• Korean Journal of Child Studies
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• v.25 no.5
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• pp.193-208
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• 2004

This study purported to empirically examine joy expression and its cognitive and social contexts in children's play. The following question was asked: 1) What kind(s) of emotional expression(s) can be considered as a defining feature of play? 2) What cognitive/social play contexts are associated with joy expression. 30 children aged 3, 4, and 5 years were observed in terms of the length of each emotional expression at play/nonplay, and at cognitive/social play categories. The findings of this study showed that regardless of children's age and gender only joy expression could be considered as a defining feature of play, and that R&T play and chase games, or associative and cooperative social play were strongly related to joy expression. The findings were discussed in reference with existing assertions and perspectives, emphasizing the importance of joy expression in defining children's play despite of the predominance of interest expression in play. The findings were also discussed in reference with metacommunication functions and social construction of joy, considering cognitive/social contexts of joy. Implications for play researchers and practitioners were described in terms of developing playful learning strategies for childhood. Limitations of this study, and suggestions for further research were also provided.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.1
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• pp.45-52
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• 2017

EEG signals that are the same as those that have the same disabled people. So, the EEG signals are becoming the next generation. In this paper, we propose an internet of things system that controls the indoor environment using EEG signal. The proposed system consists EEG measurement device, EEG simulation software and indoor environment control device. We use data as EEG signal data on emotional imagination condition in a comfortable state and logical imagination condition in concentrated state. The noise of measured signal is removed by the ICA algorithm and beta waves are extracted from it. then, it goes through learning and test process using SVM. The subjects were trained to improve the EEG signal accuracy through the EEG simulation software and the average accuracy were 87.69%. The EEG signal from the EEG measurement device is transmitted to the EEG simulation software through the serial communication. then the control command is generated by classifying emotional imagination condition and logical imagination condition. The generated control command is transmitted to the indoor environment control device through the Zigbee communication. In case of the emotional imagination condition, the soft lighting and classical music are outputted. In the logical imagination condition, the learning white noise and bright lighting are outputted. The proposed system can be applied to software and device control based BCI.

• The Journal of Society for e-Business Studies
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• v.20 no.2
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• pp.73-91
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• 2015

Nowadays, 'books' are not limited to tangible items no longer, but can be intangible digital contents, along with advancement in e-Book technology and the growth of the markets. However, the role of e-Book viewers that links digital contents and readers has been rarely studied. In this study, therefore, we examined the effects of e-Book viewer's system quality (ease-of-use, functional diversity, interactivity) and design quality (convenient design, intuitive design, emotional design) on user satisfaction, and also tested if these relations are different by the content types (cartoon, novel, and learning contents). Research findings show that all the independent variables, except for interactivity, affect user satisfaction in overall groups. In viewing cartoon content, ease-of-use, convenient design, and emotional design were significant antecedents, and intuitive design and emotional design were found important factors in novel content, while functional diversity and interactivity affect user satisfaction in learning content. We expect these findings can provide useful insights to the providers of e-Book viewers.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of The Korean Association For Science Education
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• v.24 no.2
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• pp.258-266
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• 2004

An increasing number of educators emphasize the affective domain in learning. Affective and cognitive objectives interact and can not be separated from each other. Good emotions and feelings assist students achieving optimally in the cognitive domain. Emotional intelligence harmonizes well with an affective science curriculum. The purpose of this study was to explore the effectiveness of EQ(Emotional quotient) improvement program on students' EQ, science achievement, the science related attitudes, and science anxiety. A pretest-posttest control group design was employed. Subjects were 168 male and female first grade students in a middle school. A control group was instructed with a traditional teaching method, and an experimental group was instructed using EQ improvement program. Two groups were treated for 42 hours during 14 weeks. Two way ANCOVA and correlation analysis was performed using the SPSS. The results indicated that students who received EQ program got higher EQ and their science anxiety was lowered than students who were in a control group(p<.05). EQ program was not significantly effective on science attitude than the traditional instruction but, in the domain 'the enjoyment of science class' it was effective(p<.05). EQ program was significantly effective on students' achievement than the traditional instruction(p<.05).

• Journal of Music and Human Behavior
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• v.10 no.1
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• pp.67-83
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• 2013

Assessment in music therapy is a vital part for both the therapist and client in the process of therapy. Based on what is assessed, objectives are identified to formulate specific action procedures and strategies. The existing assessment tools involve lists of skills and behaviors in developmental domains without the music assessment protocol. In this study, the authors attempted to develop an assessment protocol using rhythm production for assessing skills in cognitive and emotional-behavior domain, namely Music Therapy Assessment for Cognitive and Emotional Behaviors (MACEB). The test items of the MACEB-Rhythm were developed using rhythmic patterns varying in terms of item difficulty, which are based on the various degree of clarity in the grouping/gestalt, saliency in part-whole relationship, and complexity in repetition vs. variability. Also the developed tool purported to examine one's level of emotional behavior trait by analyzing performance of musical parameters such as tempo, pacing, and loudness in the reproduced output. In order to verify the logical sequencing of test items, firstly 61 subjects participated in verifying the item difficulty for the selected 15 pilot items. The test items were revised and re-sequenced based on the gathered scores of item difficulty. In the second procedure, seven experts in the fields of music education, music therapy and music psychology whose research interest lie in music cognition revised the developed rhythm protocol items focusing on learning sequence, cognitive process and feasibility for skills assessment. The study attempted to provide foundations for using rhythm as an assessment protocol prior to its verification of assessment validity and reliability.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.1-14
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• 2014

Both researchers and practitioners are showing an increased interested in interactive exhibition services. Interactive exhibition services are designed to directly respond to visitor responses in real time, so as to fully engage visitors' interest and enhance their satisfaction. In order to install an effective interactive exhibition service, it is essential to adopt intelligent technologies that enable accurate estimation of a visitor's emotional state from responses to exhibited stimulus. Studies undertaken so far have attempted to estimate the human emotional state, most of them doing so by gauging either facial expressions or audio responses. However, the most recent research suggests that, a multimodal approach that uses people's multiple responses simultaneously may lead to better estimation. Given this context, we propose a new multimodal emotional state estimation model that uses various responses including facial expressions, gestures, and movements measured by the Microsoft Kinect Sensor. In order to effectively handle a large amount of sensory data, we propose to use stratified sampling-based MRA (multiple regression analysis) as our estimation method. To validate the usefulness of the proposed model, we collected 602,599 responses and emotional state data with 274 variables from 15 people. When we applied our model to the data set, we found that our model estimated the levels of valence and arousal in the 10~15% error range. Since our proposed model is simple and stable, we expect that it will be applied not only in intelligent exhibition services, but also in other areas such as e-learning and personalized advertising.

• Communications of Mathematical Education
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• v.24 no.1
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• pp.107-122
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• 2010

Mathematically gifted students' emotional changes during Mathematical Olympiad training camp were studied. The emotions of the gifted during the camp were fluctuated significantly by comparing their test scores with other camp attendants, while the morale was high at the beginning. The camp attendants were likely to overcome disappointment resulting from bad scores with putting more efforts on studying, which means their self-assessments for their mathematical talents are not affected by test results. From what characterizes the emotional changes of the gifted, we conclude as follows: First, they tend to be positive on grouping classes depending on the mathematical ability. Second, careful emotional supports and care were needed in ability grouping education. Third, it is important to let the gifted have more chances to communicate with other camp attendants. It is recommended to induce the gifted to put their focus on the learning goal. Fifth, the proper environment helps the gifted be indulged in studying mathematics.

• (The)Korea Educational Review
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• v.23 no.1
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• pp.231-260
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• 2017

The Fourth Industrial Revolution foreshadows radical changes in our lives. In the era of the fourth industrial revolution called the digital revolution, individualized learning based on ubiquitous learning is emphasized. The contents of learning will be centered on procedural knowledge rather than narrative knowledge, and fusion education in which boundaries between learning domains are broken down will be achieved. First of all, learners in the fourth industrial revolution era should have critical thinking and problem solving abilities. Metacognition based on self-control and cognitive flexibility is important for effective self-directed and active learning. Creativity-based collaborative activities, social vision skills, and social and emotional skills are also important competencies. Therefore, in order to provide individualized learning contents to learners in the fourth industrial revolution era, they should be transformed into learning paradigm based on personal characteristics such as learners' self-efficacy, interest, curiosity and creativity. In addition to this, evaluation forms should be diversified according to changing teaching and learning methods. In order to cultivate teachers to lead such educational innovation, it is necessary to reconsider the teaching capacity. Teachers should be able to construct creative lessons by skillfully exploiting technology in future learning environments. In addition to this, it should also have the ability to collaborate and cognitive flexibility to converge with other academic disciplines. Along with these discussions, we proposed the need for policy intervention along with changes in education.

• Journal of the Korean School Mathematics Society
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• v.24 no.4
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• pp.327-348
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• 2021

This study examines the effects of mathematics learning mentoring activities on mathematical knowledge for teaching (MKT) of pre-service mathematics teachers. We choose six pre-service mathematics teachers in the department of mathematics education at M University. The pre-service mathematics teachers conducted 1:1 mathematics learning mentoring for two hours at a times and twice a week for 15 weeks. The pre-service mathematics teachers submitted the mentor log, which recorded weekly learning and emotional observations. We collected the mentor log and the reflection log of pre-service mathematics teachers and the interviews with pre-service mathematics teachers. Based on the collected data, we analyzed the effects of MKT, the understanding of students, and pre-service mathematics teachers' introspection by mathematics learning mentoring. We obtained conclusions as follows. First, mathematics learning mentoring provides an opportunity for pre-service mathematics teachers to apply the theory of mathematical education to schools. Thus pre-service mathematics teachers express theoretical knowledge as practical knowledge. Second, mathematics learning mentoring helps pre-service mathematics teachers have the ability to understand students and provide opportunities to reflect on their attitudes as learners. Third, mathematics learning mentoring helps advance teaching activities by providing pre-service mathematics teachers with opportunities to reflect on their teaching activities. Finally, mathematics learning mentoring has positively influenced the change in pre-service mathematics teachers' beliefs and teaching intuition.