• Proceedings of the Technology Innovation Conference
• /
• 1999.12a
• /
• pp.197-215
• /
• 1999

With the advent of knowledge-based economy and information society, information and telecommunications(IT) industry is reckoned as the crucial sector for the creation and diffusion of technological knowledge. In this study, we analyze the process of 'industrialization of IT'and 'informatization of industries' based on the technology linkage structure, or technological knowledge network. The former is defined as the process whereby IT industry absorbs technological knowledge from other industries to grow as an independent industrial sector. The latter is defined as the process whereby other industries adopt IT technology to enhance productivity and upgrade industrial structure, We employ the R&D stock as a proxy for technological knowledge of respective industries and measure the flow of technological knowledge between industries in terms of I/O relationship. By applying the network analysis, we examine the changing pattern of technology linkage structure of the Korean industry throughout the years from 1983 to 1997. Some policy implications are presented based on the findings from the analysis.

• Journal of Internet Computing and Services
• /
• v.16 no.6
• /
• pp.39-46
• /
• 2015

Knowledge space theory is a theory that provides a guidelines for human learners' possible education decisions and has been used in various educational environment. However, traditional methodologies using the knowledge space theory have always depended on handwork system and it is necessary to learn programming language such as Visual Basic and R, causing time consuming situations. In order to overcome those issues on the environment of education we propose a new Knowledge Structure Analysis System that not just analyzes learners' knowledge structures automatically but to provide critical learning path for the learners based on knowledge space theory. Proposed system is implemented by using rApache generating critical learning path computing Chi-square value. This provides an automatic way of analyzing knowledge structure in learners' knowledge space and shows systematic reviews for the knowledge space.

• International conference on construction engineering and project management
• /
• 2011.02a
• /
• pp.550-555
• /
• 2011

Utilizing construction knowledge and experiences in design phase can reduce change orders and improve productivity in construction phase. To do so, information must be made available to the design team in time. Current approaches for effective utilization of constructability knowledge, however, only focus on the formalization of constructability knowledge such as a checklist, which lacks the consideration of the appropriate use at the proper point in time. The inadequate use of constructability knowledge can result in unnecessary reworks. To deal with this problem, the design team needs to know what constructability knowledge is required for specific design activities in the design process. This paper presents a constructability implementation model using the dependency structure matrix (DSM) that focuses on information flows between design activities and constructability knowledge. For this objective, design activities in the design process are modeled in a matrix form based on their dependency. Then, constructability knowledge, which needs to be considered in the design stage, is mapped into activities and incorporated into the matrix, creating Constructability-DSM (C-DSM). Next, the partitioning algorithm is applied to C-DSM for optimal information flow. The Partitioned C-DSM is then analyzed based on the relationship between activities. Finally, the optimal utilization of construction knowledge in the design process is determined by identifying what constructability knowledge is required for each design activity, and how and when it is reflected to design for constructability. Thus, this research can help provide robust control actions to reduce unnecessary iterative cycles in design process for efficient constructability implementation.

• Journal of The Korean Association For Science Education
• /
• v.27 no.4
• /
• pp.346-353
• /
• 2007

In order to be efficient in teaching, a teacher should understand the current learner's level through diagnostic evaluation. This study has examined the major issues arising from the noble diagnostic assessment tool based on the theory of knowledge space. The knowledge state analysis method is actualizing the theory of knowledge space for practical use. The knowledge state analysis method is very advantageous when a certain group or individual student's knowledge structure is analyzed especially for strong hierarchical subjects such as mathematics, physics, chemistry, etc. Students' knowledge state helps design an efficient teaching plan by referring their hierarchical knowledge structure. The knowledge state analysis method can be enhanced by computer due to fast data processing. In addition, each student's knowledge can be improved effectively through individualistic feedback depending on individualized knowledge structure. In this study, we have developed a diagnostic assessment test for measuring student's learning outcome which is unattainable from the conventional examination. The diagnostic assessment test was administered to middle school students and analyzed by the knowledge state analysis method. The analyzed results show that students' knowledge structure after learning found to be more structured and well-defined than the knowledge structure before the learning.

• Journal of Korean Library and Information Science Society
• /
• v.36 no.1
• /
• pp.459-477
• /
• 2005

The purpose of this study is to investigate a fundamental model for categories and relationships among concepts in library and information science field in order to construct an ontology based upon the knowledge construct of human being. Questionnaire and interview were involved for this study, The results shows that students' knowledge structure was different from KDC and DDC schemes. Students had an object oriented knowledge structure and provided four relationship models. These model could provide a fundamental data for ontology construction. Also, it shows that student academic grades influenced their knowledge structures.

• Journal of Korean Academy of Nursing
• /
• v.41 no.5
• /
• pp.623-632
• /
• 2011

Purpose: This study was done to explore the knowledge structure of Korean Nursing Science. Methods: The main variables were key words from the research papers that were presented in the Journal of Korean Academy of Nursing and journals of the seven branches of the Korean Academy of Nursing. English titles and abstracts of the papers (n=5,936) published from 1995 through 2009 were included. Noun phrases were extracted from the corpora using an in-house program (BiKE Text Analyzer), and their co-occurrence networks were generated via a cosine similarity measure, and then the networks were analyzed and visualized using Pajek, a Social Network Analysis program. Results: With the hub and authority measures, the most important research topics in Korean Nursing Science were identified. Newly emerging topics by three-year period units were observed as research trends. Conclusion: This study provides a systematic overview on the knowledge structure of Korean Nursing Science. The Social Network Analysis for this study will be useful for identifying the knowledge structure in Nursing Science.

• Journal of Korean Academy of Nursing
• /
• v.46 no.1
• /
• pp.50-58
• /
• 2016

Purpose: The purpose of this study was to identify the knowledge structure of cancer survivors. Methods: For data, 1099 articles were collected, with 365 keywords as a Noun phrase extracted from the articles and standardized for analyzing. Co-occurrence matrix were generated via a cosine similarity measure, and then the network analysis and visualization using PFNet and NodeXL were applied to visualize intellectual interchanges among keywords. Results: According to the result of the content analysis and the cluster analysis of author keywords from cancer survivors articles, keywords such as 'quality of life', 'breast neoplasms', 'cancer survivors', 'neoplasms', 'exercise' had a high degree centrality. The 9 most important research topics concerning cancer survivors were 'cancer-related symptoms and nursing', 'cancer treatment-related issues', 'late effects', 'psychosocial issues', 'healthy living managements', 'social supports', 'palliative cares', 'research methodology', and 'research participants'. Conclusion: Through this study, the knowledge structure of cancer survivors was identified. The 9 topics identified in this study can provide useful research direction for the development of nursing in cancer survivor research areas. The Network analysis used in this study will be useful for identifying the knowledge structure and identifying general views and current cancer survivor research trends.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.31 no.4
• /
• pp.89-103
• /
• 2006

The purpose of this study is to examine influential factors in knowledge-sharing and to analyze how these factors influence the performances of knowledge management (KM) in public enterprises. Influencing factors of KM in this study include evaluation-compensation, knowledge management system, learning culture, and organizational structures. As a result, analysis turned out to be the KM system and organizational structure directly effects knowledge-sharing and KM performances. And knowledge-sharing performed as mediating effect between independent variables such as compensation system and organization structure, and dependent variable like KM performance. Therefore, this study concludes that each factor of evaluation-compensation system and learning culture has directly influenced to knowledge-sharing, yet KM performances have Indirectly influenced.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.10
• /
• pp.173-180
• /
• 2018

In this paper, we analyzed key keywords and research themes in the field of defense research using keyword network analysis and tried to grasp the whole knowledge structure. To do this, we extracted data from 2,165 research data from defense related research institutes from 2010 to 2017 and applied the Pareto rule to the number of abstracts of words and the number of links between words, We extracted a total of 2,303 words based on the criterion and extracted 204 final key words through component analysis. By analyzing the centrality and cohesiveness through these key words, we confirmed the concept of core research in the defense field and derived a total of 7 large groups and 16 small groups of each group in the knowledge structure of the defense area.

• Journal of the Korean Applied Science and Technology
• /
• v.39 no.6
• /
• pp.738-747
• /
• 2022

The purpose of this study is to construct a knowledge structure for the application of physical education in ecological marine sports. As specific exercises, a volleyball game (beach volleyball) and open water swimming were set, and a knowledge structure analysis framework was used for the study. Expert consultation was conducted to secure the validity of the study. The study results are as follows. First, a knowledge structure based on the 2022 revised physical education curriculum was prepared. Second, the basis for the application of physical education classes for ecological marine sports was prepared. Third, learning contents in the knowledge·understanding domain, process·functional domain, and value·attitude domain of beach volleyball were proposed. Fourth, learning contents of knowledge·understanding domain, process·function domain, and value·attitude domain of sea swimming were proposed. This study is meaningful in that it prepared in advance for the realization of the 2022 revised physical education curriculum to be introduced in the future.