• Journal of The Korean Association of Information Education
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• v.19 no.2
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• pp.225-232
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• 2015

The goal of this study is to assess the effects of Scratch programming classes on preservice teachers by using computational thinking and cognitive evaluations based on Bloom's taxonomy. To pursue this research goal we measured preservice teachers' programming skills using cognitive evaluation items based on Bloom's taxonomy after preservice teachers took one-semester Scratch programming course. In addition, a survey focused on computational thinking (CT) concepts, CT practices, and CT perspectives was conducted. We also conducted artifact-based interviews to unpack preservice teachers' experiences of working on team projects and analyzed their experiences qualitatively. The results of this study are meaningful because we assessed preservice teachers' experiences comprehensively with both quantitative and qualitative methods. In addition, this study provides us with implications for evaluation perspectives in designing programming courses for preservice teachers by adopting Bloom's taxonomy scheme.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.73-84
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• 2020

The whole world is making a variety of efforts to cope with the revolutionary changes in the economy and society that are emerging from intelligent information technology. Therefore, this study defined national public officials' intelligence information competency in the intelligent information society, and tried to derive competency clusters and sub-elements. To achieve this objective, this study explores literature research about bloom's digital taxonomy, information competency, and national ICT policies and national public officials' intelligence information competency was defined based on bloom's digital taxonomy perspective was modified and supplemented with this study and provisional constituent elements of competency were derived. In addition, 5 experts verified the content validity. As a result, 7 competency clusters and 22 sub-elements are finally derived. The findings of this study are expected to be useful as the basis for the national intelligence information human resource development.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.4
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• pp.297-322
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• 2014

The purpose of this study is to analyse the meaning and lexical morpheme of author keywords of humanities, social sciences, and art and sport in the Korea Ciation Index (KCI) and to propose a conceptual taxonomy of the author keywords. Four top-level concept categories such as 'Substance, Abstraction, General/Common, and Object' are replaced by seven more concrete categories such as 'object, action/function, property, theory/method, format/framework, general/common, and Instance'. In the middle and lower-level concept categories, the hierarchical structure is simplified and the unbalance of term distribution is reduced by creating, subdivision, integration, elimination, and movement of the categories. The result of the test based on the STNet shows that the replaced taxonomy of concept categories has the effects of making the term allocation more balanced and properties of terms more detailed.

• Journal of Information Management
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• v.40 no.2
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• pp.71-94
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• 2009

Indexing images using traditional indexing methods like taxonomy is not always efficient because of its visual content. This study examined how to apply folksonomies to image retrieval. To do this, first, we developed a category model for image tags found in Flickr. The model includes five categories and seventeen subcategories. Second, in order to evaluate the usefulness of the model to represent the various image tags as well as to investigate the end-user tagging behavior, three researchers classified the sampled image tags(141 most popular tags, 105 tags on three individual tag clouds and 3,848 image tags assigned on 156 images) according to the model. Finally, based on the research results, we proposed three methods for efficient image retrieval: extending folksonomies by combining them with ontologies; improving image retrieval efficiency using visual content and folksonomies; and updating taxonomy using folksonomies.

• Journal of the Korean Society for information Management
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• v.27 no.2
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• pp.157-171
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• 2010

This exploratory study outlines the rationalization of why Ontology's taxonomy requires a strong hierarchy, accuracy, and interoperability in order to be used as a successfully re-useable information management system. Finding the relevant information in a plethora of possible resources by bridging the gap between the user's needs and the resources of the information technology system is the goal that the information management field should find a way to achieve. This study is based on discussions and interviews with a taxonomist, information architect, and information manager, whose discussions were based on the usability and interoperability of the knowledge based information systems. These professional perspectives are necessary as they are the liaison between users and the information technology group. We found that in order for information managers to ensure successful sharing of knowledge across the end users, a common sense language must be issued in order to achieve reasoning for the artificial intelligence system.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.75-94
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• 2010

This study designed a pilot system in which queries can be expanded through a tag ontology where equivalent, synonymous, or related tags are bound together, in order to improve the retrieval effectiveness of videos. We evaluated the proposed pilot system by comparing it to a tag-based system without tag control, in terms of recall and precision rates. Our study results showed that the mean recall rate in the structured folksonomy-based system was statistically higher than that in the tag-based system. On the other hand, the mean precision rate in the structured folksonomy-based system was not statistically higher than that in the tag-based system. The result of this study can be utilized as a guide on how to effectively use tags as social metadata of digital video libraries.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.81-107
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• 2015

This study describes the Bottom-up method for implementation of an ontology system from the RDB. The STNet, a structured terminology glossary based on RDB, was served as a test bed for converting to RDF ontology, for generating the inference rules, and for evaluating the results of the semantic search. We have used protege editor of the ontology developing tool to design ontologies with test data. We also tested the designed ontology with the Inference Engine (Pellet) of protege editor. The generated reference rules were tested by TBox and SPARQL queries through STNet ontology. The results of test show that the generated reference rules were verified as true and STNet ontology were also evaluated to be useful for searching the complex combination of semantic relation.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.433-441
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• 2020

The advent of the intelligent information society and artificial intelligence education for fostering future talents is attracting the attention of the education community, and the AI graduate course for teachers is also being opened and operated. The curriculum of the AI education graduate school, which was established this year, is self-contained considering the conditions of each university. Are organized. Accordingly, this study seeks to explore the direction of curriculum development so that AI curriculum that can be more effective and enhance educational value in the graduate school of education can be developed in the future. Based on the Backward design, the AI curriculum proposed in this study includes Bloom's digital taxonomy, Bruner's spiral curriculum composition principle, and three elements such as 'content domain', 'level', and 'teacher learning method'. It was intended to consist of. Based on the direction of AI curriculum development suggested in the study, we hope that the AI curriculum of domestic graduate schools of education will be more substantial, and this framework will be revised and supplemented in the future to be used in the composition of the AI curriculum in elementary and secondary schools.