• Journal of Digital Convergence
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• v.15 no.4
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• pp.27-34
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• 2017

As information technology has been developed in a rapid way, a lot of users get to be familiar with social media. Accordingly, the possibility of social media for educational use has increased. From the view point of learning, social media help learners make communities of practice that can lead to collective intelligence. In this study, two different types of social media, synchronous and asynchronous, were compared in terms of usage patterns in the e-learning settings of college level. Content analysis has figured out four factors: learning content, tasks and assignments, emotional communications, and chatting. There found to be a statistical differences in the postings in all of the factors except tasks and assignments. In the qualitative interviews, the participants told various usage patterns of synchronous and asynchronous social media. In sum, the learners generally preferred synchronous social media. Rather, asynchronous social media were mainly used for deep thinking and summarizing. Last, suggestions were made to improve educational environments for the learners in the digital and social media age.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1418-1420
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• 2012

스마트 미디어 기기의 보급으로 많은 교육용 어플리케이션이 개발되고 있으며, SNS를 교육적 접근으로 활용한 학습모델의 사례들이 늘어나고 있는 추세이다. 현대 정보화 사회에서 요구되는 학습자 중심의 구성주의 교육 패러다임에 초점을 맞춰 학습자 스스로 학습콘텐츠를 구성하며 자기주도적 학습을 하기 위한 시스템 개발을 위해 본 논문에서는 소셜러닝 기반의 학습자 중심형 학습콘텐츠 개발도구의 설계방법에 대해 제시하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.890-892
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• 2014

최근 스마트기기가 널리 보급되고 소셜네트워크 서비스가 확산되면서, 스마트 기기 및 소셜미디어를 활용함으로서 학습에서 상호작용을 극대화한 교육환경으로 스마트러닝이 크게 부각되고 있다. 그리고 스마트러닝 콘텐츠 및 환경의 확산으로 PC 위주에서 스마트폰 등으로 이러닝 콘텐츠의 사용환경이 확장됨에 따라 콘텐츠 저작의 경제성과 효율성 등을 고려하게 되었으며, 하나의 콘텐츠를 다양한 환경에서 활용 가능하도록 하고 있다. 그러나 기존 PC기반의 콘텐츠를 스마트기기에 적용함에 있어 여러 가지 문제가 발생하는데 이 문제들을 해결하는 방안으로 먼저 콘텐츠에 대한 표준화가 중요한 요소로 작용한다. 따라서 본 논문에서는 전자책 표준화를 활용한 효율적인 스마트러닝 기법을 제시하고자 한다.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.495-509
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• 2011

According to the rapid technological development such as ubiquitous environments, there has been growing interest in learning with social media as known as social learning. This study was conducted to analyze various participation types of social media contents aiming to explore strategies for facilitating learning. Specifically, the research model was established by two aspects in using social media contents. First was classified by writings and readings in contents, which consists of prosumers, producers, consumers, and non-participants. Second criterion was categorized by instruction-related and instruction-nonrelated, which is learning contents, learning management, emotional expression, and social activities. In order to acquire empirical data, a set of fourteen undergraduate students participated in this research for eight weeks using a microblog. Based on the analyses on the data through learning activities, three learning strategies were suggested to facilitate social media based learning: analysis on learners, role of the instructor, and instructional model design.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.27-35
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• 2011

Social network services are developed which is based on interaction and collaboration between users. This used to teaching-learning and integrate personal experience based on constructivism and social learning has developed into. In order to use which better to support the N-Screen communication model is needed. Communication model is to support the interaction between learner-instructor- the system. However, until now, There are a lot of web-based communications research. In this study, Social Learning Services environment to extended to N-Screen. For seamless service, Location information of individuals to use to learning activities. To support this, the communication manager is to design and implement. Communications manager for the N-Screen services draw students use cases and define the required functions. Based on this, Communication function is designed. In addition, Considering the characteristics of each device, personal location information to be reflected.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.3
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• pp.247-264
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• 2021

This study aims to create a deep learning-based classification model to classify suicide tendency by suicide corpus constructed for the present study. Also, to analyze suicide factors, the study classified suicide tendency corpus into detailed topics by using topic modeling, an analysis technique that automatically extracts topics. For this purpose, 2,011 documents of the suicide-related corpus collected from social media naver knowledge iN were directly annotated into suicide-tendency documents or non-suicide-tendency documents based on suicide prevention education manual issued by the Central Suicide Prevention Center, and we also conducted the deep learning model(LSTM, BERT, ELECTRA) performance evaluation based on the classification model, using annotated corpus data. In addition, one of the topic modeling techniques, LDA identified suicide factors by classifying thematic literature, and co-word analysis and visualization were conducted to analyze the factors in-depth.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.17-24
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• 2009

This paper proposes a new e-learning model which introduces a participant method based on concepts of open source as well as UCC of web2.0 and achieves learner-centered learning. It is possible for learner to participate actively in creation of micro-contents and reorganize contents using various micro-content with one's learning strategies in consideration of one's own intellectual power, learning objectives and propensity to learn. The learner can achieve the learner-oriented learning through this procedure and select micro-contents in order to reorganize the personalized learning contents to take advantage of social network among learners. The higher effectiveness of learning would be expected by forming connectedness among learners using social network.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.36-45
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• 2011

An agent in collaborative e-learning has independent function for learners in any circumstance, status and task by the reasonable and general means for social learning. In order to perform it well, communication among agents requires standardized and regular information technology method. This study suggests data model as a communication tool for various agents. Therefore this study shows various agents types for collaborative learning, designation of rule for data model that enable to communicate among agents and data element of agent communication data model. A multi-agent e-learning system using like this standardized data model should able to exchange the message that is needed for communication among agents who can take charge of their independent tasks. This study should contribute to perform collaborative e-learning successfully by the application of communication data model among agents for social learning.

• Journal of the Korean Society for information Management
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• v.38 no.2
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• pp.153-172
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• 2021

This study is to create a deep learning based classification model to examine the characteristics of panic disorder and to classify the panic disorder tendency literature by the panic disorder corpus constructed for the present study. For this purpose, 5,884 documents of the panic disorder corpus collected from social media were directly annotated based on the mental disease diagnosis manual and were classified into panic disorder-prone and non-panic-disorder documents. Then, TF-IDF scores were calculated and word co-occurrence analysis was performed to analyze the lexical characteristics of the corpus. In addition, the co-occurrence between the symptom frequency measurement and the annotated symptom was calculated to analyze the characteristics of panic disorder symptoms and the relationship between symptoms. We also conducted the performance evaluation for a deep learning based classification model. Three pre-trained models, BERT multi-lingual, KoBERT, and KcBERT, were adopted for classification model, and KcBERT showed the best performance among them. This study demonstrated that it can help early diagnosis and treatment of people suffering from related symptoms by examining the characteristics of panic disorder and expand the field of mental illness research to social media.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.5
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• pp.44-56
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• 2023

This research explores the enhancement of park operation and management by analyzing the changing demands of park users. While traditional methods depended on surveys, there has been a recent shift towards utilizing social media data to understand park usage trends. Notably, most research has focused on text data from social media, overlooking the valuable insights from image data. Addressing this gap, our study introduces a novel method of assessing park usage using social media image data and then applies it to actual city park evaluations. A unique image analysis tool, built on Visual Question Answering (VQA) deep learning technology, was developed. This tool revealed specific city park details such as user demographics, behaviors, and locations. Our findings highlight three main points: (1) The VQA-based image analysis tool's validity was proven by matching its results with traditional text analysis outcomes. (2) VQA deep learning technology offers insights like gender, age, and usage time, which aren't accessible from text analysis alone. (3) Using VQA, we derived operational and management strategies for city parks. In conclusion, our VQA-based method offers significant methodological advancements for future park usage studies.