Search for: "emotional intelligence"

Effective interactions between humans and robots are vital to achieving shared tasks in collaborative processes. Robots can utilize diverse communication channels to interact with humans, such as hearing, speech, sight, touch, and learning. Our focus, amidst the various means of interactions between humans and robots, is on three emerging frontiers that significantly impact the future directions of human–robot interaction (HRI): (i) human–robot collaboration inspired by human–human collaboration, (ii) brain-computer interfaces, and (iii) emotional intelligent perception. First, we explore advanced techniques for human–robot collaboration, covering a range of methods from compliance and performance-based approaches to synergistic and learning-based strategies, including learning from demonstration, active learning, and learning from complex tasks. Then, we examine innovative uses of brain-computer interfaces for enhancing HRI, with a focus on applications in rehabilitation, communication, brain state and emotion recognition. Finally, we investigate the emotional intelligence in robotics, focusing on translating human emotions to robots via facial expressions, body gestures, and eye-tracking for fluid, natural interactions. Recent developments in these emerging frontiers and their impact on HRI were detailed and discussed. We highlight contemporary trends and emerging advancements in the field. Ultimately, this paper underscores the necessity of a multimodal approach in developing systems capable of adaptive behavior and effective interaction between humans and robots, thus offering a thorough understanding of the diverse modalities essential for maximizing the potential of HRI.

 

The SD-FIRST program helps fill in the gaps of first-generation students’ home-to-college transition, provides a robust support system by connecting existing campus resources, and provides guidance for staff and faculty on interactions and unique challenges with this student population. Programmatic elements specific for first-generation students, driven by evidence-based resiliency research, were developed to provide academic, social, and economic support. The expected outcome of the SD-FIRST program is to achieve a sustainable increased retention and graduation rate, and an increase in emotional intelligence for students participating in the program. The initial cohort of SD-FIRST scholars began in the fall 2021 semester, and the details of the program as well as initial implementation are included in this paper. 

In response to the novel coronavirus (COVID-19) pandemic, public health interventions such as social distancing and stay-at-home orders have widely been implemented, which is anticipated to contribute to reducing the spread of COVID-19. On the contrary, there is a concern that the public health interventions may increase the level of loneliness. Loneliness and social isolation are public health risks, closely associated with serious medical conditions. As COVID-19 is new to us today, little is known about emotional well-being among people with visual impairment during the COVID-19 pandemic. To address the knowledge gap, this study conducted phone interviews with a convenience sample of 31 people with visual impairment. The interview incorporated the University of California, Los Angeles (UCLA) Loneliness Scale (version 3) and the trait meta-mood scale (TMMS) to measure loneliness and emotional intelligence skills, respectively. This study found that people with visual impairment were vulnerable to the feeling of loneliness during the COVID-19 pandemic and showed individual differences in emotional intelligence skills by different degrees of loneliness. Researchers and health professionals should consider offering adequate coping strategies to those with visual impairment amid the COVID-19 pandemic. 

In the 21st Century, it becomes of utmost importance for the educator and learner to be mindful of the evolution and application of factors that govern the mental state. Many studies revealed that the success of a professional is strongly dependent on their emotion management skills to manage themselves and associated responsibilities in a demanding environment. Emotionally intelligent professionals are also able to handle challenging situations involving other people. These days many industries, research establishments, and universities that hire graduate students conduct specialized training to enhance their soft skills, mainly interpersonal skills, to make their employees perform at their highest potential. One can maximize the gain from soft skills if they are well aware of the state of human psychology developed in the form of emotional intelligence and positive intelligence. In the last two decades, the concept of emotional intelligence was created by professional personality coaching groups. These trainings are heavily attended by professionals engaged in marketing and organization leaders to enhance their capability in the workplace. However, emotional intelligence is mainly about being aware of the mental state and maintaining control of one's actions during various mental states, such as anger, happiness, sadness, remorse, etc. Aspiring graduate students in science and technology generally lack formal training in understanding human behavior and traits that can adversely impact their ability to perform and innovate at the highest level. This paper focuses on training graduate students about the popular and practical transactional analysis science and assessing their competence in utilizing this knowledge to decipher their own and other people's behavior. Transactional analysis was taught to students via Student presentation-based effective teaching (SPET) methodology. Under this approach, graduate students enrolled in the MECH 500 Class were provided a set of questions to answer by self-reading of the recommended textbook "I am OK You are OK by Thomas Harris." Each student individually answered the assignment questions and then worked in the group to prepare a group presentation for the in-class discussion. Three group discussions were conducted to present different views about the four types of transactions and underlying human traits. Before transactional analysis training, students were also trained in Positive intelligence psychology tools for a similar objective. After the discussion, students were surveyed about the depth of their understanding. Students also reflected their views on the utility of transactional analysis with respect to positive intelligence. More than 75% of students mention that they gain high competency in understanding, defining, and utilizing transactional analysis. This study presents insights for positively impacting graduate students' mindsets as they pursue an unpredicted course of research that can sometimes become very challenging. 

Typically college STEM instructors implicitly expect a level of meta-cognition, emotional resiliency, and general student readiness that largely exceeds any training or preparation students receive in K-12. Not meeting such expectations is perhaps a more significant barrier to student success than deficits in subject-based knowledge. This paper discusses initiatives at Sitting Bull College that seek, without substantial curricular change, to enhance student meta-cognition and emotional intelligence through the use of contextualized & project-based learning in a cohort model that incorporates specific skills training (such as Motivational Interviewing) for both students and instructors. 

This paper details a poster presented in the National Science Foundation (NSF) Grantees Poster Session for the 2022 ASEE Annual Conference. The study, aptly titled, aims to examine the ‘Long-Term Effect of Involvement in Humanitarian Engineering Projects on Student Professional Formation and Views of Diversity, Equity, and Inclusion (DEI).’ As part of the larger study, this poster details the results from alumni (n=19) of the Lipscomb University engineering program collected through an open-ended questionnaire. The research team performed an inductive coding analysis of the qualitative data to understand the connections between humanitarian engineering projects, professional formation, and views of DEI. Quantitative results as well as data from other participant groups, including current students and non-alumni engineering professionals, will be presented elsewhere. Emergent codes showed that participants found both outward and inward value in serving others. Outward value reflected a better quality of life for the person benefiting from service while inward value provided personal satisfaction, learning, or growth for the participant. This inward value was also evident with respect to views of DEI where participants mentioned learning or growing from past events. Two participants directly mentioned a connection between their experiences with humanitarian engineering projects and their views of DEI. Additionally, the codes connected to existing literature in engineering education as well as theories like empathy, identity development, and emotional intelligence. These results are promising for this study and will be expanded upon through interviews where these connections will be examined at a deeper level. 

CONTEXT There is today a broad consensus that emotions influence all forms of teaching and learning, and scholarship on Emotions in Engineering Education (EEE) is an emerging and rapidly growing field. However, this nascent research is currently very dispersed and not well consolidated. There is also a lack of knowledge about the state of the art, strengths, and limitations of the existing literature in the field, gaps, and future avenues for research. PURPOSE We have conducted a scoping review of EEE research, aiming to provide a first overview of the EEE scholarship landscape. We report here on preliminary findings related to (1) the status of the field, (2) geographical representation of authors, and (3) emerging hot spots and blind spots in terms of research approaches, contexts, and topics. METHODS The scoping review is part of a larger, systematic review of the EEE literature. Using an inclusive search strategy, we retrieved 2,175 items mentioning emotions and engineering education, including common synonyms. Through abstract screening and full text sifting, we identified 184 items that significantly focus on engineering education and emotion. From these items, we extracted and synthesized basic quantitative and qualitative information on publication outlets, author origins, keywords, research approaches, and research contexts. PRELIMINARY RESULTS Surprised by the large number of EEE publications, we found that EEE is a rapidly expanding, but internationally dispersed field. Preliminary results also suggest a dominance of research on higher education, often exploring students’ academic emotions or emotional competences. Research on emotional intelligence and anxiety is particularly common while studies focusing on cultural and sociological aspects of EEE are largely absent. CONCLUSIONS The EEE literature is expanding exponentially. However, the field is not well consolidated, and many blind spots remain to be explored in terms of research approaches, contexts, and foci. To accelerate the development of the field, we invite current and prospective EEE researchers to join our emerging, international community of EEE researchers. 

The overall goal of our research is to develop a system of intelligent multimodal affective pedagogical agents that are effective for different types of learners (Adamo et al., 2021). While most of the research on pedagogical agents tends to focus on the cognitive aspects of online learning and instruction, this project explores the less-studied role of affective (or emotional) factors. We aim to design believable animated agents that can convey realistic, natural emotions through speech, facial expressions, and body gestures and that can react to the students’ detected emotional states with emotional intelligence. Within the context of this goal, the specific objective of the work reported in the paper was to examine the extent to which the agents’ facial micro-expressions affect students’ perception of the agents’ emotions and their naturalness. Micro-expressions are very brief facial expressions that occur when a person either deliberately or unconsciously conceals an emotion being felt (Ekman &Friesen, 1969). Our assumption is that if the animated agents display facial micro expressions in addition to macro expressions, they will convey higher expressive richness and naturalness to the viewer, as “the agents can possess two emotional streams, one based on interaction with the viewer and the other based on their own internal state, or situation” (Queiroz et al. 2014, p.2).The work reported in the paper involved two studies with human subjects. The objectives of the first study were to examine whether people can recognize micro-expressions (in isolation) in animated agents, and whether there are differences in recognition based on the agent’s visual style (e.g., stylized versus realistic). The objectives of the second study were to investigate whether people can recognize the animated agents’ micro-expressions when integrated with macro-expressions, the extent to which the presence of micro + macro-expressions affect the perceived expressivity and naturalness of the animated agents, the extent to which exaggerating the micro expressions, e.g. increasing the amplitude of the animated facial displacements affects emotion recognition and perceived agent naturalness and emotional expressivity, and whether there are differences based on the agent’s design characteristics. In the first study, 15 participants watched eight micro-expression animations representing four different emotions (happy, sad, fear, surprised). Four animations featured a stylized agent and four a realistic agent. For each animation, subjects were asked to identify the agent’s emotion conveyed by the micro-expression. In the second study, 234 participants watched three sets of eight animation clips (24 clips in total, 12 clips per agent). Four animations for each agent featured the character performing macro-expressions only, four animations for each agent featured the character performing macro- + micro-expressions without exaggeration, and four animations for each agent featured the agent performing macro + micro-expressions with exaggeration. Participants were asked to recognize the true emotion of the agent and rate the emotional expressivity ad naturalness of the agent in each clip using a 5-point Likert scale. We have collected all the data and completed the statistical analysis. Findings and discussion, implications for research and practice, and suggestions for future work will be reported in the full paper. ReferencesAdamo N., Benes, B., Mayer, R., Lei, X., Meyer, Z., &Lawson, A. (2021). Multimodal Affective Pedagogical Agents for Different Types of Learners. In: Russo D., Ahram T., Karwowski W., Di Bucchianico G., Taiar R. (eds) Intelligent Human Systems Integration 2021. IHSI 2021. Advances in Intelligent Systems and Computing, 1322. Springer, Cham. https://doi.org/10.1007/978-3-030-68017-6_33Ekman, P., &Friesen, W. V. (1969, February). Nonverbal leakage and clues to deception. Psychiatry, 32(1), 88–106. https://doi.org/10.1080/00332747.1969.11023575 Queiroz, R. B., Musse, S. R., &Badler, N. I. (2014). Investigating Macroexpressions and Microexpressions in Computer Graphics Animated Faces. Presence, 23(2), 191-208. http://dx.doi.org/10.1162/