• Journal of the Korean Society for Library and Information Science
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• v.58 no.3
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• pp.35-64
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• 2024

The purpose of this study is to develop educational strategies and models by applying future-oriented elements of libraries, which are transitioning into integrated spaces through collaboration with archives and museums, into school library education. This study focuses on the changes where libraries expand their spaces and roles in response to the trends of a pluralistic society. The term 'Larchiveum' was established to represent a knowledge and culture complex space. The concepts and functions of this term were identified, and the characteristics of materials collected and managed by archives, museums, and art galleries, as well as domestic and international educational information services, were analyzed to explore ways to integrate them into school library education. Based on the ASSURE instructional design model, which emphasizes the effective selection and use of teaching and learning media, this study developed Larchiveum strategies, including 'Inquiry-based Information Utilization,' 'Curriculum Integration and Convergence,' 'Collaboration, Sharing, and Dissemination,' and 'Digital Archive,' and structured the educational content accordingly. The procedures and steps were refined through the evaluation and feedback of field experts, leading to the development of a collaborative educational model that incorporates Larchiveum strategies, resources, and inquiry-based instruction.

• Journal of Korean Home Economics Education Association
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• v.19 no.2
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• pp.61-75
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• 2007

The method used in this descriptive study is the survey. The purpose of the study is to investigate performances of middle school home economics(HE) teachers regarding the HE subject. Respondents in this study were 177 HE teachers. Questionnaires from HE teachers were collected through e-mails. With the operation of the SPSS/Win (ver10.1) program, the analyses such as mean, standard deviation, frequencies, percents, t-test and ANOVA are done to see the relations between the related variables. The results of this study were as follows. First, the middle school HE teachers performed well above the standards in terms of planning, execution, and evaluation about self supervision related to HE. Second, the HE teachers collected materials for instruction by using literary (books) survey, Internet and mass media. They mainly focused on improving ways of "teaching and learning" and deepening the studies related to contents of textbooks. Third, the HE teachers used various ways to improve self supervision in the following order: mass media, literary (books) survey, participation in societies for researches, meetings, various training and field trip More than half of the middle school HE teachers proceeded to graduate schools, joined meetings for researches and had experiences of taking classes in private institutes. They also made a field trip once or twice a year and depended much on TV programs and education broadcasting programs as ways of improving their performances related to self supervision. While they were actively sharing information with their peer group, they made little effort at analyzing and evaluating their classes and utilizing expert group for their classes. The main problems as to self supervision were that only the half of the HE teachers responded that they were performing self supervision related to their classes well above the standards and the area where they heavily focused on has been "teaching and learning" and "the studies related to contents of textbooks". Therefore, to motivate incentives of the HE teachers for self supervision, meetings for researches should be activated and various training programs should be developed. In addition, government should give administrative and institutional support through a publication of books introducing detailed ways of self supervision and an establishment of centers and institutions for supporting self supervision.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Cartoon and Animation Studies
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• s.35
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• pp.29-65
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• 2014

Visual culture art education (VCAE) seems to be the new paradigm for art education after postmodernism. Getting beyond the traditional art education, VCAE has expanded its scope of interest to include the visual environment that surrounds our life, thus pushing the boundary of art education beyond the traditional fine arts to cover pop culture and visual art. VCAE shares the issues as well as a lot of elements of culture and art education and in fact serves as a major theoretic background for culture and art education, in that it pays attention to the sociocultural context of images and emphasizes visual literacy and constructionist learning. In this paper, I have reviewed the theoretical background and related issues of VCAE with a view to presenting a direction for animation education, which is gaining in importance coming into the Age of Digital Media. VCAE was born in the progressive cultural atmosphere from the 1970s and thereafter, and its gist consists in figuring out visual artifacts and their action in order to improve individual and social life. Yet, VCAE continues with its development according to the changing aspects of visual culture, and currently, it is expanding its scope of interest to cover the esthetic, experiential education in visual culture and construction of meaning through digital story-telling. In the visual environment of the Digital Age, animation is establishing itself as the center of the visual culture, being a form that goes beyond an art genre or technology to realize images throughout the visual culture. Also, VCAE, which has so far emphasized visual communication and critical reading of culture, would need to reflect the new aspects of the visual culture in digital animation across the entire gamut from experiencing to understanding and appreciating art education. In this paper, I emphasize on Cross-Curricula, social reconstruction, the expansion of animation education, interests in animation as a digital media, and animation literacy. A study of animation education from the perspective of VCAE will not only provide a theoretical basis for establishing animation education, but also enrich the content of VCAE, traditionally focused on critical text reading, and promote its contemporary and futuristic orientation.

• The Korean Journal of Archival Studies
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• no.79
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• pp.5-32
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• 2024

The Korean government ranked 3rd among 193 UN member countries in the UN's 2022 e-Government Development Index. Korea, which has consistently been evaluated as a top country, can clearly be said to be a leading country in the world of e-government. The lubricant of e-government is data. Data itself is neither information nor a record, but it is a source of information and records and a resource of knowledge. Since administrative actions through electronic systems have become widespread, the production and technology of data-based records have naturally expanded and evolved. Technology may seem value-neutral, but in fact, technology itself reflects a specific worldview. The digital order of new technologies, armed with hyper-connectivity and super-intelligence, not only has a profound influence on traditional power structures, but also has an a similar influence on existing information and knowledge transmission media. Moreover, new technologies and media, including data-based generative artificial intelligence, are by far the hot topic. It can be seen that the all-round growth and spread of digital technology has led to the augmentation of human capabilities and the outsourcing of thinking. This also involves a variety of problems, ranging from deep fakes and other fake images, auto profiling, AI lies hallucination that creates them as if they were real, and copyright infringement of machine learning data. Moreover, radical connectivity capabilities enable the instantaneous sharing of vast amounts of data and rely on the technological unconscious to generate actions without awareness. Another irony of the digital world and online network, which is based on immaterial distribution and logical existence, is that access and contact can only be made through physical tools. Digital information is a logical object, but digital resources cannot be read or utilized without some type of device to relay it. In that respect, machines in today's technological society have gone beyond the level of simple assistance, and there are points at which it is difficult to say that the entry of machines into human society is a natural change pattern due to advanced technological development. This is because perspectives on machines will change over time. Important is the social and cultural implications of changes in the way records are produced as a result of communication and actions through machines. Even in the archive field, what problems will a data-based archive society face due to technological changes toward a hyper-intelligence and hyper-connected society, and who will prove the continuous activity of records and data and what will be the main drivers of media change? It is time to research whether this will happen. This study began with the need to recognize that archives are not only records that are the result of actions, but also data as strategic assets. Through this, author considered how to expand traditional boundaries and achieves reterritorialization in a data-driven society.

• Journal of The Korean Association For Science Education
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• v.30 no.5
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• pp.576-593
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• 2010

The purpose of this study was to identify the current status of ethics education in science and technology for pre-service science teachers and find out their recognition on the needs for ethics education at school. A survey was administered for this study and a total of 594 pre-service science teachers studying in college/university of education participated. The survey was organized to examine participants' 1) experience in ethics education in science and technology, 2) recognition on the needs of ethics education in science and technology, and 3) the need for it in elementary and secondary school. Each item was responded using either 1 to 5 Likert type scale, multiple choices, or open questionnaires. The results showed that 37.4% of participants obtain science technology information from the mass media, and 23.5% from the school education. Only 8.4% of the participants had the experience of taking class on ethics in science and technology. In terms of level of confidence in understanding the ethical issues in science and technology, the average response was 2.73. However, their perception on the needs of the ethics education ranges from 3.34 to 4.58, which is much stronger than other responses on average. This strong perception on the needs was much higher for pre-service science teachers for elementary school, than those of the secondary school(p<.05). All participants recognized the need for ethics education in science and technology at both elementary and secondary school. In responses for which subject should provide ethical issues on science and technology, science class was most frequently suggested (62.4%), followed by ethics class (29.1%). In responses for the most efficient form of learning, they suggested that case studies (43.5%), followed by discussions (41.4%) would be an efficient way to learn. Even in the responses of open questionnaires asking for efficient ways of learning ethical issues, participants suggested that discussions on various ethical issues on the cases in the science and technology would provide practical and substantial learning.

• Journal of The Korean Association For Science Education
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• v.36 no.6
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• pp.925-934
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• 2016

For students, astronomy is not only interesting but also difficult to learn. However, there is a limit in learning astronomy in a school science setting since astronomy is vast subject. Fortunately, science museums can be helpful in overcoming this limitation. Experiences in science museum provide something that any descriptions or illustrations cannot give. Therefore, to maximize the educational effect, it is necessary to look at astronomical exhibits regarding the educational aspects and complement them. For these reasons, the purpose of this study is to investigate characteristics of exhibitions related to astronomy and how much the exhibitions reflect the contents of their science curricula. We selected famous science museums in Korea, America, and Japan and analyzed characteristics of their astronomy exhibition. We analyze these characteristics in the aspects of exhibition technology & media, presentation method and activity types. Also, this study figures out how content of exhibitions are connected to school science curriculum. The results are summarized as follows: First, Science Museums of America and Japan utilize interactive exhibits to raise participation. It implies that Science Museum of Korea needs Interactive Exhibits that provide a realistic experience of the universe. Second, the astronomy exhibits reflect some of the learning elements of their science curricula concerned with astronomy. However, these astronomical contents are included selectively and not according to their required curriculum. It means that many students lack the opportunity to study Astronomy in their schools. Therefore, the astronomy museum must reflect learning elements of science curricula concerned with astronomy in the exhibits.

• Proceedings of the Technology Innovation Conference
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• 1998.06a
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• pp.116-127
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• 1998

The Necessity of Cyber University. Within the rapidly changing environment of global economics, the environment of higher education in the universities, also, has been, encountering various changes. Popularization on higher education related to 1lifetime education system, putting emphasis on the productivity of education services and the acquisition of competitiveness through the market of open education, the breakdown of the ivory tower and the Multiversitization of universities, importance of obtaining information in the universities, and cooperation between domestic and oversea universities, industry and educational system must be acquired. Therefore, in order to adequately cope wi th these kinds of rapid changes in the education environment, operating Cyber University by utilizing various information technologies and its fixations such as Internet, E-mail, CD-ROMs, Interact ive Video Networks (Video Conferencing, Video on Demand), TV, Cable etc., which has no time or location limitation, is needed. Using informal ion and telecommunication technologies, especially the Internet is expected to Or ing about many changes in the social, economics and educational area. Among the many changes scholars have predicted, the development and fixations of Distant Learning or Cyber University was the most dominant factor. In the case of U. S. A., Cyber University has already been established and in under operation by the Federate Governments of 13 states. Any other universities (around 500 universities has been opened until1 now), with the help of the government and private citizens have been able to partly operate the Cyber University and is planning on enlarging step-by-step in the future. It could be seen not only as U. S. A. trying to elevate its higher education through their leading information technologies, but also could be seen as their objective in putting efforts on subordinating the culture of the education worldwide. UTRA University in U. S. A., for example, is already exporting its class lectures to China, and Indonesia regions. Influenced by the Cyber University current in the U.S., the Universities in Korea is willing .to arrange various forms of Cyber Universities. In line with this, at JUNAM National University, internet based Cyber University, which has set about its work on July of 1997, is in the state of operating about 100 Cyber Universities. Also, in the case of Hanam University, the Distant Learning classes are at its final stage of being established; this is a link in the rapid speed project of setting an example by the Korean Government. In addition, the department of education has selected 5 universities, including Seoul Cyber Design University for experimentation and is in the stage of strategic operation. Over 100 universities in Korea are speeding up its preparation for operating Cyber University. This form of Distant Learning goes beyond the walls of universities and is in the trend of being diffused in business areas or in various training programs of financial organizations and more. Here, in the hope that this material would some what be of help to other Universities which are preparing for Cyber University, I would 1ike to introduce some general concepts of the components forming Cyber University and Open Education System which has been established by JUNAM University. System of Cyber University could be seen as a general solution offered by tile computer technologies for the management on the students, Lectures On Demand, real hour based and satellite classes, media product ion lab for the production of the multimedia Contents, electronic library, the Groupware enabling exchange of information between students and professors. Arranging general concepts of components in the aspect of Cyber University and Open Education, it would be expressed in the form of the establishment of Cyber University and the service of Open Education as can be seen in the diagram below.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.139-148
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• 2020

Infectious diseases have long plagued mankind, and predicting and preventing them has been a big challenge for mankind. For this reasen, various studies have been conducted so far to predict infectious diseases. Most of the early studies relied on epidemiological data from the Centers for Disease Control and Prevention (CDC), and the problem was that the data provided by the CDC was updated only once a week, making it difficult to predict the number of real-time disease outbreaks. However, with the emergence of various Internet media due to the recent development of IT technology, studies have been conducted to predict the occurrence of infectious diseases through web data, and most of the studies we have researched have been using single Web data to predict diseases. However, disease forecasting through a single Web data has the disadvantage of having difficulty collecting large amounts of learning data and making accurate predictions through models for recent outbreaks such as "COVID-19". Thus, we would like to demonstrate through experiments that models that use multiple Web data to predict the occurrence of infectious diseases through LSTM models are more accurate than those that use single Web data and suggest models suitable for predicting infectious diseases. In this experiment, we predicted the occurrence of "Malaria" and "Epidemic-parotitis" using a single web data model and the model we propose. A total of 104 weeks of NEWS, SNS, and search query data were collected, of which 75 weeks were used as learning data and 29 weeks were used as verification data. In the experiment we predicted verification data using our proposed model and single web data, Pearson correlation coefficient for the predicted results of our proposed model showed the highest similarity at 0.94, 0.86, and RMSE was also the lowest at 0.19, 0.07.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.