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The teaching of communication skills is a labour-intensive task because of the detailed feedback that should be given to learners during their prolonged practice. This study investigates to what extent our FILTWAM facial and vocal emotion recognition software can be used for improving a serious game (the Communication Advisor) that delivers a web-based training of communication skills. A test group of 25 participants played the game wherein they were requested to mimic specific facial and vocal emotions. Half of the assignments included direct feedback and the other half included no feedback. It was investigated whether feedback on the mimicked emotions would lead to better learning. The results suggest the facial performance growth was found to be positive, particularly significant in the feedback condition. The vocal performance growth was significant in both conditions. The results are a significant indication that the automated feedback from the software improves learners’ communication performances. 相似文献
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This special issue of Learning and Instruction examines the role of emotions in academic learning, with a special focus on emotions in computer-supported academic learning (or e-learning). Three central research challenges concerning emotion in e-learning are: identification (e.g., what are the key emotions in e-learning?), measurement (e.g., how can we tell how strongly a learner is experiencing each key emotion during e-learning?), and explanation (e.g., what are the causes and consequences of the learner's emotional state during learning?). A useful goal of research on emotions in e-learning is to test an affective-cognitive model of e-learning with links among an e-learning episode, the learner's emotional reaction during learning, the learner's cognitive processing during learning, and the learning outcome. 相似文献
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Mei-Hung Chiu Hongming Leonard Liaw Yuh-Ru Yu Chin-Cheng Chou 《British journal of educational technology : journal of the Council for Educational Technology》2019,50(1):469-480
Utilizing facial recognition technology, the current study has attempted to predict the likelihood of student conceptual change with decision tree models based on the facial micro-expression states (FMES) students exhibited when they experience conceptual conflict. While conceptual change through conceptual conflicts in science education is a well-studied field, there is little research done on conceptual change through conceptual conflict in terms of students' facial expressions. As facial expressions are one of the most direct and immediate responses one can get during instruction and that facial expressions are often representations student's emotions, a link between students' FMES and learning was explored. Facial data was collected from 90 tenth graders. Only data from the 72 students who made incorrect predictions were analyzed in this study. The concept taught was the relationship between boiling point and air pressure. Through facial recognition software analysis and decision tree models, the current study found Surprised, Sad and Disgusted to be key FMES that could be used to predict student conceptual change in a conceptual conflict-based scenario. 相似文献
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ABSTRACTFor the purpose of improving the quality in Elearning process and overcoming the limitations of the current online educational environments, we propose to take into consideration the emotional states of students during Elearning sessions. Our objective is to ensure the ability of emotional intelligence: Emotion Recognition, in an eLearning environment. Thus, we present an architecture of Emotionally Intelligent Elearning System (EIES). Within the development of a computational probabilistic model of emotions, we proposed a Bayesian Network (BN) model to deal with emotions in Elearning environments and handle the uncertain nature of emotion recognition process. In a second phase, we focus on the incorporation of the emotion recognition in the Elearning systems by developing a simulation of EIES based on the BN model, able to predict the students’ affects. Consequently, we reached positive and promising results related to the fact that simulated EIES based on the BN model of emotions predicts correctly the student’s emotion when an event occurs during an Elearning session. 相似文献
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孤独症是一种脑功能障碍引起的长期发展障碍的综合症,它影响着儿童很多方面的能力和表现,尤其是在社会交往和沟通方面的发展,表现出在与人相处过程中不能作出适当的反应,对与交往的人的特点与个性也不能清楚地进行判断。本文采用对一名孤独症儿童个案研究方法,通过对人物表情、卡通图片表情、创设不同情境推断人物可能的情绪反应等训练,提高孤独症学生对他人情绪的辨别力。结果显示:通过训练该名儿童在理解图中处境所描写的人物关系和其中人物蕴涵的情绪以及推断人物的情绪反应及感受上有所提高。 相似文献
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Jorge Fernández Herrero Francisco Gómez Donoso Rosabel Roig Vila 《British journal of educational technology : journal of the Council for Educational Technology》2023,54(6):1939-1963
To test the suitability of an automatic system for emotional management in the classroom following the control-value theory of achievement emotions (CVT) framework, the performance of an emotional expression recognition software of our creation is evaluated in an online synchronous context. Sixty students from the Faculty of Education at the University of Alicante participated in 16 educational activities recording close-ups of their faces and completing the AEQ emotional self-report, as well as detailed reports from the subsequent review of their videos. In addition, they completed the VCQ-36 test to measure their volitional competencies and relate their influence on their emotional response. The results indicate a high coherence between the emotional expressions detected by the automatic system and the detailed emotional self-reports, but insufficient precision to meet the CVT requirements. On the other hand, both the AEQ test results and the emotion expression recognition software suggest students' preference for participative activities as opposed to passive ones. Meanwhile, statistical analysis results indicate that volitional competencies seem to influence the emotional response of students in the educational context, although the AI system does not show sufficient sensitivity in this field. Implications and limitations of this study for future work are discussed.
Practitioner notes
What is already known about this topic
- Student motivation and involvement in the learning process are highly related to appropriate emotional regulation, which can be associated with particular educational activities, strategies and methodologies.
- Deep learning technology based on convolutional neural networks feeds automatic systems focused on facial expression recognition from image analysis.
What this paper adds
- There is high coherence between the emotional expressions detected by the AI system and the students' emotional self-reports, but the AI system provides just emotional valences, insufficient to meet the CVT framework.
- Both emotional self-reports and the emotion recognition software suggest students' preference for active educational activities as opposed to passive ones.
- Volitional competencies seem to influence the emotional response of students in the educational context.
Implications for practice and/or policy
- It is possible to use automatic systems to effectively monitor the emotional response of students in the learning process.
- Only if sensitivity improved, a real-time, easy-to-interpret emotional expression recognition software interface could be implemented to assist teachers with the emotional management of their classes within the CVT framework, maximizing their motivation and engagement.
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Chih‐Ming Chen Tai‐Hung Lee 《British journal of educational technology : journal of the Council for Educational Technology》2011,42(3):417-440
e‐Learning is becoming an increasingly popular educational paradigm because of the rapid growth of the Internet. Recent studies have argued that affective modelling (ie, considering a learner's emotional or motivational state) should also be considered while designing learning activities. Many studies indicated that various learning emotions markedly impact learning outcomes. In the language education field, many studies have investigated anxiety associated with learning a second language, noting that anxiety has an adverse effect on the performance of those speaking English as a second language. Therefore, how to reduce anxiety associated with learning a second language to increase learning performance is an important research issue in the language education field. Accordingly, this study employed a sensor, signal processing, wireless communication, system‐on‐chip and machine‐learning techniques in developing an embedded human emotion recognition system based on human pulse signals for detecting three human emotions—nervousness, peace and joy—to help teachers reduce language‐learning anxiety of individual learners in a web‐based one‐to‐one synchronous learning environment. The accuracy rate of the proposed emotion recognition model evaluated by cross‐validation is as high as 79.7136% when filtering out human pulse signals that have bias. Moreover, this study applied the embedded emotion recognition system to assist instructor's teaching in a synchronous English conversation environment by immediately reporting variations in individual learner emotions to the teacher during learning. In this instructional experiment, the teacher can give appropriate learning assistance or guidance based on the emotion states of individual learners. Experimental results indicate that the proposed embedded human emotion recognition system is helpful in reducing language‐based anxiety, thus promoting instruction effectiveness in English conversation classes. 相似文献
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Stephen M. Ritchie Kenneth Tobin Maryam Sandhu Satwant Sandhu Senka Henderson Wolff‐Michael Roth 《科学教学研究杂志》2013,50(2):137-161
Teachers often have difficulty implementing inquiry‐based activities, leading to the arousal of negative emotions. In this multicase study of beginning physics teachers in Australia, we were interested in the extent to which their expectations were realized and how their classroom experiences while implementing extended experimental investigations (EEIs) produced emotional states that mediated their teaching practices. Against rhetoric of fear expressed by their senior colleagues, three of the four teachers were surprised by the positive outcomes from their supervision of EEIs for the first time. Two of these teachers experienced high intensity positive emotions in response to their students' success. When student actions/outcomes did not meet their teachers' expectations, frustration, anger, and disappointment were experienced by the teachers, as predicted by a sociological theory of human emotions (Turner, J. H. (2007). Human emotions: A sociological theory. London, England: Routledge). Over the course of the EEI projects, the teachers' practices changed along with their emotional states and their students' achievements. We account for similarities and differences in the teachers' emotional experiences in terms of context, prior experience, and expectations. The findings from this study provide insights into effective supervision practices that can be used to inform new and experienced teachers alike. © 2012 Wiley Periodicals, Inc. J Res Sci Teach 50:137–161, 2013 相似文献
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E-learning allows learners individually to learn “anywhere, anytime” and offers immediate access to specific information. However, learners have different behaviors, learning styles, attitudes, and aptitudes, which affect their learning process, and therefore learning environments need to adapt according to these differences, so as to increase the results of the learning process. In addition, providing the same learning content to all the learners may lead to a reduction in the learner's performance. Hence, there is a need to classify the learners based on their performance and knowledge level. Learner profiles play an important role in making the e-learning environment adaptive. Providing an adaptive learning environment, catering to the changing needs and behavior of the learner can be achieved by evolving dynamic learner profiles. Navigation logs can be used to analyze learners’ behavior over a period of time. In this work, we propose dynamic learner profiling to cater to changing learner behaviors, styles, goals, preferences, performances, knowledge level, learner's state, content difficulty, and feedbacks. Based on the continuous observation of learner preferences and requirements, the learner profile is dynamically updated. Furthermore, we propose an automatic learner classification to construct the learner profile and identify the complexity level of learning content, using the Bayesian belief network and decision tree techniques. We evaluated our system with two traditional adaptive e-learning systems, using static profiles and behavioral aspects, through our performance evaluation method of different learner types. In addition, we compared the actual learners’ data with the system generated results for various types of learners, and showed the increased interest in their learning outcomes. 相似文献
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Monica A. Payne 《Emotional and Behavioural Difficulties》2013,18(2):143-155
Defining ‘emotional illiteracy’ is a task located within the broader context of expert (and subsequently public) assumptions regarding the normally expectable competencies of the age group concerned. In the late 1990s a series of neuroscientific studies reporting adolescents' limited ability to recognize emotional states from facial expressions seemed to present radically new developmental benchmarks. Although these studies were subsequently subjected to considerable methodological and interpretive criticism, some incautious assertions regarding teenagers' general inability to respond appropriately, especially in emotionally charged situations, continued to flourish. This paper charts the creation and maintenance of these ideas over the past decade to illustrate how, when primary sources are not carefully checked, powerful messages for which there is dubious empirical evidence can become incorporated into expert advice. It also suggests the importance of linking neuroscientific claims to other strands of contemporary Western efforts to define and contrast normative and disordered emotional behaviour in adolescence. 相似文献
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The current study investigated factors thought to contribute to facial emotion processing. Female university students (N = 126) completed self-report measures of childhood emotional maltreatment, anxiety symptoms, attachment anxiety and avoidance, and trait mindfulness before completing a facial emotion recognition task, where they viewed sequences of faces that incorporated progressively more emotional content until they were able to correctly identify the emotion. They completed the task under low and high cognitive load conditions to distinguish between relatively effortful versus automatic processing abilities. Regression analyses revealed that under low cognitive load, attachment avoidance and mindfulness predicted quicker identification of fear (i.e., with less perceptual information), whereas anxiety predicted slower identification of fear (i.e., with more perceptual information). In the high cognitive load condition, emotional maltreatment and mindfulness predicted quicker identification of fear, and anxiety and mindfulness predicted faster identification of emotions overall. Although current findings are correlational, most of these effects were specific to fearful faces, suggesting that experiences of childhood emotional maltreatment and associated socio-emotional sequelae are related to heightened processing of threat-related information. 相似文献
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Infants become sensitive to emotion expressions early in the 1st year and such sensitivity is likely crucial for social development and adaptation. Social interactions with primary caregivers may play a key role in the development of this complex ability. This study aimed to investigate how variations in parenting behavior affect infants' neural responses to emotional faces. Event‐related potentials (ERPs) to emotional faces were recorded from 40 healthy 7‐month‐old infants (24 males). Parental behavior was assessed and coded using the Emotional Availability Scales during free‐play interaction. Sensitive parenting was associated with increased amplitudes to positive facial expressions on the face‐sensitive ERP component, the negative central. Findings are discussed in relation to the interactive mechanisms influencing how infants neurally encode positive emotions. 相似文献
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John Chi-Kin Lee Yvonne Xian-Han Huang Edmond Hau-Fai Law Mu-Hua Wang 《Asia-Pacific Journal of Teacher Education》2013,41(3):271-287
This study explores the changing professional identities of teachers and their emotional experiences during curriculum reform in Shenzhen in the southern part of China. A qualitative approach to research was adopted. Findings reveal that the informants display several teaching behaviours and diverse emotions ranging from pain and helplessness, fulfilment and anxiety, and other mixed emotions. The three types of influential factors that influence teachers' professional identities are also discussed in this study. 相似文献
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Hosam Al-Samarraie Hassan Selim Timothy Teo Fahed Zaqout 《Interactive Learning Environments》2017,25(4):452-466
When faced with excessive detail in an online environment, typical users have difficulty processing all the elements of representation. This in turn creates cognitive overload, which narrows the user's focus to a few select items. In the context of e-learning, we translated this aspect as the learner's demand for a system that facilitates the retrieval of learning content – one in which the representation is easy to read and understand. We hypothesized that the representation of content in an e-learning system's design is an important antecedent for learner preferences. The aspects of isolation and distinctiveness were incorporated into the design of e-learning representation as an attempt to promote student cognition. Following its development, the model was empirically validated by conducting a survey of 300 university students. We found that isolation and distinctiveness in the design elements appeared to facilitate the ability of students to read and remember online learning content. This in turn was found to drive user preferences for using e-learning systems. The findings provide designers with managerial insights for enticing learners to continue using e-learning systems. 相似文献
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Kaila C. Bruer Sarah Zanette Xiao Pan Ding Thomas D. Lyon Kang Lee 《Child development》2020,91(4):e995-e1011
This study explored whether children's (N = 158; 4- to 9 years old) nonverbal facial expressions can be used to identify when children are being deceptive. Using a computer vision program to automatically decode children's facial expressions according to the Facial Action Coding System, this study employed machine learning to determine whether facial expressions can be used to discriminate between children who concealed breaking a toy(liars) and those who did not break a toy(nonliars). Results found that, regardless of age or history of maltreatment, children's facial expressions could accurately (73%) be distinguished between liars and nonliars. Two emotions, surprise and fear, were more strongly expressed by liars than nonliars. These findings provide evidence to support the use of automatically coded facial expressions to detect children's deception. 相似文献
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Amy A. Weimer Julie Sallquist Rebecca R. Bolnick 《Early education and development》2013,24(3):280-301
Research Findings: The present study investigated the relation between theory of mind (ToM) and emotion understanding among 78 children 4½ to 6½ years old (35 boys, 43 girls). ToM understanding was assessed using ignorance and false belief questions within an emotion-understanding task that evaluated children's abilities to recognize facial expressions and identify the external causes of emotions (happy, sad, angry, scared, and surprised), understand the role of beliefs and desires in emotion, and comprehend felt versus expressed emotions. Results indicated that children's understanding of the external causes of emotion, hidden emotions, and a reminder's influence on emotions improved with age and that children's understanding of the external causes of emotion related to ToM understanding. Practice or Policy: Findings suggest that programs that seek to promote children's socioemotional awareness could benefit from encouraging the development of children's understanding of the external causes of emotions to improve overall social cognition. 相似文献
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This paper explores the experiences of women doctoral students and the role of emotion during doctoral candidature. The paper draws on the concept of emotional labour to examine the two sites of emotional investment students experienced and managed during their studies: writing and family relationships. Emotion is perceived by many dominant stakeholders as soft, subjective and an impediment to acquiring objective knowledge. The importance of emotion is under recognised. When it is discussed, the role of emotion in the doctoral undertaking is often subsumed in the passionless language of bureaucratic rationalisation and economic imperatives. This paper builds on a growing literature that examines students' emotions and doctoral candidature. It draws on the experiences of women undertaking their doctoral studies at a large metropolitan university in Sydney, Australia, to show first, how emotional labouring can enable students to channel emotions towards productive behaviours that can contribute to successful doctoral candidature, and second, that studies that attend to emotion offer more nuanced insights into students' experiences during the doctoral undertaking. 相似文献