• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.390-399
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• 2022

Purpose: This study was conducted to identify the factors affecting nursing students' resilience. Methods: The subjects were 192 nursing students from a college in G city. Data were collected from september 23 to 26, 2019 and analyzed using SPSS 22.0 and descriptive statistics, t-test, ANOVA, Sheffé test, Pearson's correlation coefficients, and multiple regression. Results: Resilience showed a statistically significant difference according to gender, grade, personal relation, motive for application, major satisfaction, grade point in general characteristics. Academic engagement and resilience showed apparent positive correlation (r=.37, p<.001), stress and resilience showed weak negative correlation (r=-.23, p=.001). In multiple regression analysis, the most affecting factor was the academic engagement (𝛽=.24), poor of subjective health status (𝛽=-.21), female (𝛽=-.19), junior of grade (𝛽=.13). These variables explained 33.0% of the total variance in resilience. Conclusion: To strengthen resilience in nursing students, learning atmosphere creation through intrinsic motivation in the regular class. Also, a variable academic engagement program should be provided to be able to positive thinking about academic study and achievement.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.675-683
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• 2022

Blockchain, which is the basis of virtual assets such as cryptocurrency, is receiving great attention as one of the cornerstone technologies of the 4th industrial revolution. Blockchain is a technology that can fundamentally change our lives not only in finance, but also in politics, logistics, and culture. However, it shows lower-than-expected usability because it is complicated to learn and is continuously being developed. In this study, we tried to investigate whether the Technology Acceptance Model(TAM) of virtual assets can be changed through education on the underlying technology, blockchain. A video-based online experiment was conducted with a total of 103 participants and examined how the type of training(positive, negative) and measurement timing(before, after) affect perceived usefulness, perceived ease of use, acceptance, which are TAM variables, and trust and security, which are related to blockchain characteristics. As a result of the experiment, interactions were found in all dependent variables according to the type of education and measurement timing. Specifically, groups that received negative education had no difference in all variables before and after, but it was found that groups that received positive education showed an increase afterwards. Through this, it can be seen that the effect of education based on the anchoring effect is also shown in the intention to use virtual assets using block chain technology, suggesting that the intention to use blockchain related technology can be increased through positive education.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.703-708
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• 2022

Tables and figures in academic literature contain important and valuable information. Tables and figures represent the essence of the refined study, which is the closest to the raw dataset. If so, can researchers easily access and utilize these image data through the search system? In this study, we try to identify user perceptions and needs for image data through user and case studies. Through this study we also explore expected effects and utilizations of image search systems. It was found that the majority of researchers prefer a system that combines table and figure indexing functions with traditional search functions. They valued the provision of an advanced search function that would allow them to limit their searches to specific object types (pictures and tables). Overall, researchers discovered many potential uses of the system for indexing tables and figures. It has been shown to be helpful in finding special types of information for teaching, presentation, research and learning. It should be also noticed that the usefulness of these systems is highest when features are integrated into existing systems, seamlessly link to fulltexts, and include high-quality images with full captions. Expected effects and utilizations for user-centered image search systems are also discussed.

• Journal of Korean Home Economics Education Association
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• v.33 no.4
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• pp.1-13
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• 2021

The purpose of this study is to identify trends and potential themes of research on consumption of children and adolescents for 20 years by analyzing keywords. The keywords of 869 studies on consumption of children and adolescents published in journals listed in Korean Citation Index were analyzed using text mining techniques. The most frequent keywords were found in the order of youth, youth consumers, consumer education, conspicuous consumption, consumption behavior, and character. As a result of analyzing the frequency of keywords by dividing into five-year periods, it was confirmed that the frequency of consumer education was significantly higher betwn 2006 and 2010. Research on ethical consumption has been active since 2011, and research has been conducted on various topics instead of without a prominent keyword during the most recent 5-year period. Looking at the keywords based on the TF-IDF, the keywords related to the environment and the Internet were the main keywords between 2001 and 2005. From 2006 to 2010, the TF-IDF values of media use, advertisement education, and Internet items were high. From 2011 to 2015, fair trade, green growth, green consumption, North Korean defector youths, social media, and from 2016 to 2020, text mining, sustainable development education, maker education, and the 2015 revised curriculum appeared as important themes. As a result of topic modeling, eight topics were derived: consumer education, mass media/peer culture, rational consumption, Hallyu/cultural industry, consumer competency, economic education, teaching and learning method, and eco-friendly/ethical consumption. As a result of network analysis, it was found that conspicuous consumption and consumer education are important topics in consumption research of children and adolescents.

• The Mathematical Education
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• v.62 no.2
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• pp.289-302
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• 2023

In today's digital information society, student knowledge and skills to analyze big data and make informed decisions have become an important goal of school mathematics. Integrating big data statistical projects with digital technologies in high school <Artificial Intelligence> mathematics courses has the potential to provide students with a learning experience of high impact that can develop these essential skills. This paper proposes a set of guidelines for designing effective big data statistical project-based tasks and evaluates the tasks in the artificial intelligence mathematics textbook against these criteria. The proposed guidelines recommend that projects should: (1) align knowledge and skills with the national school mathematics curriculum; (2) use preprocessed massive datasets; (3) employ data scientists' problem-solving methods; (4) encourage decision-making; (5) leverage technological tools; and (6) promote collaborative learning. The findings indicate that few textbooks fully align with these guidelines, with most failing to incorporate elements corresponding to Guideline 2 in their project tasks. In addition, most tasks in the textbooks overlook or omit data preprocessing, either by using smaller datasets or by using big data without any form of preprocessing. This can potentially result in misconceptions among students regarding the nature of big data. Furthermore, this paper discusses the relevant mathematical knowledge and skills necessary for artificial intelligence, as well as the potential benefits and pedagogical considerations associated with integrating technology into big data tasks. This research sheds light on teaching mathematical concepts with machine learning algorithms and the effective use of technology tools in big data education.

• Journal of Dental Rehabilitation and Applied Science
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• v.38 no.4
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• pp.196-203
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• 2022

Purpose: This study aimed to evaluate the accuracy and clinical usability of an identification model using deep learning for 79 dental implant types. Materials and Methods: A total of 45396 implant fixture images were collected through panoramic radiographs of patients who received implant treatment from 2001 to 2020 at 30 dental clinics. The collected implant images were 79 types from 18 manufacturers. EfficientNet and Meta Pseudo Labels algorithms were used. For EfficientNet, EfficientNet-B0 and EfficientNet-B4 were used as submodels. For Meta Pseudo Labels, two models were applied according to the widen factor. Top 1 accuracy was measured for EfficientNet and top 1 and top 5 accuracy for Meta Pseudo Labels were measured. Results: EfficientNet-B0 and EfficientNet-B4 showed top 1 accuracy of 89.4. Meta Pseudo Labels 1 showed top 1 accuracy of 87.96, and Meta pseudo labels 2 with increased widen factor showed 88.35. In Top5 Accuracy, the score of Meta Pseudo Labels 1 was 97.90, which was 0.11% higher than 97.79 of Meta Pseudo Labels 2. Conclusion: All four deep learning algorithms used for implant identification in this study showed close to 90% accuracy. In order to increase the clinical applicability of deep learning for implant identification, it will be necessary to collect a wider amount of data and develop a fine-tuned algorithm for implant identification.

• 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.

• Korean Journal of Cognitive Science
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• v.34 no.1
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• pp.21-38
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• 2023

The present study was designed to investigate the effect of the difficulty level of retrieval practice and the association strength of categories and stimuli within categories on memory inhibition. Most of the studies have investigated whether inhibition was occurred by manipulating the degree of association strength, emotion value or physical characteristics of non-retrieval practice words within the retrieval practice category. Therefore, it was necessary to study how inhibition occurs according to the degree of difficulty of retrieval stimuli during retrieval practice. The difficulty of retrieval was manipulated into three levels: difficult condition, normal condition, and easy condition through the degree of presentation of consonants and vowels of words during retrieval learning. Additionally, the strength of association between categories and words within categories was manipulated. In previous studies, retrieval-induced forgetting occurred under conditions where the association strength between categories and words within the categories was strong. On the other hand, retrieval-induced forgetting did not occur under conditions where the association strength between categories and words within the categories was weak. The present study, if the inhibition process differs according to the difficulty of retrieval, the possibility of different results from previous studies was explored according to the difference in the strength of association with the category. As a result of the study, in the condition of strong association strength, retrieval-induced forgetting was observed under normal and difficult retrieval difficulty conditions. Whereas retrieval-induced forgetting was not observed under conditions of easy retrieval difficulty condition. In the condition of weak association strength, retrieval-induced forgetting tended to occur under difficult retrieval difficulty conditions. Whereas retrieval-induced forgetting was not observed under conditions of normal and easy retrieval difficulty condition. These results suggest that memory inhibition may appear differently depending on the difficulty of retrieval.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.576-584
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• 2022

As an important branch of cognitive psychology, "constructivism" is called a "revolution" in contemporary educational psychology, which has a profound influence on the field of pedagogy and psychology. Based on "WOS" database, this study selects "WOS Core database" and "KCI database", uses CiteSpace visualization software as analysis tool, and makes knowledge map analysis on the research literature of "constructivism" in the field of education in recent 35 years. Analysis directions include annual analysis, network connection analysis by country(region) branch, author, institution or University, and keyword analysis. The purpose of the analysis is to grasp the subject areas, research hotspots and future trends of the research on constructivism, and to provide theoretical reference for the research on constructivism. There are three conclusions from the study. 1. Studies on the subject of constructivism have continued from the 1980s to the present. It is now in a period of steady development. 2. Countries concerned with the subject of constructivism mainly include the United States, Canada, Britain, Australia and the Netherlands. The main research institutions and authors are mainly located in these countries. 3. Currently, the keywords constructivism research focus on the clusters of "instructional strategies", and the development of science and technology is affecting individual learning. In the future, instructional strategies will become the focus of structural constructivism research. With the development of instructional technology, it is necessary to conduct research related to the development of new teaching models.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.11
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• pp.81-90
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• 2016

This research examines mutual culture education in accordance with Germany's immigrant social integration policy by analyzing the National European School in Berlin. In this regard, the curricula of Joan-Miró elementary school and Finow elementary school are analyzed. Germany maintains a multicultural policy which enables immigrants to maintain their native language and identity and simultaneously integrate them into the German society. In short, maintenance of immigrants' mother tongue and immigrant students' acquisition of the German language is the core of Germany's social integration policy. The National European School in Berlin is a public school established for the sake of an educational environment in which students can not only build up language capacity, but also create a culturally mutual environment for multicultural students. The school's educational objective is mutual culture education which can integrate and maintain the cultural identity and language of multicultural students. Joan-Miró elementary school encourages mutual cultural ability and bilingual ability while preparing students for the future intelligent society, leading their independent life and self-initiated learning. Finow elementary school encourages mutual culture ability, language capacity and directional capability apart from the basic capacities that can reinforce students to become citizens in demand of the future intellectual society. Korean foreign language education needs to be practically diversified as in the case of the Germany's National European school. Also, improvement of educational environment such as students' bilingual ability, students' ability development regarding their individual characteristics, and the capability of mutual culture understanding are issues that should be urgently treated.