The Journal of the Convergence on Culture Technology
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v.9
no.5
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pp.685-695
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2023
This study aimed to investigate the current utilization and implications of digital learning support media in the field of French studies, and to explore future research directions. To achieve this, we conducted a comprehensive review of the use of digital media in various learning processes within French studies. Additionally, we examined the direct application of ChatGPT, an emerging technology, to learning by extending its use to foreign language and education fields. Our findings indicate that the application of digital learning support media in French studies is somewhat limited, with selective use in processes such as online class support media, pre-class learning, efficient learning and interaction, and self-directed learning. In the case of ChatGPT, our research found that no studies have been conducted within French studies, and very few studies have been conducted on its practical application in other educational fields. While ChatGPT has a wide range of applications and has shown positive effects on learners, ethical concerns have been raised regarding the quality, source, and reliability of information. Therefore, future research in French studies should focus on educational application and effectiveness verification in university teaching and learning situations, as well as interdisciplinary convergence with digital learning support media.
The Journal of the Convergence on Culture Technology
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v.9
no.5
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pp.837-842
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2023
This study analyzed the awareness and actual condition on metaverse utilization in education for design major students. An online survey was conducted for 14 days from May 10 to 23, 2023, targeting 120 students majoring in design at D University. The evaluation method of the questionnaire was a nominal scale and a 5-point scale, and the questionnaire results were analyzed through SPSS 29.0. First, it is necessary to sufficiently share the advantages of metaverse utilization in education with students, and to provide basic literacy programs utilizing the characteristics of metaverse and supporting class activities. Second, students' response will be higher in studio classes where practical training is conducted rather than information delivery or understanding-oriented lectures. Third, in order for the metaverse to become a means of education in the digital transformation era rather than just a temporarily medium in COVID-19 era, specific and systematic design education programs reflecting the characteristics of the metaverse need to be continuously developed. In addition, it is important for instructors to actively review the use of the metaverse and search for various ways to utilize it.
Yeon-Hee Kang;Sung Hee Yang;Yong In Cho;Jung-Hoon Kim
Journal of the Korean Society of Radiology
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v.17
no.6
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pp.947-955
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2023
This study was conducted to investigate the awareness of spent nuclear fuel among residents in nuclear power plant areas and use it as basic data for establishing a disposal facility for high-level radioactive waste. 204 questionnaires collected online were analyzed using SPSS Window Ver 28.0. To verify differences between groups, t-test and one-way ANOVA were performed. And correlation analysis was conducted to confirm the relationship between variables. As a result, first, risk perception regarding nuclear-related accidents showed statistically significant differences depending on gender and educational level. The position on the construction of a permanent disposal facility for spent nuclear fuel showed a statistically significant difference depending on gender, education, and age, and the perception of the importance of each evaluation standard for establishing a spent nuclear fuel management plan showed a statistically significant difference depending on education and age. In terms of trust in information-providing institutions, trust in the National Assembly was found to be the lowest. Second, the results of the correlation analysis between variables showed that local residents are aware that an alternative to the current disposal of spent nuclear fuel is needed, and that financial support for the construction of a permanent disposal facility is needed. Therefore, in order to build a high-level radioactive waste disposal site, it is believed that it is necessary to increase trust in the government, collect opinions from local residents, and provide economic support.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.17
no.2
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pp.153-165
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2022
The COVID-19 Pandemic incident forced all educational and learning activities to move online, so it is no longer an option to use information and communication technology for education and learning. Venture capital has made the largest investment ever in Edu-tech startups. This study investigates the factors influencing the intention to use digital technology in education, taking into account the Unified Theory of Acceptance and Use of Technology (UTAUT) along with digital literacy, which has become an essential ability in the digital age. As a result of the structural equation model analysis, we find that performance expectation, effort expectation, and social influence have a positive effect on the intention to use digital technology in education. Moreover, digital literacy has a positive effect on performance expectation, effort expectation, and social impact, but the direct effect on the intention to use digital technology on learning is not significant. Furthermore, to see the moderating effect of age, the results of multi-group analysis present that the differences between 10s and 60s, between 20s and 60s, between 30s and 60s on the path of social influence on the intention to use digital technology in education are significantly reduced. This study academically contributes to expanding the research on the factors affecting the intention to use digital technology in a specific situation of education by considering both digital literacy and Unified Theory of Acceptance and Use of Technology (UTAUT). In addition, it can be used as a practical guide to the factors to be considered for each age when making learning participants more actively use digital technology.
If the plant genetic resources and information-sharing systems held by arboretums worldwide are effectively utilized, it is believed that a conservation system for plant diversity in the currently inaccessible North Korean region could be established. This study was conducted to review the scientific names of plants native to North Korea but not to South Korea and to assess the status of genetic resources held in domestic and international arboretums. To compile a list and status of North Korean plant's genetic resources, updated checklists of vascular plants in Korean Peninsula and online plant information databases were consulted to compile synonym, distribution range, and other related information. A total of 486 taxa (449 species, 13 subspecies, 21 varieties, 1 forma and 2 hybrids) from 236 genera and 64 families, representing 12.34% of the total native flora of the Korean Peninsular were presented in the North Korea plant list, and the presence of rare, endemic and northern lineage species was confirmed. It was found that 384 taxa from 190 genera, 53 families of North Korean plants are held as genetic resources in 333 arboretums and plant research institutions across 46 countries and 5 continents worldwide. This study is expected to contribute to the construction and application of a species list for plants native to the Korean Peninsula.
Journal of the Korean BIBLIA Society for library and Information Science
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v.35
no.1
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pp.47-71
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2024
This study aims to compare the awareness of the social value of public libraries between users and non-users to materialize the abstract concept of social value and, thereby, to present measures that can be applied to the library field. For this purpose, a survey was conducted in person or online for 15 days from May 7, 2023, targeting Paju citizens. Frequency analysis, factor analysis, independent samples t-test, and one-way analysis of variance were conducted on 206 valid response copies using SPSS 25.0. In the results, it is shown that, first, for awareness of the social value of public libraries according to socio-demographic characteristics, there were significant differences depending on age, with in particular, awareness among those in their 10s and 40s being higher than other age groups. For awareness of community development, the awareness of the female group was higher than that of the male group, while, for the awareness according to occupation, it is shown that awareness was highest in the following order: student, others, housewife, self-employed, and office worker. Second, for the awareness of the social value of public libraries, the awareness of the user group was higher than that of the non-user group in all areas. Third, for awareness of the social value of public libraries according to the level of library use, there was no significant difference between groups. In conclusion, it is suggested that measures to encourage non-users to become users, develop new content and services targeting male group and those in their 60s, and 20s, and strengthen community activities are needed to raise awareness of the social value of Paju City public libraries in the future.
This study was conducted to provide basic data on how to use Generative AI and education to strengthen Generative AI competency in vocational counseling by confirming the experience and perception of job counselors' use of Generative AI. A questionnaire was produced based on literature research and FGI preliminary surveys, and the main contents of the questionnaire were 'experience in using Generative AI (whether to have experience, type of tool, job, educational experience, etc.) and Generative AI recognition (recognition level, usefulness, availability, educational needs, etc.). An online survey was conducted for vocational counselors, and a total of 293 data were analyzed. As a result of major research, first, there were many counselors who had no experience in using Generative AI(60%), and the response that the reason for not using it was because they did not feel the need(28%). Second, the 'degree of recognition' in the Generative AI was somewhat low (M=2.77), and 'Generative AI usefulness' was found to be at a normal level (M=3.32), and it was recognized that it would be necessary mainly for jobs related to 'vocational information'. Third, 'tool (computer use, etc.) competency' (26%) was the highest as the competency required for future vocational counselors, and 'how to use Generative AI' (57%) accounted for a high proportion of the educational content necessary to improve these competencies.
News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.
In medical imaging, three-dimensional (3D) display using Virtual Reality Modeling Language (VRML) as a portable file format can give intuitive information more efficiently on the World Wide Web (WWW). The web-based 3D visualization of functional images combined with anatomical images has not studied much in systematic ways. The goal of this study was to achieve a simultaneous observation of 3D anatomic and functional models with planar images on the WWW, providing their locational information in 3D space with a measuring implement using VRML. MRI and ictal-interictal SPECT images were obtained from one epileptic patient. Subtraction ictal SPECT co-registered to MRI (SISCOM) was performed to improve identification of a seizure focus. SISCOM image volumes were held by thresholds above one standard deviation (1-SD) and two standard deviations (2-SD). SISCOM foci and boundaries of gray matter, white matter, and cerebrospinal fluid (CSF) in the MRI volume were segmented and rendered to VRML polygonal surfaces by marching cube algorithm. Line profiles of x and y-axis that represent real lengths on an image were acquired and their maximum lengths were the same as 211.67 mm. The real size vs. the rendered VRML surface size was approximately the ratio of 1 to 605.9. A VRML measuring tool was made and merged with previous VRML surfaces. User interface tools were embedded with Java Script routines to display MRI planar images as cross sections of 3D surface models and to set transparencies of 3D surface models. When transparencies of 3D surface models were properly controlled, a fused display of the brain geometry with 3D distributions of focal activated regions provided intuitively spatial correlations among three 3D surface models. The epileptic seizure focus was in the right temporal lobe of the brain. The real position of the seizure focus could be verified by the VRML measuring tool and the anatomy corresponding to the seizure focus could be confirmed by MRI planar images crossing 3D surface models. The VRML application developed in this study may have several advantages. Firstly, 3D fused display and control of anatomic and functional image were achieved on the m. Secondly, the vector analysis of a 3D surface model was defined by the VRML measuring tool based on the real size. Finally, the anatomy corresponding to the seizure focus was intuitively detected by correlations with MRI images. Our web based visualization of 3-D fusion image and its localization will be a help to online research and education in diagnostic radiology, therapeutic radiology, and surgery applications.
Along with the rapid advance in internet technologies, ubiquitous mobile device usage has enabled consumers to access real-time information and increased interaction with others through various social media. Consumers can now get information more easily when making purchase decisions, and these changes are affecting the brand landscape. In a digitally connected world, brand image is not communicated to the consumers one-sidedly. Rather, with consumers' growing influence, it is a result of co-creation where consumers have an active role in building brand image. This explains a reality where people no longer purchase products just because they know the brand or because it is a famous brand. However, there has been little discussion on the matter, and many practitioners still rely on the traditional measures of brand indicators. The goal of this research is to present the limitations of traditional definition and measurement of brand and brand image, and propose a more direct and adequate measure that reflects the nature of a connected world. Inspired by the proverb, "A man is known by the company he keeps," the proposed measurement offers insight to the position of brand (or brand image) through co-purchased product networks. This paper suggests a framework of network analysis that clusters brands of cosmetics by the frequency of other products purchased together. This is done by analyzing product networks of a brand extracted from actual purchase data on Amazon.com. This is a more direct approach, compared to past measures where consumers' intention or cognitive aspects are examined through survey. The practical implication is that our research attempts to close the gap between brand indicators and actual purchase behavior. From a theoretical standpoint, this paper extends the traditional conceptualization of brand image to a network perspective that reflects the nature of a digitally connected society.
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