• Knowledge Management Research
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• v.24 no.3
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• pp.95-125
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• 2023

As the aviation industry has rapidly been grown, there are more factors for customers to consider when choosing an airline. In response, airlines are trying to increase customer value by providing high-quality services and differentiated experiential value. While early customer value research centered on utilitarian value, which is the trade-off between cost and benefit in terms of utility for products and services, the importance of experiential value has recently been emphasized. However, experiential value needs to be studied in a specific context that fully represents customer preferences because what constitutes customer value changes depending on the product or service context. In addition, customer value has an important influence on customers' decision-making, so it is necessary for airlines to accurately understand what constitutes customer value. In this study, we collected customer reviews and ratings from Skytrax, a website specializing in airlines, and utilized the BERTopic technique to derive factors of customer value. The results revealed nine factors that constitute customer value in airlines, and six of them are related to customer satisfaction. This study proposes a new methodology that enables a granular understanding of customer value and provides airlines with specific directions for improving service quality.

• Journal of Christian Education in Korea
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• v.77
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• pp.251-276
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• 2024

This study aimed to enhance the educational competencies of instructors and improve the quality of higher education by identifying instructing types, developing an assessment diagnostic tool, and designing a customized faculty training curriculum for each type. To achieve this, a literature review and Delphi research were conducted. The results are summarized as follows: First, instructing types such as 'Star Lecturer', 'Learning Mentor', and 'Designer' were identified through the analysis of previous studies. Second, a diagnostic tool for determining an instructor's type was developed by modifying and enhancing Grasha's Teaching Style Inventory, which is widely used both domestically and internationally. This tool comprises 24 questions, with 8 questions for each type. Third, a curriculum was designed for each instructing type, consisting of common courses necessary for all types and specialized courses tailored to the characteristics of each type. The common courses cover essentials for lesson design, implementation, and evaluation, while the specialized courses cater to the unique needs of each instructing type. Fourth, the developed model, tools, and curriculum underwent validation. A Delphi method was employed with a group of 10 experts, leading to revisions and finalizations based on their feedback. This study has laid the groundwork for instructors to identify their own teaching styles and receive customized training, thereby enhancing their teaching effectiveness and overall educational quality. However, further research is necessary to develop systems and mechanisms for the operationalization of these findings, including incentives for instructors and strategies for disseminating information among participants.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.270-283
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• 2012

With the advent of multi-channel TV, IPTV and smart TV services, excessive amounts of TV program contents become available at users' sides, which makes it very difficult for TV viewers to easily find and consume their preferred TV programs. Therefore, the service of automatic TV recommendation is an important issue for TV users for future intelligent TV services, which allows to improve access to their preferred TV contents. In this paper, we present a recommendation model based on statistical machine learning using a collaborative filtering concept by taking in account both public and personal preferences on TV program contents. For this, users' preference on TV programs is modeled as a latent topic variable using LDA (Latent Dirichlet Allocation) which is recently applied in various application domains. To apply LDA for TV recommendation appropriately, TV viewers's interested topics is regarded as latent topics in LDA, and asymmetric Dirichlet distribution is applied on the LDA which can reveal the diversity of the TV viewers' interests on topics based on the analysis of the real TV usage history data. The experimental results show that the proposed LDA based TV recommendation method yields average 66.5% with top 5 ranked TV programs in weekly recommendation, average 77.9% precision in bimonthly recommendation with top 5 ranked TV programs for the TV usage history data of similar taste user groups.

• Journal of The Korean Association For Science Education
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• v.25 no.3
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• pp.400-410
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• 2005

According to the cognitive conflict process model, student anxiety factor is known to have both positive and negative effects on student response behaviors in a conflict situation for conceptual change learning. However, there is little research that reveals what type of anxiety, either constructive or destructive, is related when conducting step-by-step experiments to resolve cognitive conflicts. This study attempted to learn the characteristic of explanatory hypothesis according to anxiety type after conducting five step-by-step experiments related to action and reaction concept. Results found that students who belonged to the types of 'conviction in logical misconception', 'insisting on additional variables', and 'reasonable modification' suggested explanatory hypothesis close to physical nature. On the other hand, those who showed the other five types of anxiety ('compatible predictions', 'dependence on others', 'fusion of past experience', 'lack of confidence', and 'conflict with past experience') suggested temporary supported hypothesis or simple explanatory hypothesis according to student intuition and simple observation. These results indicate that students in the above-mentioned five categories need more external interactions with instructors based on the type of anxiety related to student behavior. In addition, the results present student characteristics which instructors should be more attentive to when using step-by-step experiments to resolve cognitive conflicts.

• Cartoon and Animation Studies
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• s.48
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• pp.271-310
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• 2017

This paper examines the composition and the content of media art which is an art education subject in a national curriculum of Australia; and discusses implications for Korean education curriculums. Media covered by Media Art subject in Australia are the multi types of general media including TV, movie, video, newspaper, radio, video game, the internet, and mobile media; and their contents. The purpose of ACARA's media art education curriculum is to improve creative use, knowledge, understanding, and technology of communication techniques for multiple purposes and the audiences. Through the Media Art subject, both the students and the community are able to participate in the actual communications with the rich culture surrounding them and to develop the knowledge and understanding of the 5 core concepts of language, technology, system, audience and re-creation while testing the culture. The implication of this study is as the following. ACARA's media art education curriculum has been developed as an independent educational program and has a special significance within Australian education curriculums. Although ACARA's media art education curriculum is formed as an independent subject, it is suggested within the curriculum to instruct in close connection with other subjects upon execution. Its organization and elaborateness in curriculum composition are very effective in terms of the teacher's teaching-learning design and as well as the evaluation. This seems to show a good model of leading media literacy curriculum. ACARA's media art education curriculum can be a great reference in introducing media literacy to Korean national education curriculums.

• Journal of The Korean Association For Science Education
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• v.36 no.4
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• pp.657-668
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• 2016

The purpose of the study is to explore the types and coping methods of dilemmas that pre-service science teachers experience during student teaching. For this, we collected 131 dilemma journals that 34 pre-service science teachers wrote during a four-week period of student teaching. Results show that first, there are five categories of dilemmas, they are, 'Which science teacher should I be?', 'What is good science teaching?', 'How should I build relationships with the people around me at school?', and 'Who am I as a student teacher?'. Second, pre-service science teachers' status as a students-teachers made them cope with dilemmas passively. Third, when they cope with the dilemmas, student-teachers considered the dilemmas as conflicts of irreconcilable alternatives rather than opportunities of conciliation and compromise, therefore, most pre-service science teachers choose just one alternative and only 20% of dilemmas are resolved by compromise choice. Finally, dilemmas which showed the features of science teaching are the dilemmas related to scientific inquiry teaching and science teaching-learning model. Based on the results, we discussed the implications for teacher education.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.173-193
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component-based software development to promote application interaction and integration within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web services repositories not only be well-structured but also provide efficient tools for an environment supporting reusable software components for both service providers and consumers. As the potential of Web services for service-oriented computing is becoming widely recognized, the demand for an integrated framework that facilitates service discovery and publishing is concomitantly growing. In our research, we propose a framework that facilitates Web service discovery and publishing by combining clustering techniques and leveraging the semantics of the XML-based service specification in WSDL files. We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the Web service domain. We have developed a Web service discovery tool based on the proposed approach using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web services repositories. We believe that both service providers and consumers in a service-oriented computing environment can benefit from our Web service discovery approach.

• Journal of the Korean Chemical Society
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• v.65 no.3
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• pp.209-218
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• 2021

This study investigated the condition of chemistry teacher's student competency assessment based on the inquiry report. To this end, an inquiry report was collected for chemistry teachers who took the training at two universities that conducted the 2020 first-class chemistry teacher training. The science subject competencies presented in NAEA analysis framework was used to analyze what kind of competencies teachers assess students through inquiry reports. A total of 63 chemistry teachers submitted inquiry reports, which were analyzed by competency, sub-element of each competency, and detail element to analyze the actual situation. As a result of the study, most chemistry teachers reflected their 'scientific inquiry and problem-solving ability' in their evaluation through inquiry reports. 'Ability to understand and apply scientific principles', which is mainly evaluated through paper-based evaluation, was partially used as confirmation of prerequisite learning at the beginning of the inquiry and the weight of evaluating 'scientific communication skill' was not large. In 'scientific inquiry and problem-solving ability' through inquiry report, 'design and conduct explorations', 'data analysis and interpretation' and 'drawing conclusion and suggesting solution' were mainly assessed. However, 'discover and recognize problems' and 'development and use of model' were hardly assessed.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.1
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• pp.5-25
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• 2022

In most countries, public libraries are knowledge information centers, complex cultural spaces, lifelong learning facilities, and third places for local residents. The social homage spoken on the premise of this identity and socio-cultural role is the knowledge and information agora, cultural infrastructure, living room in the city, and the university of the people. However, if there is a significant gap between public libraries regardless of country or region, it will inevitably lead to information gaps, regional gaps, and cultural inequality and cultural welfare gaps among local residents. This study is regarded as the essence of regional cultural facilities and premised that the regional gap in public libraries is a factor of regional cultural gaps. Based on this premise, the gap between the location quotient, input indicators, and output indicators of public libraries of regional governments in Korea and basic local governments in the Gyeongbuk region was analyzed. And this study derived core elements through correlation and regression analysis of input and output indicators of all public libraries nationwide, developed a management model for each indicator, and suggested a plan to resolve the relative gap for public libraries by city and county in Gyeongbuk.

• Smart Media Journal
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• v.11 no.10
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• pp.89-96
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• 2022

An open domain machine reading comprehension is a model that adds a function to search paragraphs as there are no paragraphs related to a given question. Document searches have an issue of lower performance with a lot of documents despite abundant research with word frequency based TF-IDF. Paragraph selections also have an issue of not extracting paragraph contexts, including sentence characteristics accurately despite a lot of research with word-based embedding. Document reading comprehension has an issue of slow learning due to the growing number of parameters despite a lot of research on BERT. Trying to solve these three issues, this study used BM25 which considered even sentence length and InferSent to get sentence contexts, and proposed an open domain machine reading comprehension with ALBERT to reduce the number of parameters. An experiment was conducted with SQuAD1.1 datasets. BM25 recorded a higher performance of document research than TF-IDF by 3.2%. InferSent showed a higher performance in paragraph selection than Transformer by 0.9%. Finally, as the number of paragraphs increased in document comprehension, ALBERT was 0.4% higher in EM and 0.2% higher in F1.