• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.391-398
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• 2022

As non face-to-face classes carry on discussion about learner's attention continues. To improve learning effect learner's attention is important whether non face-to-face classes or face-to-face classes. In this study a mobile application prototype inducing learner attention is developed taking account of learner emotion that is one of the factors affecting learner attention. When learner selects one of the four emotions displayed in the application, it shows the activity inducing the learner's attention related to the selected emotion. In order to evaluate the usability of the developed application, 32 middle and high school students are asked to run the application and then conduct a survey using 5 point Likert scale. The survey result indicates that there is a possibility that the developed application in this study induces learner attention as showing that the result point of 'I can pay attention' and 'I feel psychological stable' is respectively 3.56 and the result point of 'I feel useless thought disappear' is 3.6.

• Journal of Korean Elementary Science Education
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• v.38 no.2
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• pp.244-262
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• 2019

The purpose of this study is to explore how the practical knowledge used by an elementary school science teacher during learner-centered science instruction can promote elementary students' construction of positive emotion. Using an auto-ethnographic approach over a period of three months, the researchers collected students' interest diaries, post interviews with students, video recordings in science classes, and students' personal diaries and analyzed them by means of the constant comparative method. In this way, the researchers categorized the structure of the practical knowledge held by the teacher and explained how it was applied in learner-centered science instruction to promote students' construction of positive emotion. Three images of an elementary science teacher's practical knowledge emerged and can be categorized under the following headings: 1) 'From science classroom to science $caf{\acute{e}}$', 2) 'Pleasant experiment class for all students and the teacher', and 3) 'A science class for students who were marginalized'. These images were backed up by principles and rules, and the teacher came to embody these images as he implemented these rules. This study also discusses how the impact of a science teacher's practical knowledge on students' construction of positive emotions can be interpreted as promoting positive outcomes rather than negative sanctions, meeting students' expectation from lab activities, and meeting the specific needs of marginalized students in a science class.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.57-62
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• 2022

This study was conducted with the purpose of listening to the explanations of artworks in the non-face-to-face class and confirming the learner's feelings as a result of the class. The proposed system listens to the explanation of the artwork, inputs the learner's emotions with a dedicated key, and expresses the result in music. To this end, the direction of the non-face-to-face art appreciation class model using the emotion key was set, and based on this, a system for non-face-to-face art appreciation was constructed. The learner will use the 'smart device using the emotion key' proposed in this study to listen to the explanation of the artwork and to input the emotion for the question presented. Through the proposed system, learners can express their emotional state in online art classes, and instructors receive the results of class participation and use them in various ways for educational analysis.

• The Journal of Korean Association of Computer Education
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• v.10 no.4
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• pp.125-133
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• 2007

Many researches have tried to introduce affective computing for Human-Computer Interaction (HCI). In the affective aspect, emotional memories significantly affect on people's cognitive processing activities. In this paper, to observe the effect of affective feedback for emotional state of learners in an e-learning environment, selected emotional feedback messages and delivery method are integrated into an e-learning system. Self reporting button for recognizing learner's emotional state are used for detecting learner's emotional states and the test results show that providing affective feedback to learner has positive effects in e-learning environment in terms of learner's academic achievements.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.519-525
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• 2006

Advances in information and telecommunication technology increasingly reveal the potential of computer supported education. However, most computer supported learning systems until recently did not pay much attention to different characteristics of individual learners. Intelligent learning environments adaptive to learner's preferences and tasks are desired. Each learner has different preferences and needs, so it is very crucial to provide the different styles of learners with different learning environments that are more preferred and more efficient to them. This paper reports a study of the intelligent learning environment where the learner's preferences are diagnosed using learner models, and then user interfaces are customized in an adaptive manner to accommodate the preferences. In this research, the learning user interfaces were designed based on a learning-style model by Felder & Silverman, so that different learner preferences are revealed through user interactions with the system. Then, a learning style modeling is done from learner behavior patterns using Decision Tree and Neural Network approaches. In this way, an intelligent learning system adaptive to learning styles can be built. Further research efforts are being made to accommodate various other kinds of learner characteristics such as emotion and motivation as well as learning mastery in providing adaptive learning support.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.8-17
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• 2019

The main purpose of this study isto explore the potential of affective computing (AC) platforms in education through two phases ofresearch: Phase I - platform analysis and Phase II - classification of academic emotions. In Phase I, the results indicate that the existing affective analysis platforms can be largely classified into four types according to the emotion detecting methods: (a) facial expression-based platforms, (b) biometric-based platforms, (c) text/verbal tone-based platforms, and (c) mixed methods platforms. In Phase II, we conducted an in-depth analysis of the emotional experience that a learner encounters in online video-based learning in order to establish the basis for a new classification system of online learner's emotions. Overall, positive emotions were shown more frequently and longer than negative emotions. We categorized positive emotions into three groups based on the facial expression data: (a) confidence; (b) excitement, enjoyment, and pleasure; and (c) aspiration, enthusiasm, and expectation. The same method was used to categorize negative emotions into four groups: (a) fear and anxiety, (b) embarrassment and shame, (c) frustration and alienation, and (d) boredom. Drawn from the results, we proposed a new classification scheme that can be used to measure and analyze how learners in online learning environments experience various positive and negative emotions with the indicators of facial expressions.

• Educational Technology International
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• v.18 no.2
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• pp.101-129
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• 2017

This study attempted to collect learners' emotion and state motivation, analyze their inner states, and measure state motivation using a non-self-reported survey. Emotions were measured by learning segment in detailed learning situations, and they were used to indicate total state motivation with prediction power. Emotion was also used to explain state motivation by learning segment. The purpose of this study was to overcome the limitations of video-based learning environments by verifying whether the emotions measured during individual learning segments can be used to indicate the learner's state motivation. Sixty-eight students participated in a 90-minute to measure their emotions and state motivation, and emotions showed a statistically significant relationship between total state motivation and motivation by learning segment. Although this result is not clear because this was an exploratory study, it is meaningful that this study showed the possibility that emotions during different learning segments can indicate state motivation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.67-75
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• 2022

Recently, e-learning has been attracting significant attention due to COVID-19. However, while e-learning has many advantages, it has disadvantages as well. One of the main disadvantages of e-learning is that it is difficult for teachers to continuously and systematically monitor learners. Although services such as personalized e-learning are provided to compensate for the shortcoming, systematic monitoring of learners' concentration is insufficient. This study suggests a method to evaluate the learner's concentration by applying machine learning techniques. In this study, emotion and gaze data were extracted from 184 videos of 92 participants. First, the learners' concentration was labeled by experts. Then, statistical-based status indicators were preprocessed from the data. Random Forests (RF), Support Vector Machines (SVMs), Multilayer Perceptron (MLP), and an ensemble model have been used in the experiment. Long Short-Term Memory (LSTM) has also been used for comparison. As a result, it was possible to predict e-learners' concentration with an accuracy of 90.54%. This study is expected to improve learners' immersion by providing a customized educational curriculum according to the learner's concentration level.

• Journal of Engineering Education Research
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• v.10 no.3
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• pp.21-37
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• 2007

The purpose of this study is to exploring the direction of woman engineering education by the analysis of learner's recognition. In order to investigate the direction of woman engineering education, the literature reviews were explored in the context of the human resource developmentand in the viewpoint of instructional technology. The survey results such as the learner's experience recognition of engineering education were analyzed and they were discussed by experts in the field of education, instructional technology, and engineering. From the analysis result of 399 students(man:206, woman:193) in P university, there were significant differences with man and woman to the factors of (a) understanding, (b) satisfaction, (c) motivation, (d) learning ability, (e) parents' expectation, (f) pleasure in the study, and (g) expectation grade. This study was suggesting the recommendations of woman engineering education in the viewpoints of cognition, emotion, motivation, environment and instructional strategy. The research results will show the cues of human resource development for women in the field of engineering education.

• Korean Journal of Culture and Social Issue
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• v.14 no.1_spc
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• pp.187-221
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• 2008

Although academic interest, the intersection of cognition, emotion, and motivation, is a primary goal of learning and mediates the effects of learning, the present learning environment is full of impeding factors which undermine learner's interests in learning situation. The purpose of this study is to examine current state of academic interests of Korean students and to identify several potential causes of developmental declines in academic interests. It has been consistently found that academic interests in various school subjects decrease with age and grade in school. Three potentially contributing factors to the observed loss of academic interests are mainly discussed: deprived autonomy, severe competition, and normative evaluation. Based on theories on interest and motivation, and empirical findings, various prescriptions are also suggested for designing an interest-based learning environment in order to trigger and enhance learner's academic interests.