urge of impulse buying. Consumer’s hedonic motivation has a positive effect on both emotion state and the urge of impulse buying. On the other hand, the study found that money available for the consumer would positively affect consumer's emotion state and time available for the consumer would negatively affect the relationship between website service quality and consumer emotion. The result of this study validates Internet impulse buying behavior based on the S-O-R theory. This study also suggests that having a good website atmosphere and service quality is important to influencing consumers’ emotion and increasing the likelihood of consumer purchasing. The study could serve as a basis for the future research regarding online consumer behavior.

Keywords: emotion state, impulse buying, stimulus-organism-response, the urge of impulse buying

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Authors: Bahareh Golchin, Nooshin Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: John McDowall, Crysta Derham

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Broaden and build theory of emotion describes how experiencing positive emotions, such as happiness, broadens our ‘thought-action repertoire’ leading us to be more likely to go out and act on our positive emotions. This results in the building of new relationships, resources and skills, which we can draw on in times of need throughout life. In contrast, the experience of negative emotion is thought to narrow our ‘thought-action repertoire’, leading to specific actions to aid in survival. Three experiments aimed to explore the effect of briefly presented schematic faces (happy, sad, and neutral) on attentional scope using the flanker task. Based on the broaden and build theory it was hypothesised that there would be an increase in reaction time in trials primed with a happy face due to a broadening of attention, leading to increased flanker interference. A decrease in reaction time was predicted for trials primed with a sad face, due to a narrowing of attention leading to less flanker interference. Results lended partial support to the broaden and build hypothesis, with reaction times being slower following happy primes in incongruent flanker trials. Recent research is discussed in regards to potential mediators of the relationship between emotion and attention.

Keywords: emotion, attention, broaden and build, flanker task

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Authors: Anvikshaa Bisen, Krish Makkar

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Professionals misdiagnose autism by ticking off symptoms on a checklist without questioning the causes of said symptoms, and without understanding the innate neurophysiology of the autistic brain. A dysfunctional cingulate gyrus (CG) hyperfocuses attention in the left frontal lobe (logical/analytical) with no ability to access the right frontal lobe (emotional/creative), which plays a central role in spontaneity, social behavior, and nonverbal abilities. Autistic people live in a specialized inner space that is entirely intellectual, free from emotional and social distractions. They have no innate biological way of emotionally connecting with other people. Autistic people process their emotions intellectually, a process that can take 24 hours, by which time it is too late to have felt anything. An inactive amygdala makes it impossible for autistic people to experience fear. Because they do not feel emotion, they have no emotional memories. All memories are of events that happened about which they felt no emotion at the time and feel no emotion when talking about it afterward.

Keywords: autism, Asperger, Asd, neuropsychology, neuroscience

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Authors: Jaishree Ranganathan, Poonam Rajurkar, Angelina A. Tzacheva, Zbigniew W. Ras

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In today’s world, business often depends on the customer feedback and reviews. Sentiment analysis helps identify and extract information about the sentiment or emotion of the of the topic or document. Attribute selection is a challenging problem, especially with large datasets in actionable pattern mining algorithms. Action Rule Mining is one of the methods to discover actionable patterns from data. Action Rules are rules that help describe specific actions to be made in the form of conditions that help achieve the desired outcome. The rules help to change from any undesirable or negative state to a more desirable or positive state. In this paper, we present a Lexicon based weighted scheme approach to identify emotions from customer feedback data in the area of manufacturing business. Also, we use Rough sets and explore the attribute selection method for large scale datasets. Then we apply Actionable pattern mining to extract possible emotion change recommendations. This kind of recommendations help business analyst to improve their customer service which leads to customer satisfaction and increase sales revenue.

Keywords: actionable pattern discovery, attribute selection, business data, data mining, emotion

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Authors: García López

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The Government Departments of Health have the task of informing and educating citizens about public health issues. For this, they use channels like Twitter, key in the search for health information and the propagation of content. The tweets, important in the virality of the content, may contain emotions that influence the contagion and exchange of knowledge. The goal of this study is to perform an analysis of the emotional projection of health information shared on Twitter by official American accounts: the disease control account CDCgov, National Institutes of Health, NIH, the government agency HHSGov, and the professional organization PublicHealth. For this, we used Tone Analyzer, an International Business Machines Corporation (IBM) tool specialized in emotion detection in text, corresponding to the categorical model of emotion representation. For 15 days, all tweets from these accounts were analyzed with the emotional analysis tool in text. The results showed that their tweets contain an important emotional load, a determining factor in the success of their communications. This exposes that official accounts also use subjective language and contain emotions. The predominance of emotion joy over sadness and the strong presence of emotions in their tweets stimulate the virality of content, a key in the work of informing that government health departments have.

Keywords: emotions in tweets, emotion detection in the text, health information on Twitter, American health official accounts, emotions on Twitter, emotions and content

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Authors: Mingming Jiang

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This literature review aims to offer an overview of existing research on learning analytics and learning design, the alignment between the two, and how learning analytics has been leveraged to inform learning design in higher education. Current research suggests a need to create more alignment and integration between learning analytics and learning design in order to not only ground learning analytics on learning sciences but also enable data-driven decisions in learning design to improve learning outcomes. In addition, multiple conceptual frameworks have been proposed to enhance the synergy and alignment between learning analytics and learning design. Future research should explore this synergy further in the unique context of higher education, identifying learning analytics metrics in higher education that can offer insight into learning processes, evaluating the effect of learning analytics outcomes on learning design decision-making in higher education, and designing learning environments in higher education that make the capturing and deployment of learning analytics outcomes more efficient.

Keywords: learning analytics, learning design, big data in higher education, online learning environments

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Authors: Michaela Porubanova

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In this exploratory study to examine the effects of emotional significance on change detection using the flicker paradigm, three different categories of scenes were randomly presented (neutral, positive and negative) in three different blocks. We hypothesized that because of the different effects on attention, performance in change detection tasks differs for scenes with different effective values. We found the greatest accuracy of change detection was for changes occurring in positive and negative scenes (compared with neutral scenes). Secondly and most importantly, changes in negative scenes (and also positive scenes, though not with statistical significance) were detected faster than changes in neutral scenes. Interestingly, women were less accurate than men in detecting changes in emotionally significant scenes (both negative and positive), i.e., women detected fewer changes in emotional scenes in the time limit of 40s. But on the other hand, women were quicker to detect changes in positive and negative images than men. The study makes important contributions to the area of the role of emotions on information processing. The role of emotion in attention will be discussed.

Keywords: attention, emotion, flicker task, IAPS

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Authors: Zaralyn Bernardo, Dante Boac, Annabelle Del Rosario

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Professional individuals who are in a primary role to impart learning with the new generation are alarmingly tend to have a vast decrease in their workforce due to stress at work. Thus, the study used mixed method research design to explore the ideal and actual coping patterns of college school teachers, both private and public, using Coping Response Inventory-Adult (CRI-Adult). It was suggested that in order for coping to be effective there must be a congruence or good match between coping efforts and preferred coping style. Results basically provided the same information on sources of teacher stress. However, workload and low salary were more likely heightened, for public and private school, respectively. There is also a significant difference between the ideal and actual coping style of college school teachers. Though the public school teachers leaned towards problem-focused as their ideal way of coping, both public and private teachers are somewhat inclined to use emotion-focused coping in actual situation. Results of FGD identified the factors that contribute to the incongruence or mismatch in their preferred style of coping and actual efforts to cope. Identified factors based on thematic analysis (TA) are clustered into themes such as affectivity and rehearsal of the preferred coping responses, sensitivity to pressure impairs coping efficacy, seeking for social acceptance and approval, indefinite appraisal of perceived stress, emotional dysregulation, and impulsivity, immediate desire to terminate negative emotion and adversity. Most of the factors somewhat provide partial elucidation on the engagement of the respondents on emotion-focused coping.

Keywords: coping responses subtypes, appraisal, teacher stress, ideal and actual coping

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Authors: Hyojung Shin, Munhee Kweon

Abstract:

Non-suicide Self Injuri (NSSI) can be defined as the act of an individual who does not intend to die directly and intentionally damaging his or her body tissues. According to a study conducted by the Korean Ministry of Education in 2018, the NSSI is widely spreading among teenagers, with 7.9 percent of all middle school students and 6.4 percent of high school students reporting experience in NSSI. As such, it is understood that the first time of the NSSI is in adolescence. However, the NSSI may not start and stop at a certain time, but may last longer. However, despite the widespread prevalence of NSSI among teenagers, little is known about the process and maintenance of NSSI college students on a continuous development basis. Korea's NSSI research trends are mainly focused on individual internal vulnerabilities (high levels of painful emotions/awareness, lack of pain tolerance) and interpersonal vulnerabilities (poor communication skills and social problem solving), and little studies have been done on individuals' unique characteristics and environmental factors such as substrate or environmental vulnerability factors. In particular, environmental factors are associated with the occurrence of NSSI by acting as a vulnerability factor that can interfere with the emotional control of individuals, whereas individual factors play a more direct role by contributing to the maintenance of NSSI, so it is more important to consider this for personal environmental involvement in NSSI. This study focused on the Fight-Flight-Freeze System as a factor in the defensive avoidance system of Reward Sensitivity in individual factors. Also, Environmental factors include the level of expressed emotion in family. Wedig and Nock (2007) said that if parents with a self-critical cognitive style take the form of criticizing their children, the experience of NSSI increases. The high level of parental criticism is related to the increasing frequency of NSSI acts as well as to serious levels of NSSI. If the normal coping mechanism fails to control emotions, people want to overcome emotional difficulties even through NSSI, and emotional disturbances experienced by individuals within an unsupported social relationship increase vulnerability to NSSI. Based on these theories, this study is to find ways to prevent NSSI and intervene in counseling effectively by verifying the differences between the characteristics experienced NSSI persons and non-experienced NSSI persons. Therefore, the purpose of this research was to examine the relationship of Fight-Flight-Freeze System (FFFS), level of expressed emotion in family and emotion regulation difficulties, comparing those who experienced Non-Suicidal Self-Injury (NSSI) with those who did not experienced Non-Suicidal Self-Injury (NSSI). The data were collected from university students in Seoul Korea and Gyeonggi-do province. 99 subjects were experienced student of NSSI, while 375 were non- experienced student of NSSI. The results of this study are as follows. First, the result of t-test indicated that NSSI attempters showed a significant difference in fight-flight-freeze system, level of expressed emotion and emotion regulation difficulties, compared with non-attempters. Second, fight-flight-freeze system, level of expressed emotion in family and emotion regulation difficulties of NSSI attempters showed a significant difference in correlation. The correlation was significant only freeze system of fight-flight-freeze system, Level of expressed emotion in family and emotion regulation difficulties. Third, freeze system and level of expressed emotion in family predicted emotion regulation difficulties of NSSI attempters. Fight-freeze system and level of expressed emotion in family predicted emotion regulation difficulties of non-NSSI attempters. Lastly, Practical implications for counselors and limitations of this study are discussed.

Keywords: fight-flight-freeze system, level of expressed emotion in family, emotion regulation difficulty, non-suicidal self injury

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Authors: Elizabeth M. Seabrook, Nikki S. Rickard

Abstract:

Examining time-dependent measures of emotion such as variability, instability, and inertia, provide critical and complementary insights into mental health status. Observing changes in the pattern of emotional expression over time could act as a tool to identify meaningful shifts between psychological well- and ill-being. From a practical standpoint, however, examining emotion dynamics day-to-day is likely to be burdensome and invasive. Utilizing social media data as a facet of lived experience can provide real-world, temporally specific access to emotional expression. Emotional language on social media may provide accurate and sensitive insights into individual and community mental health and well-being, particularly with focus placed on the within-person dynamics of online emotion expression. The objective of the current study was to examine the dynamics of emotional expression on the social network platform Facebook for active users and their relationship with psychological well- and ill-being. It was expected that greater positive and negative emotion variability, instability, and inertia would be associated with poorer psychological well-being and greater depression symptoms. Data were collected using a smartphone app, MoodPrism, which delivered demographic questionnaires, psychological inventories assessing depression symptoms and psychological well-being, and collected the Status Updates of consenting participants. MoodPrism also delivered an experience sampling methodology where participants completed items assessing positive affect, negative affect, and arousal, daily for a 30-day period. The number of positive and negative words in posts was extracted and automatically collated by MoodPrism. The relative proportion of positive and negative words from the total words written in posts was then calculated. Preliminary analyses have been conducted with the data of 9 participants. While these analyses are underpowered due to sample size, they have revealed trends that greater variability in the emotion valence expressed in posts is positively associated with greater depression symptoms (r(9) = .56, p = .12), as is greater instability in emotion valence (r(9) = .58, p = .099). Full data analysis utilizing time-series techniques to explore the Facebook data set will be presented at the conference. Identifying the features of emotion dynamics (variability, instability, inertia) that are relevant to mental health in social media emotional expression is a fundamental step in creating automated screening tools for mental health that are temporally sensitive, unobtrusive, and accurate. The current findings show how monitoring basic social network characteristics over time can provide greater depth in predicting risk and changes in depression and positive well-being.

Keywords: emotion, experience sampling methods, mental health, social media

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Authors: Konstantinos Sofianos, Michael Stefanidakis

Abstract:

Nowadays, advances in information and communication technologies offer a range of opportunities for new approaches, methods, and tools in the field of education and training. Teacher-centered learning has changed to student-centered learning. E-learning has now matured and enables the design and construction of intelligent learning systems. A smart learning system fully adapts to a student's needs and provides them with an education based on their preferences, learning styles, and learning backgrounds. It is a wise friend and available at any time, in any place, and with any digital device. In this paper, we propose an intelligent learning system, which includes an ontology with all elements of the learning process (learning objects, learning activities) and a massive open online course (MOOC) system. This intelligent learning system can be used in music education.

Keywords: intelligent learning systems, e-learning, music education, ontology, semantic web

Procedia PDF Downloads 279

Authors: Merve Denizci Nazligul

Abstract:

Dancers seem to have much higher risk levels for the development of eating disorders, compared to non-dancing counterparts. In a remarkably competitive nature of dance environment, perfectionism and emotion regulation difficulties become inevitable risk factors. Moreover, early maladaptive schemas are associated with various eating disorders. In the current study, it was aimed to investigate the mediating role of difficulties with emotion regulation on the relationship between perfectionism and disordered eating behaviors, as well as on the relationship between early maladaptive schemas and disordered eating behaviors. A total of 70 volunteer dancers (n = 47 women, n = 23 men) were recruited in the study (M age = 25.91, SD = 8.9, range 19–63) from the university teams or private clubs in Turkey. The sample included various types of dancers (n = 26 ballets or ballerinas, n =32 Latin, n = 10 tango, n = 2 hiphop). The mean dancing hour per week was 11.09 (SD = 7.09) within a range of 1-30 hours. The participants filled a questionnaire set including demographic information form, Dutch Eating Behavior Questionnaire, Multidimensional Perfectionism Scale, three subscales (Emotional Inhibition, Unrelenting Standards-Hypercriticalness, Approval Seeking-Recognition Seeking) from Young Schema Questionnaire-Short Form-3 and Difficulties in Emotion Regulation Scale. The mediation hypotheses were tested using the PROCESS macro in SPSS. The findings revealed that emotion regulation difficulties significantly mediated the relationship between three distinct subtypes of perfectionism and emotional eating. The results of the Sobel test suggested that there were significant indirect effects of self-oriented perfectionism (b = .06, 95% CI = .0084, .1739), other-oriented perfectionism (b = .15, 95% CI = .0136, .4185), and socially prescribed perfectionism (b = .09, 95% CI = .0104, .2344) on emotional eating through difficulties with emotion regulation. Moreover, emotion regulation difficulties significantly mediated the relationship between emotional inhibition and emotional eating (F(1,68) = 4.67, R2 = .06, p < .05). These results seem to provide some evidence that perfectionism might become a risk factor for disordered eating behaviors when dancers are not able to regulate their emotions. Further, gaining an understanding of how inhibition of emotions leads to inverse effects on eating behavior may be important to develop intervention strategies to manage their disordered eating patterns in risk groups. The present study may also support the importance of using unified protocols for transdiagnostic approaches which focus on identifying, accepting, prompting to express maladaptive emotions and appraisals.

Keywords: dancers, disordered eating, emotion regulation difficulties, perfectionism

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Authors: Mikel Alonso López

Abstract:

The early eighties saw the rise of a new research trend in several prestigious journals, mainly articles that related emotions with the decision-making processes of the consumer, and stopped treating them as external elements. That is why we ask questions such as: what are emotions? Are there different types of emotions? What components do they have? Which theories exist about them? In this study, we will review the main theories and components of emotion analysing the cognitive factor and the different emotional states that are generally recognizable with a focus in the classic debate as to whether they occur before the cognitive process or the affective process.

Keywords: emotion, consumer behaviour, feelings, decision making

Procedia PDF Downloads 315