• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.1
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• pp.1-16
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• 2024

Alvin Toffler mentioned that it is important for future society to keep pace with synchronization and that time deviations can hinder social development. As we experience the new normal era of untact, we have experienced an increase in non-face-to-face contact and accelerated digital transformation. Amid these rapid changes, we can maintain the need for synchronization or change in space. Therefore, we would like to study what kind of settlements people create and choose. We looked at the metaverse as an object that could indirectly find out about this, and used the content called "Animal Crossing" to collect data related to the spatial form of the metaverse. Sampling utilized a judgment sampling method during non-probability sampling to alleviate differences due to the progress of the game. The collected data was classified according to floor plan and location type and briefly organized through descriptive statistics. After matching each facility by use, data was constructed by setting coordinates for each cluster and listing them. This data was interpreted graphically on the coordinate plane for each cluster, and Euclidean analysis was performed to analyze the relationships between clusters and residential choice using a Euclidean matrix. As a result of the analysis, it could be interpreted that efficiency was pursued by arranging similar functions in close proximity. Nevertheless, when choosing a residence, it was interpreted that the intention was to create a community through arrangement adjacent to residents rather than efficiency or convenience. Due to the differences between the metaverse and the real world, it is expected that there will be limitations in equating it with reality. However, through the space expressed in the virtual world by people who are far away from the constraints of reality, we can indirectly know the wishes that we have not been able to express due to our lack of awareness.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.185-200
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• 2024

This study explored the changes in the elementary science teaching expertise of teachers who participated in an in-school professional learning community for elementary science instructional research. Six elementary school teachers from grades 4, 5, and 6 at an 18-class S elementary school in a medium-sized city in Chungcheongbuk-do conducted collaborative instructional research on elementary science lessons as part of an in-school professional learning community, which was held 26 times over 7 months in 2020. During the professional learning community, video and audio recordings of the activities, research lessons, course materials, and professional learning community reflection activities were collected for analysis. The collected data were analyzed using qualitative research methods; data processing, reading, note-taking, description, classification, interpretation, reporting, and visualization; and the instructional professionalism elements were extracted based on the instructional professionalism framework. In the early professional learning community activity stages, the participating teachers first discussed their teaching perspectives, their experiences, and their goals for teaching science, which resulted in a selection of research questions. The teachers then collaboratively designed and implemented research lessons for each grade level, after which lesson reflections were conducted. The teachers' abilities to engage in qualitative reflection on the research questions improved after each reflection iteration. It was found that this professional learning community collaborative lesson study experience positively contributed to teaching expertise development. Based on the study findings, the implications for using professional learning communities to improve elementary teachers' science teaching expertise are given.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.134-145
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• 2024

The purpose of this study was to propose a framework for developing test scenarios for issuance of conditional driver's licenses. The framework was composed of five stages. Initially, we reviewed the literature on traffic crash characteristics in terms of accident frequency and severity regarding the main factors of crashes caused by older drivers. In the second stage, the characteristics of crashes attributed to non-elderly, early elderly, and late elderly drivers were analyzed using data obtained from the Traffic Accident Analysis System (TAAS), and crash types for elderly drivers were derived. In the third stage, black box videos of high-risk crash types were analyzed to derive crash stories that described the circumstances in which crashes occurred. In the fourth step, crash situations were classified by rating the types of crash stories derived to develop various scenarios. Step 5 involved creating a scenario by applying the PEGASUS 5-Layer format, which has recently been used to develop test scenarios for autonomous vehicles. The results of this study are expected to be used as a basis for developing driving ability evaluation scenarios for the issuance of conditional driver's licenses.

• Journal of The Korean Association For Science Education
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• v.27 no.7
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• pp.592-608
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• 2007

This study explored the types of conceptual change of 'force' within middle school students' conceptual ecologies. This qualitative study was implemented with the use of classroom observations and two interviews with the participants. 11 middle school students (7 females and 4 males) joined in this study. The interviews with the participants were conducted individually before and after the 'force' unit. The collected data were all transcribed and analyzed interpretively. The results of this study consisted of two parts. First, the participants' conceptual ecologies of 'force' were categorized into 4: epistemological commitments (fixed or interactional explanatory consistency), analogy (attribute, working), metaphysical beliefs (people-oriented ontology, animism, causationism, mixed), and past experiences. Second, two representative cases including 'stable' and 'transitional' states were explained based on the interactions within their own conceptual ecologies. We can see students' conceptions with the integrated perspective in the sense that this results tried to get contextual and interactional understandings of the status of the conception and the possibilities of conceptual change. In addition, it implied that conceptual change research should have the perspective of conceptual ecology evolution in the future.

• Journal of Industrial Convergence
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• v.22 no.1
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• pp.137-148
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• 2024

This study aims to analyse the research trends and identify issues in elementary physical education in the new normal era. For this purpose, the taxonomic analysis method proposed by Spradley (2016) was applied, and 43 Korean academic articles were finally categorised and analysed. The findings are as follows. First, due to the changes in the educational environment caused by COVID-19, most of the remote and online physical education classes were conducted as content-oriented classes. It was found that there was a lack of communication between teachers and students in online physical education classes. Second, the difficulties of remote and online physical education classes and online and offline combined physical education classes, as well as research on how to overcome and improve them, were concentrated. Third, the need for evolution of physical education teachers and training of future professionals in line with the methodological transformation of primary physical education and the current situation was raised. In addition, the number of studies utilising blended learning, flipped learning, and new technologies, which have gained attention in primary physical education due to COVID-19, has increased. Based on the findings, we proposed the direction and future tasks of elementary physical education in the new normal era.

• Information Systems Review
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• v.21 no.4
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• pp.47-68
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• 2019

As cloud services and deployment models become diverse, there are a growing number of cloud computing selection options. Therefore, financial companies need a methodology to select the appropriated cloud for each financial computing system. This study adopted the Balanced Scorecard (BSC) framework to classify factors for the introduction of cloud computing in financial companies. Using Analytic Hierarchy Process (AHP), the evaluation items are layered into the performance perspective and the cloud consideration factor and a comprehensive decision model is proposed. To verify the proposed research model, a system of financial company is divided into three: account, information, and channel system, and the result of decision making by both financial business experts and technology experts from two financial companies were collected. The result shows that some common factors are important in all systems, but most of the factors considered are very different from system to system. We expect that our methodology contributes to the spread of cloud computing adoption.

• Information Systems Review
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• v.21 no.3
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• pp.111-129
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• 2019

Recently, artificial intelligence (AI)-enabled products and services such as smartphones, smart speakers, chatbots are being released due to advances in AI technology. Thus researchers making effort to reveal that consumers' intention to adopt AI-enabled products. Yet, little is known about the intended adoption of AI-enabled products. Because most of studies has been not consideredthe perceived utility value of consumers for each attribute by classified based on the characteristics of AI-enabled products. Therefore, the purpose of this study is to investigate the difference in importance between attributes that affect the intention to adopt of AI-enabled products. For this, first, identified and classified the attributes of AI-enabled products based on IS Success Model of DeLone and McLean. Second, measured the utility value of each attribute on the adoption of AI-enabled products through conjoint analysis. And we employed construal level theory to see whether there are differences in the relative importance of AI-enabled products attributes depending on the temporal distance. Third, we segmented the market based on the utility value of each respondent through cluster analysis and tried to understand the characteristics and needs of consumers in each segment market. We expect to provide theoretical implications for conceptually structured attributes and factors of AI-enabled products and practical implications for how development efforts of AI-enabled products are needed to reach consumers need for each segment.

• Information Systems Review
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• v.19 no.2
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• pp.185-209
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• 2017

In modern society, crime records have been digitized. Digital information is difficult to distinguish from original information, but the former is easy to modulate. This situation explains the increasing importance of digital forensics. However, digital forensic has several inefficiencies because of the rapid development of technology, unclear jurisdiction, and tool errors. This study surveyed digital forensic specialists and derived the priority of domestic digital forensic issues by redefining 17 issues in digital forensics from Brungs-Jamieson study in Australia. The present study was divided into four groups, namely, police, government and public corporations, private companies, and legal groups. The study could compare and analyze comparative analysis of existing studies in Australia and the US. This study can also examine differences in the results of each group in Korea. Thus, the key issues in Korea were derived as "Requirements to 'Fire Up' Original." The differences of the three groups in terms of legal issues were then identified. This finding enables us to understand differences in priorities and importance between groups and countries.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.78-88
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• 2024

Ship-radiated noise received by passive sonar that can measure underwater noise can be identified and classified ship using Detection of Envelope Modulation on Noise (DEMON) analysis. However, in a low Signal-to-Noise Ratio (SNR) environment, it is difficult to analyze and identify the target frequency line containing ship information in the DEMONgram. In this paper, we conducted a study to extract target frequency lines using semantic segmentation among deep learning techniques for more accurate target identification in a low SNR environment. The semantic segmentation models U-Net, UNet++, and DeepLabv3+ were trained and evaluated using simulated DEMONgram data generated by changing SNR and fundamental frequency, and the DEMONgram prediction performance of DeepShip, a dataset of ship-radiated noise recordings on the strait of Georgia in Canada, was compared using the trained models. As a result of evaluating the trained model with the simulated DEMONgram, it was confirmed that U-Net had the highest performance and that it was possible to extract the target frequency line of the DEMONgram made by DeepShip to some extent.

• Journal of Family Resource Management and Policy Review
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• v.28 no.1
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• pp.13-25
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• 2024

The rate of single-person households has been increasing all over the world, and there has been a particularly rapid increase in them in Korea. Single-person households show unique and various characteristics related to the reasons for becoming a single-person household, gender, life cycle, and so on. Thus, research needs to focus on the specific groups of single-person households in order to provide tailored policies and programs. This study segmented single-person households in three groups based on life cycle: young, middle-aged, and older adults. Differences in the level of healthy lifestyle, as well as factors affecting that, were investigated according to the groups. The data were collected in 2022, with 237 respondents from single-person households in Kimpo. Descriptive statistics, t-test, ANOVA, and multiple regression analysis were conducted. The overall level of healthy lifestyle was found to be significantly higher for young adults compared to older adults. Results from multiple regression show that significant factors related to the healthy lifestyle of single-person households were gender, educational attainment, whether becoming a single-person household was voluntary, and whether the respondents had experienced discrimination as a single-person household. Significant factors differed by the sub-categories of the healthy lifestyle scale. This study has implications related to discovering differences in the level of healthy lifestyles of single-person households through examining the factors affecting it according to life cycle.