• The Journal of Korean Academic Society of Nursing Education
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• 제17권2호
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• pp.226-234
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• 2011

Purpose: The purpose of this study was to identify the effect of a simulation-based practice on clinical performance and problem solving processes for nursing students. Method: The study used a one group pre-post test design. Students experienced a simulation-based practice that included team base learning, skill training, taking a high-fidelity simulation with SimMan 3G, and also being debriefed for 12 weeks (August 2010 to December 2010). The pre-test and post-test were conducted to compare the differences in knowledge, clinical nursing skills, and problem solving processes. Result: After students had received the simulation-based practice, they showed statistically significant higher knowledge (t=14.73, p<.001) and clinical nursing skills (t=15.47, p<.001) than before. However, there was no significant difference in the problem solving process score (t=1.53, p=.127). Conclusion: This study showed that knowledge and clinical nursing skills were significantly improved by the simulation-based practice. Further research would be required to identify how the problem solving process that uses simulation-based practice could be developed further.

• Journal of the Korean BIBLIA Society for library and Information Science
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• 제25권1호
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• pp.39-60
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• 2014

In domestic university libraries, the difference between the knowledge resource collection activities on campus is depending on the size of the university, and their collection is concentrated on some types of digital resources. In recent years, the main universities in developed countries has developed actively in social openness and share activities of their knowledge resources, through the OA-based institutional repository, for the purpose of image improvement and competitiveness as a knowledge production base. This study examined ways to improve the relevant regulations in order to effectively collect and systematically manage the knowledge resources from graduate school, research institutes, center for teaching and learning, e-learning center, museum, press, a variety of campus organizations, so as to enhance the role of the library as the right manager of knowledge resources on campus. To this end, this study, considering the improvement of relevant regulations, investigates the operating situation of the library regulations of 176 universities and suggests necessary improvement methods in order to facilitate the digital legal deposit and expand its scope.

• KIPS Transactions on Software and Data Engineering
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• 제6권4호
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• pp.193-202
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• 2017

Development of Intelligent Systems involves effective integration of large-scaled knowledge processing and understanding, human-machine interaction, and intelligent services. Especially, in our project for development of a self-growing knowledge-based system with inference methodologies utilizing the big data technology, we are building a platform called WiseKB as the central knowledge base for storing massive amount of knowledge and enabling question-answering by inferences. WiseKB thus requires an effective methodology to analyze diverse requirements convoluted with the integration of various components of knowledge representation, resource management, knowledge storing, complex hybrid inference, and knowledge learning, In this paper, we propose an integrated requirement analysis method that blends the traditional sequential method and the iterative-incremental method to achieve an efficient requirement analysis for large-scale systems.

• Transactions of the Korean Society of Mechanical Engineers
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• 제14권5호
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• pp.1138-1146
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• 1990

A knowledge-based expert system has been developed implementing the ambiguous process of conceptual design of flywheels in earlier design stage to assist the selection of proper flywheel types and dimensions. Knowledge for the flywheel design consists of the rules for conventional as well as super flywheels and other informations required for the design process. Those knowledges were extracted from literatures and some experts in the field. With these knowledges, an integrated knowledge based expert system was developed to help users with informations and facilities to design flywheels interactively using a commercial package of knowledge-based system called INSIGHT2 of backward chaining and proprietary package of forward chaining written in LISP language. The developed system consists of the knowledge base part and calculation park : the first one consists of main module and user level modules and the other one is to assist in analyzing the stress distribution in the flywheels and deciding the flywheel dimensions and specifications for various types of flywheels using proper data bases and graphic facilities. With this flywheel design software, several examples were tried generating acceptable design results.

• The Journal of Society for e-Business Studies
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• 제24권3호
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• pp.87-98
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• 2019

As artificial intelligence is actively studied, it is being applied to various fields such as image, video and natural language processing. The natural language processing, in particular, is being studied to enable computers to understand the languages spoken and spoken by people and is considered one of the most important areas in artificial intelligence technology. In natural language processing, it is a complex, but important to make computers learn to understand a person's common sense and generate results based on the person's common sense. Knowledge graphs, which are linked using the relationship of words, have the advantage of being able to learn common sense easily from computers. However, the existing knowledge graphs are organized only by focusing on specific languages and fields and have limitations that cannot respond to neologisms. In this paper, we propose an intelligent chatbotsystem that collects and analyzed data in real time to build an automatically scalable knowledge graph and utilizes it as the base data. In particular, the fine-tuned BERT-based for relation extraction is to be applied to auto-growing graph to improve performance. And, we have developed a chatbot that can learn human common sense using auto-growing knowledge graph, it verifies the availability and performance of the knowledge graph.

• Journal of The Korean Association For Science Education
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• 제28권6호
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• pp.618-632
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• 2008

Despite the rapidly growing body of research on science teachers' pedagogical content knowledge (PCK), most of the research has mainly focused on the definition of PCK and its components. The main purpose of this research was to explore the operational definition of PCK and to suggest another form by re-conceptualizing PCK, with the newly defined and conceptualized PCK capable of being used as standards and/or criteria in selecting the curricular content of and deciding the subject area of science teacher education. In this research, the science teachers' PCK was defined as the "practical knowledge and skills that are acquired through the curriculum of science education and in the course of teaching experiences, and which are used in their teaching of secondary school science." The science teachers' PCK was further defined as consisting of two integrated and/or combined dimensions: subject matter and pedagogy, each of which comprises several components. In this paper, the PCK is called science education literacy. The paper also presents the ways to apply the operational definition of PCK and re-conceptualized PCK and a few suggestions for the research on science teachers' PCK.

• Journal of Korean Elementary Science Education
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• 제25권4호
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• pp.430-453
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• 2006

The purpose of this study was to explore how an elementary school teacher developed PCK by utilizing her knowledge domains in teaching practice, regarding the specific science topic of 'animals:' A case study approach was adopted with the participation of a 1st grade teacher, in a poor urban neighborhood elementary school in NYC. Data was collected through interview and the participant observation method in order to investigate: a) the teacher's existing knowledge base in terms of subject matter knowledge, pedagogical knowledge and contextual knowledge; b) how she develops PCK during classroom practice, centering on the relationship between knowledge domains. The findings illustrate the ways in which the three knowledge domains are closely related and developed as PCK through the whole teaching process. In particular, the findings indicate that the teacher's contextual knowledge plays a critical role in shaping and developing PCK. Before instruction, her contextual knowledge regarding the administrative policies and the school test system in the district enabled her to make decisions and plans about teaching science. During classroom teaching, her knowledge of students' sociocultural backgrounds and living conditions in the urban setting helped her to identify specific teaching strategies and resources suitable to the students' needs and interests. The study results imply that science instruction can be more feasible in meeting the demands of particular groups of students if teachers make an effort to become knowledgeable about their own teaching context and utilize it in developing their PCK.

• Journal of Intelligence and Information Systems
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• 제18권2호
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• pp.61-83
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• 2012

A knowledge map describes the network of related knowledge into the form of a diagram, and therefore underpins the structure of knowledge categorizing and archiving by defining the relationship of the referential navigation between knowledge. The referential navigation between knowledge means the relationship of cross-referencing exhibited when a piece of knowledge is utilized by a user. To understand the contents of the knowledge, a user usually requires additionally information or knowledge related with each other in the relation of cause and effect. This relation can be expanded as the effective connection between knowledge increases, and finally forms the network of knowledge. A network display of knowledge using nodes and links to arrange and to represent the relationship between concepts can provide a more complex knowledge structure than a hierarchical display. Moreover, it can facilitate a user to infer through the links shown on the network. For this reason, building a knowledge map based on the ontology technology has been emphasized to formally as well as objectively describe the knowledge and its relationships. As the necessity to build a knowledge map based on the structure of the ontology has been emphasized, not a few researches have been proposed to fulfill the needs. However, most of those researches to apply the ontology to build the knowledge map just focused on formally expressing knowledge and its relationships with other knowledge to promote the possibility of knowledge reuse. Although many types of knowledge maps based on the structure of the ontology were proposed, no researches have tried to design and implement the referential navigation-enabled knowledge map. This paper addresses a methodology to build the ontology-based knowledge map enabling the referential navigation between knowledge. The ontology-based knowledge map resulted from the proposed methodology can not only express the referential navigation between knowledge but also infer additional relationships among knowledge based on the referential relationships. The most highlighted benefits that can be delivered by applying the ontology technology to the knowledge map include; formal expression about knowledge and its relationships with others, automatic identification of the knowledge network based on the function of self-inference on the referential relationships, and automatic expansion of the knowledge-base designed to categorize and store knowledge according to the network between knowledge. To enable the referential navigation between knowledge included in the knowledge map, and therefore to form the knowledge map in the format of a network, the ontology must describe knowledge according to the relation with the process and task. A process is composed of component tasks, while a task is activated after any required knowledge is inputted. Since the relation of cause and effect between knowledge can be inherently determined by the sequence of tasks, the referential relationship between knowledge can be circuitously implemented if the knowledge is modeled to be one of input or output of each task. To describe the knowledge with respect to related process and task, the Protege-OWL, an editor that enables users to build ontologies for the Semantic Web, is used. An OWL ontology-based knowledge map includes descriptions of classes (process, task, and knowledge), properties (relationships between process and task, task and knowledge), and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. Therefore a knowledge network can be automatically formulated based on the defined relationships, and the referential navigation between knowledge is enabled. To verify the validity of the proposed concepts, two real business process-oriented knowledge maps are exemplified: the knowledge map of the process of 'Business Trip Application' and 'Purchase Management'. By applying the 'DL-Query' provided by the Protege-OWL as a plug-in module, the performance of the implemented ontology-based knowledge map has been examined. Two kinds of queries to check whether the knowledge is networked with respect to the referential relations as well as the ontology-based knowledge network can infer further facts that are not literally described were tested. The test results show that not only the referential navigation between knowledge has been correctly realized, but also the additional inference has been accurately performed.

• Asia pacific journal of information systems
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• 제18권4호
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• pp.57-81
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• 2008

Knowledge is an essential strategic weapon for sustaining competitive advantage and is the key determinant for organizational growth. When knowledge is shared and disseminated throughout the organization, it increases an organization's value by providing the ability to respond to new and unusual situations. The growing importance of knowledge as a critical resource has forced executives to pay attention to their organizational knowledge. Organizations are increasingly undertaking knowledge management initiatives and making significant investments. Knowledge sourcing is considered as the first important step in effective knowledge management. Most firms continue to make an effort to realize the benefits of knowledge management by using various knowledge sources effectively. Appropriate knowledge sourcing strategies enable organizations to create, acquire, and access knowledge in a timely manner by reducing search and transfer costs, which result in better firm performance. In response, the knowledge management literature has devoted substantial attention to the analysis of knowledge sourcing strategies. Many studies have categorized knowledge sourcing strategies into intemal- and external-oriented. Internal-oriented sourcing strategy attempts to increase firm performance by integrating knowledge within the boundary of the firm. On the contrary, external-oriented strategy attempts to bring knowledge in from outside sources via either acquisition or imitation, and then to transfer that knowledge across to the organization. However, the extant literature on knowledge sourcing strategies focuses primarily on large organizations. Although many studies have clearly highlighted major differences between large and small firms and the need to adopt different strategies for different firm sizes, scant attention has been given to analyzing how knowledge sourcing strategies affect firm performance in small firms and what are the differences between small and large firms in the patterns of knowledge sourcing strategies adoption. This study attempts to advance the current literature by examining the impact of knowledge sourcing strategies on small firm performance from a holistic perspective. By drawing on knowledge based theory from organization science and complementarity theory from the economics literature, this paper is motivated by the following questions: (1) what are the adoption patterns of different knowledge sourcing strategies in small firms (i,e., what sourcing strategies should be adopted and which sourcing strategies work well together in small firms)?; and (2) what are the performance implications of these adoption patterns? In order to answer the questions, this study developed three hypotheses. First hypothesis based on knowledge based theory is that internal-oriented knowledge sourcing is positively associated with small firm performance. Second hypothesis developed on the basis of knowledge based theory is that external-oriented knowledge sourcing is positively associated with small firm performance. The third one based on complementarity theory is that pursuing both internal- and external-oriented knowledge sourcing simultaneously is negatively or less positively associated with small firm performance. As a sampling frame, 700 firms were identified from the Annual Corporation Report in Korea. Survey questionnaires were mailed to owners or executives who were most erudite about the firm s knowledge sourcing strategies and performance. A total of 188 companies replied, yielding a response rate of 26.8%. Due to incomplete data, 12 responses were eliminated, leaving 176 responses for the final analysis. Since all independent variables were measured using continuous variables, supermodularity function was used to test the hypotheses based on the cross partial derivative of payoff function. The results indicated no significant impact of internal-oriented sourcing strategies while positive impact of external-oriented sourcing strategy on small firm performance. This intriguing result could be explained on the basis of various resource and capital constraints of small firms. Small firms typically have restricted financial and human resources. They do not have enough assets to always develop knowledge internally. Another possible explanation is competency traps or core rigidities. Building up a knowledge base based on internal knowledge creates core competences, but at the same time, excessive internal focused knowledge exploration leads to behaviors blind to other knowledge. Interestingly, this study found that Internal- and external-oriented knowledge sourcing strategies had a substitutive relationship, which was inconsistent with previous studies that suggested complementary relationship between them. This result might be explained using organizational identification theory. Internal organizational members may perceive external knowledge as a threat, and tend to ignore knowledge from external sources because they prefer to maintain their own knowledge, legitimacy, and homogeneous attitudes. Therefore, integrating knowledge from internal and external sources might not be effective, resulting in failure of improvements of firm performance. Another possible explanation is small firms resource and capital constraints and lack of management expertise and absorptive capacity. Although the integration of different knowledge sources is critical, high levels of knowledge sourcing in many areas are quite expensive and so are often unrealistic for small enterprises. This study provides several implications for research as well as practice. First this study extends the existing knowledge by examining the substitutability (and complementarity) of knowledge sourcing strategies. Most prior studies have tended to investigate the independent effects of these strategies on performance without considering their combined impacts. Furthermore, this study tests complementarity based on the productivity approach that has been considered as a definitive test method for complementarity. Second, this study sheds new light on knowledge management research by identifying the relationship between knowledge sourcing strategies and small firm performance. Most current literature has insisted complementary relationship between knowledge sourcing strategies on the basis of data from large firms. Contrary to the conventional wisdom, this study identifies substitutive relationship between knowledge sourcing strategies using data from small firms. Third, implications for practice highlight that managers of small firms should focus on knowledge sourcing from external-oriented strategies. Moreover, adoption of both sourcing strategies simultaneousiy impedes small firm performance.

• KIPS Transactions on Software and Data Engineering
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• 제9권3호
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• pp.91-100
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• 2020

Unlike the existing Visual Question Answering(VQA) problems, the new Visual Commonsense Reasoning(VCR) problems require deep common sense reasoning for answering questions: recognizing specific relationship between two objects in the image, presenting the rationale of the answer. In this paper, we propose a novel deep neural network model, KG_VCR, for VCR problems. In addition to make use of visual relations and contextual information between objects extracted from input data (images, natural language questions, and response lists), the KG_VCR also utilizes commonsense knowledge embedding extracted from an external knowledge base called ConceptNet. Specifically the proposed model employs a Graph Convolutional Neural Network(GCN) module to obtain commonsense knowledge embedding from the retrieved ConceptNet knowledge graph. By conducting a series of experiments with the VCR benchmark dataset, we show that the proposed KG_VCR model outperforms both the state of the art(SOTA) VQA model and the R2C VCR model.