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Although being fundamental for both clinical and educational work with children, there is currently no in-depth research on examining children’s emotion awareness and vocabulary in Vietnam. The goal of this exploratory study is to determine the effect of chil- dren’s gender, grade level, and socioeconomic background on their emotion awareness and vocabulary, and the semantic and grammatical diversity of Vietnamese children’s emotional vocabulary. The sample included 264 Vietnamese children (M = 7.80, SD = .97, 43.18% boys) as well as their mothers. Quantitative findings suggested that children in Grade 3 more frequently quoted surprise- and anger-related vocabulary than did those in lower grades. Children’s socioeconomic background had a significant effect on both emotion awareness and vocabulary whereas gender did not. Qualitative analysis revealed diverse grammatical types to describe emotions, except idioms, as well as the presence of body-related emotion vocabulary within children’s records. Finally, a high prevalence of emotion words such as “happy” and “sad” was subject to further cross-cultural review.

Developers experience a wide range of emotions during programming tasks, which may have an impact on job performance. In this paper, we present an empirical study aimed at (i) investigating the link between emotion and progress, (ii) understanding the triggers for developers' emotions and the strategies to deal with negative ones, (iii) identifying the minimal set of non-invasive biometric sensors for emotion recognition during programming tasks. Results confirm previous findings about the relation between emotions and perceived productivity. Furthermore, we show that developers' emotions can be reliably recognized using only a wristband capturing the electrodermal activity and heart-related metrics. © 2020 Association for Computing Machinery., open access

EVA1 is describing a new class of emotion-aware autonomous systems delivering intelligent personal assistant functionalities. EVA requires a multi-disciplinary approach, combining a number of critical building blocks into a cybernetics systems/software architecture: emotion aware systems and algorithms, multimodal interaction design, cognitive modelling, decision making and recommender systems, emotion sensing as feedback for learning, and distributed (edge) computing delivering cognitive services., QC 20180831

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works., Emotion awareness is becoming a key aspect in collaborative work at academia, enterprises and organizations that use collaborative group work in their activity. Due to pervasiveness of ICT's, most of collaboration can be performed through communication media channels such as discussion forums, social networks, etc. The emotive state of the users while they carry out their activity such as collaborative learning at Universities or project work at enterprises and organizations influences very much their performance and can actually determine the final learning or project outcome. Therefore, monitoring the users' emotive states and using that information for providing feedback and scaffolding is crucial. To this end, automated analysis over data collected from communication channels is a useful source. In this paper, we propose an approach to process such collected data in order to classify and assess emotional states of involved users and provide them feedback accordingly to their emotive states. In order to achieve this, a fuzzy approach is used to build the emotive classification system, which is fed with data from ANEW dictionary, whose words are bound to emotional weights and these, in turn, are used to map Fuzzy sets in our proposal. The proposed fuzzy-based system has been evaluated using real data from collaborative learning courses in an academic context., Peer Reviewed, Postprint (author's final draft)

Starting from Volume 17 Issue 4, all published articles of the Journal of Educational Technology & Society are available under Creative Commons CC-BY-ND-NC 3.0 license., Considering social and emotional competence in learning, emotion awareness aims to detect the emotions that students show during their learning interactions and make these emotions explicit to them. Being aware of their emotions, students become more conscious of their situation, what may prompt them to behavioral change. The main goal of this work is to analyze the effects of emotion awareness, supported by specific teaching strategies, on students’ motivation, engagement, self-regulation and learning outcome in long-term blended collaborative learning practices. A bilateral goal also involves an initial study that explores the way emotion awareness affects teacher’s attitude and feedback as well as the competencies that teachers need to have in order to achieve a positive change on students’ affective and cognitive state. To this end a quasi-experimental study was designed with high school students. The results of this study show that when students are aware of their emotions and guided by specific teaching strategies, their learning performance improves in relation to their motivation, engagement and self-regulation. Likewise, when teachers are conscious of students’ emotional state their attitude and feedback become more effective and timely., Peer Reviewed, Postprint (published version)

Group recommender systems help users to find items of interest collaboratively. Support for such collaboration has been mainly provided by tools that visualize membership awareness, preference awareness and decision awareness. However, these mechanisms do not address group dynamic issues: how member may affect each other. In this paper, we investigate the roles of emotion awareness tools and how they may enable positive group dynamics. We first describe the design process behind a set of dynamic emoticons, which we call empatheticons. We then show that they allow users to represent, annotate, and visualize group members' emotions in GroupFun, a group music recommender. An in-depth user study (N = 18) with GroupFun demonstrates that users' emotion annotation for recommended songs can be influenced by other group members. Most importantly, empatheticons enhance users' perceptions of the connectedness (immediacy) and familiarity (intimacy) with each other and the positive group dynamics.

Group recommender systems help users to find items of interest collaboratively. Support for such collaboration has been mainly provided by tools that visualize membership awareness, preference awareness and decision awareness. However, these mechanisms do not address group dynamic issues: how member may affect each other. In this paper, we investigate the roles of emotion awareness tools and how they may enable positive group dynamics. We first describe the design process behind a set of dynamic emoticons, which we call empatheticons. We then show that they allow users to represent, annotate, and visualize group members' emotions in GroupFun, a group music recommender. An in-depth user study (N = 18) with GroupFun demonstrates that users' emotion annotation for recommended songs can be influenced by other group members. Most importantly, empatheticons enhance users' perceptions of the connectedness (immediacy) and familiarity (intimacy) with each other and the positive group dynamics.

(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works., Emotions strongly influence human's behavior in individual and social situations and must be seriously considered in any human activity, such as e-Learning. Indeed, the embedding of emotional awareness features into virtual learning environments could offer a more authentic and challenging e-Learning experience, either individual or collaborative. However, the lack of empirical results together with the complexity attributed to the management by computers of human emotions and affective data, seriously limits the advances in e-Learning as it impedes to virtualize many real-world learning situations in which emotions play a significant role. In this paper, we investigate the use of the SmartBox device for emotion measurement of distance learners during their study as well as the development of affective strategies based on the SmartBox's stimulation capabilities. The aim is to collect emotion data from different sources in order to provide the most appropriate affective responses that positively influence distance learners' study and results and ultimately enhance the e-Learning process., Peer Reviewed, Postprint (author's final draft)

Group recommender systems help users to find items of interest collaboratively. Support for such collaboration has been mainly provided by tools that visualize membership awareness, preference awareness and decision awareness. However, these mechanisms do not address group dynamic issues: how member may affect each other. In this paper, we investigate the roles of emotion awareness tools and how they may enable positive group dynamics. We first describe the design process behind a set of dynamic emoticons, which we call empatheticons. We then show that they allow users to represent, annotate, and visualize group members' emotions in GroupFun, a group music recommender. An in-depth user study (N = 18) with GroupFun demonstrates that users' emotion annotation for recommended songs can be influenced by other group members. Most importantly, empatheticons enhance users' perceptions of the connectedness (immediacy) and familiarity (intimacy) with each other and the positive group dynamics.