• Title/Summary/Keyword: Collaborative Problem-Solving

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Suggestion of Community Design for the Efficiency of CPTED - Focused on Community Furniture - (범죄예방환경설계(CPTED)의 효율성 증대를 위한 커뮤니티디자인 제안 - 커뮤니티퍼니쳐를 중심으로 -)

  • Lee, Ho Sang
    • Korea Science and Art Forum
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    • v.29
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    • pp.305-318
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    • 2017
  • The need for recognizing the crime in the urban spaces as a social problem and finding out specific approaches such as the study of space design and various guidelines for crime prevention is increasing. In this regard, "Crime Prevention Through Environmental Design" (marked as "CPTED") is actively underway. Yeomri-dong Salt Way is the first place to which the Seoul Crime Prevention Design Project was appled. The business objective of improving the local environment has been implemented rationally through cooperation and voluntary participation between subject of the project executives and community members. Since its efficiency has been proven, the sites have been expanded since then and becomes a benchmarking example of each local government.This kind of problem solving effort has the same context in purpose and direction of the 'Village Art Project' which has been implemented since 2009 with the aim of promoting the culture of the underdeveloped area and encouraging the participation of the residents by introducing the public art. It is noteworthy that this trend is centered around the characteristics of community functions and values. The purpose of this study is to propose the application method of community furniture as a way to increase the efficiency of CPTED to improve the 'quality of life' of residents. To do this, we reviewed CPTED, community design, public art literature and prior research, and identified the problems and implications based on the site visit Yeomri-dong of Seoul and Gamcheon Village of Pusan which is the successful model of "Seoul Root out Crime by Design" and 'Maeulmisul Art Project' respectively. The common elements of the two case places identified in this study are as follows: First, the 'lives' of community residents found its place in the center through the activation of community by collaborative activities in addition to the physical composition of the environment. Second, community design and introduction of public art created a new space, and thereby many people came to visit the village and revitalize the local economy. Third, it strengthened the natural monitoring, the territoriality and control, and the activity increase among the CPTED factors. The psychological aspect of CPTED and the emotional function of public art are fused with the 'community furniture', thereby avoiding a vague or tremendous approach to the public space through a specific local context based on the way of thinking and emotion of local people and it will be possible to create an environment beneficial for all. In this way, the possibility and implication of the fusion of CPTED and public art are expected to be able to reduce the social cost through the construction of the crime prevention infrastructure such as expansion of the CPTED application space, and to suggest a plan to implement the visual amenity as a design strategy to regenerate city.

A Study on the Effect of Network Centralities on Recommendation Performance (네트워크 중심성 척도가 추천 성능에 미치는 영향에 대한 연구)

  • Lee, Dongwon
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.23-46
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    • 2021
  • Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

A Case Study on the Community-based Elderly Care Services Provided by the Social Economy Network in Gwangjin-Gu, Seoul (사회적경제 조직의 지역사회 돌봄 네트워킹 가능성에 대한 비판적 고찰: 서울시 광진구 노인돌봄 클러스터 사례연구)

  • Kim, HyoungYong;Han, EunYoung
    • 한국노년학
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    • v.38 no.4
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    • pp.1057-1081
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    • 2018
  • This study analyzed the case of elderly care cluster in Gwangjin-gu to explore the possibilities of social economy as a provider of community-based social services. Community-based means the approach by which community organizations build a voluntary and collaborative network to enhance collective problem-solving abilities. Therefore, it is very likely that the social economy that emphasizes people, labor, community, and democratic principles can contribute to community-based social services. This study analyzed social economic network by using four characteristics of social economy suggested by OECD community economy and employment program as an analysis framework. The results of this study are as follows: First, it is found that social economy would hardly supply community-based social services through network cooperation because of a large variation in community identity, investment to new product, and labor protection. Second, community users are not the consumers of the social economy and the products of the social economy stay in market products only for the organizations in social economy. In order to create good services that meet the needs of residents, community development approaches are required at the same time. The importance of community space where local residents and social economy meet is derived. Third, public support such as purchasing support has weakened the ecosystem of social economy by making the distinction between public economy and social economy more obscure. On the other hand, public investment in community infrastructure is an indirect aid to social economy to communicate with residents and to promote good supply and consumption. In the end, community-based social services need a platform where the social economy and the people meet. This type of public investment can create the ecosystem of the social economy.

An Analysis of the Trends in Academic Research on Invention Gifted Education (발명영재교육에 관한 학술연구 동향 분석)

  • Lee Minhye;Hillenblink Maximilian Ludwig
    • Journal of the International Relations & Interdisciplinary Education
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    • v.3 no.1
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    • pp.1-28
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    • 2023
  • This study was conducted to examine the quantitative trend of domestic studies in invention gifted education, identify the intrinsic meaning and connection attributes in these research analysis, and provide basic data to explore future development plans. To this end, 97 domestic academic papers were finally selected as "Invention Gifted Education" by the Korea Research and Information Service (RISS), technical statistical analysis was conducted with SPSS on publication year, author composition, researcher's affiliation and location area, and published journal. The trend, which had been on the rise since 2007, confirmed by academic papers on gifted education in invention, peaked at the time of the 3rd comprehensive plan for gifted education and has since declined again. As a result of technical statistical analysis of the author's characteristics, half of the papers were jointly published, followed by a number of independent authors. The papers published alone were identified as belonging to universities, research institutes, elementary schools, and middle schools, and the cooperative papers were many studies cooperated with young researchers and professional researchers, and only one collaborative study was conducted between young researchers. When looking at the regions and journals in which the Invention Gifted Education thesis was published, it was concentrated in some regions or journals, and the deviation was very large. As a result of language network analysis using academic paper keywords, creativity and programs were identified as meaningful keywords that showed top appearance, and the keyword pair with high co-appearance was invention gifted-creativity. The keyword of connection-centeredness at the top served as an intermediary for creativity, problem-solving, development, and company to expand to other research topics, and served as a research topic that could be expanded to various topics. In the case of mediation-centeredness, creativity, programs, and effects showed high mediation-centeredness, indicating that it is an important keyword that plays a role in mediating or mediating other keywords. Through these research results, national policy measures need to be prepared for the development of gifted education, and the need to create an invention ecological culture that can enhance teachers' expertise while increasing social responsibility for gifted education.

Characteristics and Changes in Scientific Empathy during Students' Productive Disciplinary Engagement in Science (학생들의 생산적 과학 참여에서 발현되는 과학공감의 특성과 변화 분석)

  • Heesun, Yang;Seong-Joo, Kang
    • Journal of The Korean Association For Science Education
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    • v.44 no.1
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    • pp.11-27
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    • 2024
  • This study aimed to investigate the role of scientific empathy in influencing students' productive disciplinary engagement in scientific activities and analyze the key factors of scientific empathy that manifest during this process. Twelve fifth-grade students were divided into three subgroups based on their general empathic abilities. Lessons promoting productive disciplinary engagement, integrating design thinking processes, were conducted. Subgroup discourse analysis during idea generation and prototype stages, two of five problem-solving steps, enabled observation of scientific empathy and practice aspects. The results showed that applying scientific empathy effectively through design thinking facilitated students' productive disciplinary engagement in science. In the idea generation stage, we observed an initial increase followed by a decrease in scientific empathy and practice utterances, while during the prototyping stage, utterance frequency increased, particularly in the later part. However, subgroups with lower empathic abilities displayed decreased discourse frequency in scientific empathy and practice during the prototype stage due to a lack of collaborative communication. Across all empathic ability levels, the students articulated all five key factors of scientific empathy through their utterances in situations involving productive science engagement. In the high empathic ability subgroup, empathic understanding and concern were emphasized, whereas in the low empathic ability subgroup, sensitivity, scientific imagination, and situational interest, factors of empathizing with the research object, were prominent. These results indicate that experiences of scientific empathy with research objects, beyond general empathetic abilities, serve as a distinct and crucial factor in stimulating diverse participation and sustaining students' productive engagement in scientific activities during science classes. By suggesting the potential multidimensional impact of scientific empathy on productive disciplinary engagement, this study contributes to discussions on the theoretical structure and stability of scientific empathy in science education.

Pareto Ratio and Inequality Level of Knowledge Sharing in Virtual Knowledge Collaboration: Analysis of Behaviors on Wikipedia (지식 공유의 파레토 비율 및 불평등 정도와 가상 지식 협업: 위키피디아 행위 데이터 분석)

  • Park, Hyun-Jung;Shin, Kyung-Shik
    • Journal of Intelligence and Information Systems
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    • v.20 no.3
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    • pp.19-43
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    • 2014
  • The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.