• 디지털융복합연구
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• 제13권1호
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• pp.77-83
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• 2015

본 연구는 이러닝의 학습효과 및 만족도에 대한 한계가 대두되고, 이러닝 산업의 구조적 모순이 지속됨에 따라 이를 해결하기 위한 정책적 대안을 제시하고자 수행되었다. 이러닝의 한계의 극복과 이러닝 산업의 건전한 성장을 위한 수단으로서 이러닝에서의 빅데이터 적용 방안을 제시하고, 이에 대한 정책 실천과제를 제안하였다. 정책 실천과제로서 첫째, 기술개발 지원, 둘째, 전문인력 양성, 셋째, 중소기업 보급 지원, 넷째, 법/제도 개선을 꼽고 이에 대한 체계적 추진을 제언하였다.

• 지식경영연구
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• 제6권1호
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• pp.105-122
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• 2005

The LG Electronics case shows the process whereby an organization evolves as a learning organization through the integration of e-learning and knowledge management. In other words, it shows the process whereby e-learning is recognized as an important means of solving a problem concerning actual worksite operations, as it became one of the daily activities in the organization. In terms of organizational learning, this process points to the fact that e-learning is emerging as the fastest and most effective means of transferring the internally shared value of a company. Recently, advanced corporations and organizations have been endeavoring to boost their internal and external customer satisfaction and customer loyalty, paving the way for changes in their organizational cultures, and establishing learning organizations through e-learning. Therefore, from an advanced viewpoint, e-learning within a company is not a simple system of transferring educational contents, but is a knowledge portal concept connected with knowledge management. To achieve this end, the organization is required to undergo changes that is, it should make the acquisition of learning possible through e-learning and a knowledge management system (KMS) in order to improve corporate performance. Since LG Electronics is utilizing e-learning as a strategic means to change the paradigm of corporate education, and, in particular, is attempting to integrate this with knowledge management, insights that will facilitate the understanding of the core success factors in and challenges to the integration of knowledge management and e-learning can be obtained through this case.

• Educational Technology International
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• 제21권2호
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• pp.155-191
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• 2020

The aim of this study was to examine the trends (e.g., the distribution of the studies by year, country, research methods, and participants' education level) and fundamental findings [e.g., interaction in Virtual Reality (VR) environments, educational content through VR and Augmented Reality (AR) technologies, learning environment in AR, etc.] regarding immersive learning technologies such as VR and AR in English Language Teaching (ELT) between 2010 and 2019. Employing a systematic review research methodology, data was gathered from 59 academic articles published in the following databases: EBSCOhost, ERIC, Web of Science, and Taylor & Francis. The studies were analyzed using a content analysis approach, and findings demonstrated that immersive learning technologies in ELT came to prominence in 2017. Mixed methods research was the most widely employed research method. The most studied language skill was vocabulary for AR and speaking for VR. The results also revealed advantages and challenges with regards to the use of immersive learning technologies in ELT. Further analysis illustrated the findings related to characteristics of immersive learning technologies in ELT. Based on this review, research and design implications for researchers and practitioners are presented.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.214-222
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• 2021

Recently, the growth of e-commerce in Saudi Arabia has been exponential, bringing new remarkable challenges. A naive approach for product matching and categorization is needed to help consumers choose the right store to purchase a product. This paper presents a machine learning approach for product matching that combines deep learning techniques with standard artificial neural networks (ANNs). Existing methods focused on product matching, whereas our model compares products based on unstructured descriptions. We evaluated our electronics dataset model from three business-to-consumer (B2C) online stores by putting the match products collectively in one dataset. The performance evaluation based on k-mean classifier prediction from three real-world online stores demonstrates that the proposed algorithm outperforms the benchmarked approach by 80% on average F1-measure.

• 한국항해항만학회지
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• 제38권3호
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• pp.193-202
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• 2014

The comprehensive review of the STCW 1978, as amended in 1995 and associated Code was carried out from 2006 to 2010. These amendments will have a certain degree of impact on Maritime Education and Training(MET) institutes in terms of education and training of seafarer worldwide. Particularly, the Far East region countries are effected more than other regions since they covered about 30% of officers and 37% ratings in the world. In view of these facts this dissertation conceived to analyze the problems in the Far East main seafarer supply countries faced the implementation of "STCW Manila Amendments" To analyze these problems, this dissertation carried out questionnaire research to 7 targeted main MET of major Far East seafarer supply countries. After research this dissertation suggests the possible solutions such as, Joint On-Board Training Center; Joint Asia Maritime E-learning Systems; methods to reducing work-load, ship inspection burden and determine mandatory minimum safety manning standards in a safe way; technical cooperation fund to installation of training equipment; and clarify vague terminology of STCW Manila Amendments, to solve problems identified through the questionnaires.

• Educational Technology International
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• 제11권2호
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• pp.149-172
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• 2010

Knowledge can be more meaningful when it is shaped and personalized through interaction with others. Implementation of open learning environments such as open courseware or shared knowledge communities has gradually become more common. A case study which investigated instructors' experiences and perceptions of publishing and using open courseware in the classroom was conducted at a university in Korea. Responses from participating students and an evaluation group regarding how they perceived open learning environments were also examined. Based on the inductive analysis of the data, this study discusses advantages and challenges of publishing open courseware and collaborative learning environments. Also, practical guidelines for developing reusable learning materials are suggested.

• International Journal of Computer Science & Network Security
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• 제21권2호
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• pp.54-65
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• 2021

The movement control order and shutting down educational institution in Saudi Arabia has jeopardized the teaching and learning process. Education was shifted to distance learning in order to avoid any academic loss. In the middle of the Covid-19 crisis, there is a need to assess the full image of e-learning in Saudi Arabia. To investigate student and teachers' perception and acceptance, parents' attitudes and believes about distance education are the main goals of the study. The mix-method research design was employed to collect data. Three surveys were distributed to 100 students and 50 teachers and 50 parents from different educational institutions in Saudi Arabia, while semi-structured interviews were conducted with 10 parents. Random stratified and convenient sampling methods were adopted. Both descriptive and content analysis was conducted using SPSS25.0 and NVIVO software for quantitative and qualitative data accordingly. The findings showed that students are comfortable with remote education and are receiving enough support from schools and instructors but they think online education can't replace conventional face-to-face learning. Moreover, the results showed that teachers are having challenges in preparing online classes because of the development of conducting online classes and the lack of training. However, parents showed negative attitudes regarding the benefits and values of remote education and preferred conventional learning styles in elementary schools. Parents tended to reject and resist distance learning for several reasons: professional knowledge and lack of time to support their young kids in online classes, the shortcomings of e-learning, young children's inadequate self-regulation. Saudi parents are neither trained nor ready to use e-learning. The study provided suggestion and implications for teacher education and policymakers.

• 디지털융복합연구
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• 제13권7호
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• pp.9-21
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• 2015

최근 대학이러닝 환경은 급변하고 있고, 특히 글로벌 유수 대학을 중심으로 한 MOOCs 서비스의 확산은 국내 대학이러닝에도 새로운 변화와 도전을 촉진하고 있다. 급변하는 이러닝 환경 속에서 대학이러닝은 MOOCs를 중심으로 어떻게 변화하고 발전해 나갈 것인지 융복합적인 관점에서 발전방안에 대한 탐색이 요구된다. 이에 본 연구에서는 MOOCs를 기반으로 대학이러닝의 융복합적인 발전방안을 개념적 틀과 함께 제안하였다. 본 연구를 위해 대학이러닝 및 MOOCs 관련 문헌 연구, 전문가 자문회의, 대학이러닝을 둘러싼 SWOT 분석, 대학이러닝지원센터 관련자 대상 설문 등을 실시하였다. 이러한 과정을 통해 MOOCs의 특성을 반영한 '개방형 고등교육 강좌 서비스', '교수학습 큐레이션 서비스', '교수학습 프랙티스 서비스', '창의적 교수학습 방법 개발 및 공유 서비스', '클라우드 기반의 교육용 플랫폼 지원 서비스' 등의 이슈를 융복합적으로 통합한 안을 도출하였고, MOOCs 기반으로 한 융복합적 발전방안을 마련하였다. 본 연구 결과를 통해 대학이러닝의 도약적 발전을 위한 방안이 제시되고, 아울러 국내 MOOCs의 도입과 적용에 대한 논의의 기초가 마련될 것으로 기대된다.

• 대한원격탐사학회지
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• 제36권4호
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• pp.609-626
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• 2020

Satellite-based land surface temperature (LST) has been used as one of the major parameters in various climate and environmental models. Especially, Moderate Resolution Imaging Spectroradiometer (MODIS) LST is the most widely used satellite-based LST product due to its spatiotemporal coverage (1 km spatial and sub-daily temporal resolutions) and longevity (> 20 years). However, there is an increasing demand for LST products with finer spatial resolution (e.g., 10-250 m) over regions such as urban areas. Therefore, various methods have been proposed to produce high-resolution MODIS-like LST less than 250 m (e.g., 100 m). The purpose of this review is to provide a comprehensive overview of recent research trends and challenges for the downscaling of MODIS LST. Based on the recent literature survey for the past decade, the downscaling techniques classified into three groups-kernel-driven, fusion-based, and the combination of kernel-driven and fusion-based methods-were reviewed with their pros and cons. Then, five open issues and challenges were discussed: uncertainty in LST retrievals, low thermal contrast, the nonlinearity of LST temporal change, cloud contamination, and model generalization. Future research directions of LST downscaling were finally provided.

• Smart Structures and Systems
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• 제24권5호
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• pp.669-681
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• 2019

Bridge collapses may deliver a huge impact on our society in a very negative way. Out of many reasons why bridges collapse, poor maintenance is becoming a main contributing factor to many recent collapses. Furthermore, the aging of bridges is able to make the situation much worse. In order to prevent this unwanted event, it is indispensable to conduct continuous bridge monitoring and timely maintenance. Visual inspection is the most widely used method, but it is heavily dependent on the experience of the inspectors. It is also time-consuming, labor-intensive, costly, disruptive, and even unsafe for the inspectors. In order to address its limitations, in recent years increasing interests have been paid to the use of unmanned aerial vehicles (UAVs), which is expected to make the inspection process safer, faster and more cost-effective. In addition, it can cover the area where it is too hard to reach by inspectors. However, this strategy is still in a primitive stage because there are many things to be addressed for real implementation. In this paper, a typical procedure of bridge inspection using UAVs consisting of three phases (i.e., pre-inspection, inspection, and post-inspection phases) and the detailed tasks by phase are described. Also, three major challenges, which are related to a UAV's flight, image data acquisition, and damage identification, respectively, are identified from a practical perspective (e.g., localization of a UAV under the bridge, high-quality image capture, etc.) and their possible solutions are discussed by examining recently developed or currently developing techniques such as the graph-based localization algorithm, and the image quality assessment and enhancement strategy. In particular, deep learning based algorithms such as R-CNN and Mask R-CNN for classifying, localizing and quantifying several damage types (e.g., cracks, corrosion, spalling, efflorescence, etc.) in an automatic manner are discussed. This strategy is based on a huge amount of image data obtained from unmanned inspection equipment consisting of the UAV and imaging devices (vision and IR cameras).