• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.239-246
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• 2021

In the field of computer graphics and HCI, there are many studies on systems that create characters and interact naturally. Such studies have focused on the user's response to the user's behavior, and the study of the character's behavior to elicit positive emotions from the user remains a difficult problem. In this paper, we develop a prototype of an interaction system to elicit positive emotions from users according to the movement of virtual characters using artificial intelligence technology. The proposed system is divided into face recognition and motion generation of a virtual character. A depth camera is used for face recognition, and the recognized data is transferred to motion generation. We use imitation learning as a learning model. In motion generation, random actions are performed according to the first user's facial expression data, and actions that the user can elicit positive emotions are learned through continuous imitation learning.

• Smart Media Journal
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• v.9 no.3
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• pp.90-97
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• 2020

With the development of the Internet and smartphones, digital sound sources are easily accessible, and accordingly, interest in music search and recommendation is increasing. As a method of recommending music, research using melodies such as pitch, tempo, and beat to classify genres or emotions is being conducted. However, since lyrics are becoming one of the means of expressing human emotions in music, the role of the lyrics is increasing, so a study of emotion classification based on lyrics is needed. Therefore, in this thesis, we analyze the emotions of the farewell lyrics in order to subdivide the farewell emotions based on the lyrics. After constructing an emotion dictionary by vectoriziong the similarity between words appearing in the parting lyrics through Word2Vec learning, we propose a method of classifying parting lyrics emotions using Word2Vec and LSTM, which classify lyrics by similar emotions by learning lyrics using LSTM.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.83-89
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• 2021

This study examined how the learning styles and emotions of 234 students enrolled in early childhood education-related departments affected their ability to participate in the learning community. The research collected the variables of the pre-service early childhood teachers' ability to participate in the learning community, the emotions that they experienced while learning, and their learning styles. The collected data were analyzed through correlation analysis and regression analysis. The results indicate that the students' ability to participate in the learning community was positively correlated with the following: their analytical learning attitude (among learning styles); learning motivation; degree of preference for discussion and discussion types; positive and negative emotions, which are subcategories of learning emotion; and the degree of preference for experimentation and their practice type among teaching methods. Second, regression analysis showed that the students' ability to participate in the learning community could be predicted by negative emotion as a subcategory of their learning emotion, learning motivation, degree of preference for the experiment and practice type, their analytical learning attitude, and the degree to which students value studying the content of their major subjects.

• ETRI Journal
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• v.35 no.5
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• pp.869-879
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• 2013

This study is related to the acquisition of physiological signals of human emotions and the recognition of human emotions using such physiological signals. To acquire physiological signals, seven emotions are evoked through stimuli. Regarding the induced emotions, the results of skin temperature, photoplethysmography, electrodermal activity, and an electrocardiogram are recorded and analyzed as physiological signals. The suitability and effectiveness of the stimuli are evaluated by the subjects themselves. To address the problem of the emotions not being recognized, we introduce a methodology for a recognizer using prototype-based learning and particle swarm optimization (PSO). The design involves two main phases: i) PSO selects the P% of the patterns to be treated as prototypes of the seven emotions; ii) PSO is instrumental in the formation of the core set of features. The experiments show that a suitable selection of prototypes and a substantial reduction of the feature space can be accomplished, and the recognizer formed in this manner is characterized by high recognition accuracy for the seven emotions using physiological signals.

• Journal of The Korean Association For Science Education
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• v.40 no.5
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• pp.503-514
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• 2020

In a sense that achievement emotion is directly associated with achievement activity of students and its result, drastic changes in educational environment such as expansion of e-learning due to COVID-19 may have a large impact on the achievement emotion of students inevitably. However, studies on the foregoing still remain insufficient, and development of a questionnaire capable of making a quantitative measurement on the achievement emotion of students under the environment of e-learning may become the basis of relevant studies, so this study developed the e-learning Achievement Emotions Questionnaire-Korean Middle school Science(e-AEQ-KMS) and verified its validity. e-AEQ-KMS in this study was developed based on the Achievement Emotions Questionnaire-Korean Middle school Science (AEQ-KMS) and by reflecting characteristics of e-learning science class. With 226 questions in total, the questionnaire is composed to measure 9 kinds of achievement emotion such as enjoyment, hope, pride, relief, anger, anxiety, hopelessness, shame, and boredom under 3 academic situations of class situation, learning situation and testing situation. The result of this study has a great significance in the way that it set out a framework for making a comparative analysis quantitatively on the achievement emotion of Korean middle school students in science for e-learning classes.

• Journal of The Korean Association For Science Education
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• v.33 no.2
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• pp.444-465
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• 2013

The purpose of this study is to extract core situations that can arouse various academic emotions and to analyze the characteristics of intensity-frequency of these academic emotions from Korean elementary students in Science classes. To accomplish this study, authors conducted a survey of 642 sixth grade students. The result of the study are as follows: First, science academic emotions varied depending on each of the science learning situations. On the whole, positive-emotions were aroused in science experiment situations and negative-emotions were aroused in evaluation, personality of individuals and other people, teaching-learning method and science experiment situations. If teachers want to manage a specific emotion, they should control the core situations that can arouse that specific emotion. Second, positive-emotions appeared more than negative-emotions in intensity and frequency. But boredom, annoyance and stuffiness appeared the most among negative-emotions. Teachers have to reduce students' boredom, annoyance and stuffiness that are aroused in their science classes. Based on the results, authors become assured that introduction of the emotions was a very useful method in enhancing Korean elementary students' affective domain achievement in science classes.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.259-265
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• 2006

Learning and emotions are very important parts to implement intelligent robots. In this paper, we implement intelligent virtual character based on reinforcement learning which interacts with user and have internal emotion model. Virtual character acts autonomously in 3D virtual environment by internal state. And user can learn virtual character specific behaviors by repeated directions. Mouse gesture is used to perceive such directions based on artificial neural network. Emotion-Mood-Personality model is proposed to express emotions. And we examine the change of emotion and learning behaviors when virtual character interact with user.

• Journal of the Korean Chemical Society
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• v.67 no.4
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• pp.253-270
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• 2023

The purpose of this study was to examine the effect of student-led assessment on achievement emotions and science concept understanding in middle school science classes. For this purpose, 4 of the 7 classes in the third grade of mid- dle school in small and medium-sized cities were selected as the experimental group and conducted student-led assessment, while the comparative group (3 classes) conducted teacher-led assessment. The student-led assessment consisted of 4 stages in which learners took initiative to set learning goals and develop assessment criteria, conduct self assessment and peer assess- ment, and carry out seven assessment activities. Student-led assessment was effective in improving positive achievement emotions and relieving negative achievement emotions and increasing students' science concept understanding in middle school students. Students perform student-led assessment, grasp their reach, and repeatedly go through reflective thinking to compensate for deficiencies in the learning process. Therefore, student-led assessment can be used as a tool to increase science concept understanding by continuously checking the level of science concept understanding.

• The Journal of the Korea Contents Association
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• v.15 no.4
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• pp.545-555
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• 2015

We investigated the influence of negative emotion such as state-trait anxiety and depression and working memory (WM) on Foreign Language Vocabulary Learning (FLVL) of South Korean university students. Also, its implications for developing contents for FLVL were discerned. To do so, state-trait anxiety and depression inventories as well as four kinds of WM test were performed for 132 undergraduate students. Participants also had two semantic learning sessions for Swahili words. The mean scores of negative emotions were normal level. The results of structural equation modeling (SEM) showed that there was no effect of negative emotion on FLVL, while direct effects of the negative emotion on WM and the WM on FLVL were significant. Such results suggested that FLVL would be weakened, with the result that WM had been impaired by negative emotions. These outcomes suggested that when developing FLVL content for university students, it is necessary to consider the negative emotions of foreign language learners and to develop the contents for FLVL in the light of WM load.

• The Journal of Economics, Marketing and Management
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• v.7 no.1
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• pp.26-38
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• 2019

Purpose - This paper is to review recent literature, by conducting a thorough investigation of the limitations and implications for future research on work-life balance with the focus and linkages between work-life balance practices, machine learning and emotional intelligence, work-life conflict, the correlations between work-life enrichment and work-life balance practices, the relationships between employee job satisfaction and work-life balance, the links between work-life balance and the managerial support. Research design, data, and methodology - The paper will further detail linkages between work-life balance and organizational performance outcomes productivity and innovation. Previous literatures have paid attentions to the link of HR practices and organizational outcomes such as productivity, flexibility, and financial performance, but the understanding needs to be extended to involve innovation performance. Dealing with employees' emotions using different machine learning techniques is one of the phenomenal researches in today's world. Here, we examine how far the employees are conscious of their own self and found the ideas and views of an individual about themselves and others. Without proper knowledge about their personality it will be very difficult for an individual to manage their own emotions. This study also aims at finding out the individual abilities to manage their emotions in order to perform well. Conclusions - A theoretical conceptual framework has been built by integrating the existing literature to explain a number of factors which are closely associated with work-life balance. The conceptual model illustrates how the work-life balance interplays with performance and interrelates with the aforementioned factors.