• The Mathematical Education
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• v.63 no.2
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• pp.369-385
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• 2024

With the advancement of digital technology, a variety of digital materials are being utilized in education. For their appropriate use of digital resources, teachers need to be able to evaluate the quality of digital resource and determine the suitability for teaching. This study explored how preservice teachers evaluate TocToc-Math, an Artificial Intelligence (AI)-based math support system. Based on an evaluation framework developed through prior research, preservice teachers evaluated TocToc-Math with evidence-based criteria, including content quality, pedagogy, technology use, and mathematics curriculum alignment. The findings shows that preservice teachers positively evaluated TocToc-Math overall. The evaluation tendencies of preservice teachers were classified into three groups, and the specific characteristics of each factor differed depending on the group. Based on the research results, we suggest implications for improving preservice teachers' evaluation abilities regarding the use of digital technology and AI in mathematics education.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.225-233
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• 2017

In this paper, we collected the articles related to artificial intelligence among SCI(E) journals published by Korean authors in 'Web of Science' and conducted frequency analysis and keyword network analysis. As a result of the analysis, the artificial intelligence thesis showed an average growth of about 10% per year, but the relative ratio decreased. As time went on, we could confirm that there is a lot of practical and applied research in artificial intelligence research. Unlike the US 'National Strategy for Artificial Intelligence Research and Development,' the field of research in Korea was focused on local and technical aspects. Therefore, Korea should go beyond the theoretical and technical iterations of artificial intelligence, and research should be carried out to present a comprehensive future direction.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.203-208
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• 2021

This study is to investigate the impact of emotional intelligence of online shopping mall call center counselor on customer orientation. The SPSS 25.0 ststistics program was applied for the empirical analysis 148(87.05%)of 170 copies are used for final data analysis. The implications of results are as follows. First, use of emotion, a subfactor of emotional Intelligence, has shown to have a significant positive effect on customer orientation. Second, other's emotional appraisal, a subfactor of emotional Intelligence, has shown to have a significant positive effect on customer orientation. Third, self emotional appraisal, a subfactor of emotional Intelligence, has shown to have a significant positive effect on customer orientation. Fourth, regulation of emotion, a subfactor of emotional Intelligence, has shown to have a significant positive effect on customer orientation.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.185-192
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• 2021

The purpose of this study is to investigate the relationship between emotional intelligence and convergence factors of hospital administrative staff. During the survey period from From May 1st to May 31st, 2019, anonymous self-administered responses to 212 administrative staffs of 19 hospitals randomly selected in J area were used as analysis data. According to hierarchical multiple regression analysis, the higher the ego-resiliency, the higher the organizational loyalty, and the higher the organizational commitment, the higher the emotional intelligence, and their explanatory power was 43.0%. Based on these analysis results, efforts are needed to increase ego-resiliency, increase organizational loyalty, and increase organizational commitment in order to increase the emotional intelligence of hospital administrative jobs. The above results are expected to be applied to industrial health education and job management in the future at hospitals to enhance emotional intelligence of hospital administrative staffs. Future research requires the establishment and analysis of a structural equation model that affects the emotional intelligence of hospital administrative staffs.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.435-441
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• 2021

This study was performed to investigate the relations on nursing professionalism, consciousness of biomedical ethics and intrapersonal intelligence of nursing students. The study included 159 nursing students. Data collection period was from December 3, 2018 to December 7 (5 days). Nursing professionalism was 3.97 with low social awareness and consciousness of biomedical ethics was 2.95 with high right to life of newborn and organ transplantation but low artificial abortion and euthanasia. Intrapersonal intelligence was 3.79, which showed high self reflection and self-understanding but low self-planning. There was significant positive correlation between nursing professionalism and consciousness of biomedical ethics (r=.31, p<.001) and nursing professionalism and intrapersonal intelligence(r=.39, p<.001). Nursing professionalism showed a positive correlation with biomedical ethics and intrapersonal intelligence. As a result, the nursing education strategy for positive establishment of nursing professionalism of nursing college students needs to be provided with education to improve intrapersonal intelligence that can improve self-development and education that deals with the foundation of Nursing professionalism.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.549-560
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• 2021

The study was done to investigate the mediating effects of communication ability on the relationship among self-awareness, empathy, emotional intelligence and interpersonal competence of nursing students. Data on subject's self-awareness, empathy, emotional intelligence and interpersonal competence were collected using a structured self-reporting questionnaire. During September and December 2019, data were collected from 282 nursing students in J and K cities. Data were analyzed using three-step mediated regression analysis with the SPSS WIN 21.0 programs. Self-awareness, empathy, emotional intelligence and communication ability were positively correlated with interpersonal competence of nursing students. Also, communication ability had a partial mediating effect on the relationship among self-awareness, empathy, emotion intelligence and interpersonal competence. These finding indicate that it will be more effective to education strategies that can increase self-awareness, empathy, emotional intelligence and communication ability together when developing education programs that improve interpersonal competence.

• Smart Media Journal
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• v.10 no.1
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• pp.99-107
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• 2021

In addition to the 4th Industrial Revolution and Industry 4.0, the recent megatrends in the ICT field are Big-data, IoT, Cloud Computing, and Artificial Intelligence. Therefore, rapid digital transformation according to the convergence of various industrial areas and ICT fields is an ongoing trend that is due to the development of technology of AI services suitable for the era of the 4th industrial revolution and the development of subdivided technologies such as (Business Intelligence), IA (Intelligent Analytics, BI + AI), AIoT (Artificial Intelligence of Things), AIOPS (Artificial Intelligence for IT Operations), and RPA 2.0 (Robotic Process Automation + AI). This study aims to integrate and advance various machine learning services of infrastructure-side GPU, CDA (Connected Data Architecture) framework, and AI based on mass distributed Abyss storage in accordance with these technical situations. Also, we want to utilize AI business revenue model in various industries.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.359-364
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• 2021

Recently, research on predictive systems using deep learning and machine learning of artificial intelligence is being actively conducted. Due to the development of artificial intelligence, the role of the investment manager is being replaced by artificial intelligence, and due to the higher rate of return than the investment manager, algorithmic trading using artificial intelligence is becoming more common. Algorithmic trading excludes human emotions and trades mechanically according to conditions, so it comes out higher than human trading yields when approached in the long term. The deep learning technique of artificial intelligence learns past time series data and predicts the future, so it learns like a human and can respond to changing strategies. In particular, the LSTM technique is used to predict the future by increasing the weight of recent data by remembering or forgetting part of past data. fbprophet, an artificial intelligence algorithm recently developed by Facebook, boasts high prediction accuracy and is used to predict stock prices and cryptocurrency prices. Therefore, this study intends to establish a sound investment culture by providing a new algorithm for automatic cryptocurrency trading by analyzing the actual value and difference using fbprophet and presenting conditions for accurate prediction.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.125-132
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• 2018

In this paper, we design a programming education model that uses emotional intelligence and apply the model to programming education in elementary school. In our previous work, we found that there is a meaningful correlation between emotional intelligence and programming ability. In this paper, as a follow-up study, we design a programming education model based on a storytelling model and emotional intelligence. In order to test the performance of the proposed model, we applied our proposed model to the 5th grade elementary school students who have no programming experience. Based on extensive survey work and statistical analysis, we found that the experimental group by the programming education using the emotional intelligence got a statistically significant higher achievement than the comparative group by the traditional programming education. We hope that our model will be helpful in programming education in schools.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.346-351
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• 2023

With the rapid development of Artificial Intelligence (AI) technology, there is an increasing variety of methods for creating 3D models. These include innovations such as text-only generation, 2D images to 3D models, and combining images with cue words. Each of these methods has unique advantages, opening up new possibilities in the field of 3D modeling. The purpose of this study is to explore and summarize these methods in-depth, providing researchers and practitioners with a comprehensive perspective to understand the potential value of these methods in practical applications. Through a comprehensive analysis of pure text generation, 2D images to 3D models, and images with cue words, we will reveal the advantages and disadvantages of the various methods, as well as their applicability in different scenarios. Ultimately, this study aims to provide a useful reference for the future direction of AI modeling and to promote the innovation and progress of 3D model generation technology.