• Journal of Korean Library and Information Science Society
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• v.45 no.3
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• pp.441-462
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• 2014

The purpose of this study is to analyze the concept of information commons and learning commons that has emerged in recent years, and point out the difference between the two concepts, as well as its implications for public libraries, which get lessons learned from learning commons at Japanese public libraries. To track its evolution to learning commons, the theoretical component of learning commons was analyzed. Based on the reference, a research framework for the case study of learning commons was developed. With IT technology diffusion, libraries have become information commons. However, the main mission of libraries should basically remain as learning. Because of this, libraries which function as information commons should go back to being learning commons, which are primarily places of learning. This research shows that libraries should stress its original basic mission which is learning, beyond being information commons in the Japanese library.

• Journal of the Korean Society for information Management
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• v.17 no.4
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• pp.27-45
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• 2000

National statistical data such as Korean Census is fundamental data for national administration. In this paper, we present an automatic coding system utilizing morphological analyser and knowledge dictionaries. Knowledge bases are constructed based on an authority dictionaries which were developed by authors utilizing a newly learning theory. Test data indicates 99.5% of productivity and 83.3% of accuracy. The presented methods can be effectively applied to analyze statistical information.

• Smart Media Journal
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• v.12 no.8
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• pp.45-59
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• 2023

Users who want to experience the metaverse for tourism are exposed to strategic planning in space for the purpose of cultural content. In addition, users learn integrated cultural content in the process of proceeding according to the virtual environment. and Along with the meaning of time and space, users will experience space-telling. It is important to induce interest from the beginning of the experience to continue the experience. However, obstacles arise in this process. This is because developers should promote connections with new information to users who do not have sufficient prior knowledge and only have keywords of interest. Therefore, efficient design methods to enhance interest should be studied in advance. But so far, there has been no research on how to systematically design prior organizers to induce interest in virtual space. This study is an interest-inducing design method that occurs in the process of developing the meaning of virtual space and storytelling of cultural content, and can be seen as a basic study using conceptual guidance-based prior organizer education and learning techniques. First, virtual space elements and human behavior theories were considered. Subsequently, five representative examples of previous organizers currently used were explored, and redesigned and proposed based on a conceptual map for information access and delivery purposes. Through this research process, it was possible to confirm that spatial attributes and cognitive interest elements were effectively transmitted to meaningful learning leading to storytelling learning and elements of service design design method through conceptual guidance.

• Journal of Korean Library and Information Science Society
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• v.41 no.2
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• pp.107-126
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• 2010

Education is an intentional and planned change process for achieving the objective. Thus, an educational objects sets is very important in elementary and secondary instructional practice. Bloom created the original taxonomy of the cognitive, affective, psychomotor domain for categorizing level of abstraction of questions that commonly occur in educational settings in 1956. During the 1990, Anderson & Krathwohl, Marzano led a new educational taxonomy which met for the purpose of updating the Bloom's taxonomy, hoping to add relevance for 21st century teaching and learning. The educational taxonomy with information literacy process is relationship. The purpose of this study is restructure of information literacy process based on educational object taxonomy.

• (The) Research of the performance art and culture
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• no.37
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• pp.365-389
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• 2018

This research aims to study Michael Chekhov's acting techniques scientifically, because his techniques has been studied only theoretically or empirically. Especially, this study focuses on 'imagination' and 'Psychological Gesture' from the perspective of cognitive psychology. Chekhov thought 'imagination' as the basis and core of all the works of acting. In cognitive psychology, it is called as 'imagery' and means 'a representation of the mind of the object not communicated by the sensory organs currently'. This study starts with defining imagery and takes a brief look at the features and kinds of imagery. Then the researcher will prove scientifically the possibility of training acting using imagery as Chekhov's assertion. For the proof of the validity of imagery, we'll look for the theoretical evidences-functional equivalence hypothesis, psychoneuromuscular theory, symbolic learning theory, psychophygiological information processing-and experimental ones-measurements of cerebral blood flow or event-related potential, experiments with fMRI(functional magnetic resonance imaging) or PET(positron emission tomography). As a result, we can see that imagery is functionally identical to perception and improves fulfillment of cognitive and physical tasks. As proving physical changes can draw out psychological changes(feeling) on the medium of imagery, we can also see the validity of Psychological Gesture. From the above research, even if Chekhov developed the acting techniques only on the basis of his experience, his techniques can be thought as having scientific validity. Though insufficient, this study can be a help for actors or students as they using Chekhov's techniques.

• The Transactions of the Korea Information Processing Society
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• v.2 no.2
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• pp.215-228
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• 1995

Despite their importance in language, there have been relatively few computational studies in understanding words. This paper describes how neural networks can learn to perceive and produce words. Most traditional linguistic theories presuppose abstract underlying representations (UR) and a set of explicit rules to obtain the surface realization. There are, however, a number of questions that can be raised regarding this approach: (1) assumption of URs, (2) formation of rules, and (3) interaction of rules. In this paper, it is hypothesized that rules would emerge as the generalizations the network abstracts in the process of learning to associate forms with meanings of the words. Employing a simple recurrent network, a series of simulations on different types of morphophonemic processes was run. The results of the simulations show that this network is capable of learning to perceive whether words are in basic from or in inflected form, given only forms, and to produce words in the right form, given arbitrary meanings, this eliminating the need for presupposing abstract URs and rules.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.6
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• pp.1379-1386
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• 2005

For efficient welding it is necessary to maintain stability of the welding process and control the shape of the welding bead. The welding quality can be controlled by monitoring important parameters, such as, the Arc Voltage, Welding Current and Welding Speed during the welding process. Welding systems use either a vision sensor or an Arc sensor, both of which are unable to control these parameters directly. Therefore, it is difficult to obtain necessary bead geometry without automatically controlling the welding parameters through the sensors. In this paper we propose a novel approach using fuzzy logic and neural networks for improving welding qualify and maintaining the desired weld bead shape. Through experiments we demonstrate that the proposed system can be used for real welding processes. The results demonstrate that the system can efficiently estimate the weld bead shape and remove the welding detects.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.179-192
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• 2014

Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.

• The Journal of the Acoustical Society of Korea
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• v.29 no.4
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• pp.286-293
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• 2010

There are two major conventional quantization algorithms: resolution-constrained quantization (RCQ) and entropy-constrained quantization (ECQ). Although RCQ works well for fixed transmission-rate, it produces the distortion outliers since the cell sizes are different. Compared with RCQ, ECQ has the constraints on the cell size but it produces the rate outliers. We propose the cell-size constrained vector quantization (CCVQ) that improves the generalized Lloyd algorithm (GLA). The CCVQ algorithm is able to make a soft-decision between RCQ and ECQ by using the flexible penalty measure according to the cell size. Although the proposed method increases the small amount of overall mean-distortion, it can reduce the distortion outliers.

• Journal of The Korean Association For Science Education
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• v.36 no.6
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• pp.867-876
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• 2016

In accordance with the changing of society, remarkable increase in knowledge and information, the competencies to choose and use proper information in various domains are considered as an important skill. As one of the methods in developing these competencies, it is emphasized that a problem-based learning can make student understand and use knowledge by solving the contextualized problem. However, it is skeptical of learner's development of competencies to use knowledge by solving well-defined given problem. Therefore it is required that students be allowed to develop the competency to find problem through experiences to determine and evaluate the purpose of the problem and method. The purpose of this study is to understand how undergraduate students use science or technology in finding a problem. In this line, this study articulated four cases conducted by participants who engaged in convergence teaching-learning program. And this study investigated the participants' process of problem-finding, method and reason to apply science or technology. The results were drawn by analyzing interviews and written data, including their proposal, a poster, and final reports. Participants changed the form of problem from initial ill-structured one into a concrete one, where the participant could derive a detailed solution. Science or technology applied as the detailed example to convert problem into a concrete form, or as the analyzing tool or theoretical background of problem to make a link with other domain. Their reason of applying science or technology could be summarized in 'personal interest based on prior experience' and 'alternatives to resolve a dissatisfaction.' Based on the result, this study suggests holistic approach that is included in both intuitive thinking and logical thinking and metacognitive regulation to stimulate problem-finding in problem-based learning program.