• Educational Technology International
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• v.9 no.2
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• pp.79-95
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• 2008

This paper aims to investigate modeling scripts based on the mode of group interaction in a computer-supported collaborative learning environment. Based on a literature review, this paper assumes that group interaction and its mode would have strong influence on the online collaborative learning process, and furthermore lead learners to create and share significant knowledge within a group. This paper deals with two different modes of group interaction- distributed and shared interaction. Distributed interaction depends on the external representation of individual knowledge, while shared interaction is concerned with sharing knowledge in group action. In order to facilitate these group interactions, this paper emphasizes the utilization of appropriate CSCL scripts, and then proposes the conceptual framework of CSCL scripts which integrate the existing scripts such as implicit, explicit, internal and external scripts. By means of the model regarding CSCL scripts based on the mode of group interaction, the implications for research on the design of CSCL scripts are explored.

• English Language & Literature Teaching
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• v.17 no.4
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• pp.1-22
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• 2011

Little has been known about the process of the language teacher professional development. The present study aims to investigate an assumption that anybody who has subject matter knowledge will be a good language teacher. A teacher with rich linguistic knowledge started to question the effectiveness of his online class. The teacher, in collaboration with a teacher trainer, became involved in the critical examination of his online class, seeking for more effective ways of teaching. The trainer provided the teacher with clinical supervision, which is characterized as developmental, collaborative, non-judgemental, interactive, and teacher-centered. The data collected at the multi-facets of the online teaching shows how the process of the teacher's decision-making became principled on the basis of recent developments in English language teaching, and how the teacher has gained pedagogical knowledge through reflection upon his teaching. The feedback from the students reveals that such teacher professional development is beneficial to student learning. These findings suggest that language teacher's professional development can take place when they are engaged in reflective teaching and classroom investigation. It is also suggested that the process of teacher development can be enhanced through collaborative supervision with trust, openness and congeniality between parties involved.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.3
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• pp.349-360
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• 2019

This study analyzes the trends of recommendation services for customized fashion styles in relation to artificial intelligence. To achieve this goal, the study examined filtering technologies of collaborative, content based, and deep-learning as well as analyzed the characteristics of recommendation services in the users' purchasing process. The results of this study showed that the most universal recommendation technology is collaborative filtering. Collaborative filtering was shown to allow intuitive searching of similar fashion styles in the cognition of need stage, and appeared to be useful in comparing prices but not suitable for innovative customers who pursue early trends. Second, content based filtering was shown to utilize body shape as a key personal profile item in order to reduce the possibility of failure when selecting sizes online, which has limits to being able to wear the product beforehand. Third, fashion style recommendations applied with deep-learning intervene with all user processes of buying products online that was also confirmed to penetrate into the creative area of image tag services, virtual reality services, clothes wearing fit evaluation services, and individually customized design services.

• Journal of The Korean Association For Science Education
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• v.38 no.5
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• pp.667-680
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• 2018

The purpose of this study is to investigate 1) the types of knowledge students ask for in their reading comprehension of science textbooks using an online annotation system, 2) the accuracy of the knowledge provided by the students to their peers, 3) the frequency of knowledge sharing behaviors, 4) the evaluation of the effect of collaborative reading, and 5) the trust among peers as knowledge sharers. Questions made by 241 students in the second grade of middle school using an online annotation system in two chapters of the science textbook were analyzed using Bloom's revised taxonomy and their answers were grouped according to five accuracy categories. Also, questionnaires for the evaluation of the effectiveness of collaborative reading comprehension and of trust among the students were used. The students asked their peers 'understanding questions' which comprised almost 80% of the total questions they made and were similar with individual metacognitive strategies for reading comprehension. Of the total threads, 71% has scientifically correct threads shared by the students. The frequency of the knowledge sharing behaviors was high but this was affected by the rewards (point system). Students evaluated that collaborative reading comprehension conducted through an online annotation system were helpful in their learning. In addition, the ratio of students trusting their peers who did the knowledge sharing is over 80%. This study shows that when students use an online annotation system, they can fill one another's cognitive gaps in the reading process by sharing knowledge. Also, collaborative reading using an online annotation system has proved that cognitive individualization is possible through sharing knowledge interactively and dynamically, unlike reading hard copies of textbooks which are a one way information transfer.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.7-13
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• 2024

User preferences and ratings may be anticipated by recommendation systems, which are widely used in social networking, online shopping, healthcare, and even energy efficiency. Constructing trustworthy recommender systems for various applications, requires the analysis and mining of vast quantities of user data, including demographics. This study focuses on holding elections with vague voter and candidate preferences. Collaborative user ratings are used by filtering algorithms to provide suggestions. To avoid information overload, consumers are directed towards items that they are more likely to prefer based on the profile data used by recommender systems. Better interactions between governments, residents, and businesses may result from studies on recommender systems that facilitate the use of e-government services. To broaden people's access to the democratic process, the concept of "e-democracy" applies new media technologies. This study provides a framework for an electronic voting advisory system that uses machine learning.

• 전자공학회논문지 IE
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• v.48 no.1
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• pp.36-44
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• 2011

The purpose of this study was to develop the basic design principles for the engineering mathematics teaching model that supported college students to become collaborative problem solvers. For this purpose, the following four design principles were drawn from the steps of systems approach, especially with consideration of needs of engineering students, professors, curriculum and relevant research on mathematical education. As a result, the four design principles for the engineeering mathematics teaching model were drawn as follows: (1) Improve students' basic mathematical learning abilities through repetition and elaborative practice of the basic mathematical concepts and principles, (2) Develop students' problem solving abilities through collaborative projects or learning activities with peers, (3) Facilitate students' reflection and provide teacher's monitoring and prompt feedback during their learning process, and (4) Build up online learning environments that enable students to become self-regulated learners.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.363-364
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• 2022

The COVID-19 pandemic had substantial negative impacts and caused several disruptions to the global supply chain of the shipping industry. The key challenges identified in terms of maritime manpower are the Certificates of Competency (CoC) or the expiration and/or failure to complete refresher and/or revalidation courses, which directly hinder employment retention and lost opportunities at sea. To tackle this issue directly and swiftly, the creation of the APEC SEN Distance Learning Platform was suggested and approved by APEC as part of an official project. This paper introduces the APEC-wide accessible distance learning platform with the following key topics: the organisation and operation of the platform, the themes and content to be prioritised, the process of education, training, certification, and the ways to promote accreditation, mutual recognition on CoC, education and training videos by taking collaborative actions, and the development of content.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1006-1027
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• 2022

In the crowdfunding market, various crowdfunding platforms can offer founders the possibilities to collect funding and launch someone's next campaign, project or events. Especially, healthcare crowdfunding is a field that is growing rapidly on health-related problems based on online platforms. One of the largest platforms, GoFundMe, has raised US$ 5 billion since 2010. Unfortunately, while providing crucial help to care for many people, it is also increasing risk of fraud. Using the largest platform of crowdfunding market, GoFundMe, we conduct an exhaustive search of detection on fraud from October 2016 to September 2019. Data sets are based on 6 main types of medical focused crowdfunding campaigns or events, such as cancer, in vitro fertilization (IVF), leukemia, health insurance, lymphoma and, surgery type. This study evaluated a detect of fraud process to identify fraud from non-fraud healthcare crowdfunding campaigns using various machine learning technics.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.61-74
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• 2011

The author analyses the challenging activities of Japanese libraries in this decade by launching two keywords; "product-sharing" and "outcome generation." "Product-sharing" means that libraries share knowledge, skills, and records which are produced as the result of the services or in the process of activities. And "outcome generation" means that libraries generate any efficiency or effectiveness through their services to users. Using these concepts, reported are the current situation and aspects of Japanese libraries which try to make various contributions to the society; research and learning of the people, and education and training for professional librarians, and so on. In the analysis, the author shows some examples of "product-sharing" at first, including the records of reference transaction and the multi-functioned online public access catalogue. Especially, focused is on the various possibility and adoptability of the Collaborative Reference Database System of the National Diet Library of Japan. This system is one of digital reference service in Japan, and the database of reference transaction records is expected to be useful for research and academic studyies as knowledge-base of professional librarians. And the system is also expected to be a platform for LIS education and professional development in the e-learning environment. Secondly, as the examples of "outcome generation", explained are the problem-solving-type activities, and provision of the collection about books on struggling against disease and illness. A few examples of outcome in the problem-solving-type activities are these; increase of sales in the services for shop managers, business persons, and entrepreneurs, contribution to affluent daily life by providing the local information services to residents and neighbourhoods, and etc. And for both the patients with serious cases and their family or those who nurse them, books about other persons' notes or memorandum are the greatest support, and sometime healing. The author discuss the 'raison d'etre' of these activities focusing on public libraries in Japan.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.155-167
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• 2024

Distribution and logistics industries contribute some of the biggest GDP(gross domestic product) in South Korea and the number of related companies are quarter of the total number of industries in the country. The number of retail tech companies are quickly increased due to the acceleration of the online and untact shopping trend. Furthermore, major distribution and logistics companies try to achieve integrated data management with the fulfillment process. In contrast, small and medium distribution companies still lack of the capacity and ability to develop digital innovation and smartization. Therefore, in this paper, a deep learning-based demand forecasting & recommendation model is proposed to improve business competitiveness. The proposed model is developed based on real sales transaction data to predict future demand for each product. The proposed model consists of six deep learning models, which are MLP(multi-layers perception), CNN(convolution neural network), RNN(recurrent neural network), LSTM(long short term memory), Conv1D-BiLSTM(convolution-long short term memory) for demand forecasting and collaborative filtering for the recommendation. Each model provides the best prediction result for each product and recommendation model can recommend best sales product among companies own sales list as well as competitor's item list. The proposed demand forecasting model is expected to improve the competitiveness of the small and medium-sized distribution and logistics industry.