• 제목/요약/키워드: learning management

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중국 3대 경제권 자동차 산업에 대한 연구: 기술학습, 아키텍처, 클러스터를 중심으로 (An Integrative Research on Chinese Automobile Industry in Three Economic Blocs: Focusing on Technological Learning, Architecture, and Cluster Approach)

  • 백서인;김희태;권상집
    • 지식경영연구
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    • 제15권4호
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    • pp.147-170
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    • 2014
  • This study investigates the main characteristics of Chinese automobile industry based on the technology learning, architecture theory and cluster. As a case study sample, we chose three most representative automobile firms from three main cities in China, FAW from northern part of China, SAIC from middle part of China, and BYD from southern part of China. According to the research findings, FAW has equipped self-production ability in virtue of political support but felled behind in future transportation due to lack of convergence with local cluster. In case of SAIS, similar phenomenon happened in spite of highest purchasing power of shanghai. BYD has achieved great quantum jump through the aggressive investment strategy in electric vehicle even though there are still many technological learning and experience to be cumulated. Overall, this research extends the current literature on key roles (technological learning, architecture, and cluster features) in the automobile industry growth by suggesting their crucial aspects in knowledge management and strategic planning to a newly emerging market, China, and sheds light on the relationship between regional characteristics and automobile growth.

MOOC 기반 이러닝 서비스의 질 관리 방안에 관한 연구 (A Study on Quality Management of MOOC-based e-Learning Service)

  • 박정호;최은영
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2017년도 춘계학술대회
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    • pp.219-221
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    • 2017
  • 최근 오픈 콘텐츠의 성격을 가지는 MOOC(Massive Open Online Course)가 여러 대학에서 서비스되면서 대학교육의 패러다임을 변화시키고 있으며, 이와 함께 MOOC 기반 이러닝 서비스도 다양한 유형으로 발전하고 있다. 지금까지 MOOC 기반 이러닝 서비스의 질 관리는 MOOC의 유형에 관계없이 MOOC가 제공하는 일반적인 요소들을 대상으로 연구되어 왔다. 본 연구에서는 MOOC 유형별로 이러닝 서비스의 질에 영향을 미치는 요인 분석을 통해 MOOC 기반 이러닝 서비스의 질 관리를 개선하기 위한 방안을 제시한다.

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The Moderating Role of Environmental Turbulence between Learning Orientation and SME Performance in the Manufacturing Sector of Pakistan

  • SAJJAD, Ali;IBRAHIM, Yusnidah;SHAMSUDDIN, Jauriyah
    • 유통과학연구
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    • 제20권5호
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    • pp.1-11
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    • 2022
  • Purpose: This study attemptsto investigate the moderating effects of environmental turbulence (ET) between learning orientation (LO) and SMEs' performance. Research design, data, and Methodology: To gain insights and provide implications for manufacturing SMEs in Pakistan, this study adopted simple random sampling to collect 379 valid responses. Data were collected through a self-administrative questionnaire from manufacturing SMEs owners/managers. Partial least squares of structural equation modeling have been used to test research hypotheses by using SmartPLS® 3.0 software. Results: The study's primary finding is that LO has a significantly positive effect on SMEs' performance and this relationship is strengthened under the moderating influence of environmental turbulence (ET). Conclusion: Environmental turbulence (ET) enables SMEs to focus on learning capability to get a more competitive advantage. Moreover, SMEs owner/managers ought to emphasize continuous learning that accentuates the capability to compete with environmental changes. Findings support notifying Pakistan's Small and Medium Enterprise Development Authority (SMEDA) in dealings with Manufacturing SMEs in terms of improving their internal capabilities. This research contributes to the literature as it provides a more detailed and in-depth explanation of distribution management-related issues faced by SMEs. This research carries a significant influence on literature and relevant Resource-based view and contingency theories.

Video Learning Enhances Financial Literacy: A Systematic Review Analysis of the Impact on Video Content Distribution

  • Yin Yin KHOO;Mohamad Rohieszan RAMDAN;Rohaila YUSOF;Chooi Yi WEI
    • 유통과학연구
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    • 제21권9호
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    • pp.43-53
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    • 2023
  • Purpose: This study aims to examine the demographic similarities and differences in objectives, methodology, and findings of previous studies in the context of gaining financial literacy using videos. This study employs a systematic review design. Research design, data and methodology: Based on the content analysis method, 15 articles were chosen from Scopus and Science Direct during 2015-2020. After formulating the research questions, the paper identification process, screening, eligibility, and quality appraisal are discussed in the methodology. The keywords for the advanced search included "Financial literacy," "Financial Education," and "Video". Results: The results of this study indicate the effectiveness of learning financial literacy using videos. Significant results were obtained when students interacted with the video content distribution. The findings of this study provide an overview and lead to a better understanding of the use of video in financial literacy. Conclusions: This study is important as a guide for educators in future research and practice planning. A systematic review on this topic is the research gap. Video learning was active learning that involved student-centered activities that help students engage with financial literacy. By conducting a systematic review, researchers and readers may also understand how extending an individual's financial literacy may change after financial education.

Leveraging Visibility-Based Rewards in DRL-based Worker Travel Path Simulation for Improving the Learning Performance

  • Kim, Minguk;Kim, Tae Wan
    • 한국건설관리학회논문집
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    • 제24권5호
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    • pp.73-82
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    • 2023
  • Optimization of Construction Site Layout Planning (CSLP) heavily relies on workers' travel paths. However, traditional path generation approaches predominantly focus on the shortest path, often neglecting critical variables such as individual wayfinding tendencies, the spatial arrangement of site objects, and potential hazards. These oversights can lead to compromised path simulations, resulting in less reliable site layout plans. While Deep Reinforcement Learning (DRL) has been proposed as a potential alternative to address these issues, it has shown limitations. Despite presenting more realistic travel paths by considering these variables, DRL often struggles with efficiency in complex environments, leading to extended learning times and potential failures. To overcome these challenges, this study introduces a refined model that enhances spatial navigation capabilities and learning performance by integrating workers' visibility into the reward functions. The proposed model demonstrated a 12.47% increase in the pathfinding success rate and notable improvements in the other two performance measures compared to the existing DRL framework. The adoption of this model could greatly enhance the reliability of the results, ultimately improving site operational efficiency and safety management such as by reducing site congestion and accidents. Future research could expand this study by simulating travel paths in dynamic, multi-agent environments that represent different stages of construction.

A Study on the Establishment of Odor Management System in Gangwon-do Traditional Market

  • Min-Jae JUNG;Kwang-Yeol YOON;Sang-Rul KIM;Su-Hye KIM
    • 웰빙융합연구
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    • 제6권2호
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    • pp.27-31
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    • 2023
  • Purpose: Establishment of a real-time monitoring system for odor control in traditional markets in Gangwon-do and a system for linking prevention facilities. Research design, data and methodology: Build server and system logic based on data through real-time monitoring device (sensor-based). A temporary data generation program for deep learning is developed to develop a model for odor data. Results: A REST API was developed for using the model prediction service, and a test was performed to find an algorithm with high prediction probability and parameter values optimized for learning. In the deep learning algorithm for AI modeling development, Pandas was used for data analysis and processing, and TensorFlow V2 (keras) was used as the deep learning library. The activation function was swish, the performance of the model was optimized for Adam, the performance was measured with MSE, the model method was Functional API, and the model storage format was Sequential API (LSTM)/HDF5. Conclusions: The developed system has the potential to effectively monitor and manage odors in traditional markets. By utilizing real-time data, the system can provide timely alerts and facilitate preventive measures to control and mitigate odors. The AI modeling component enhances the system's predictive capabilities, allowing for proactive odor management.

교육적 가치를 높이는 디지털배지 설계와 활용 연구 (Research on the Design and Use of Digital Badges to Increase Educational Value)

  • 민연아;이지은
    • 한국IT서비스학회지
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    • 제22권6호
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    • pp.71-86
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    • 2023
  • The rapid change in industry and the technological gap give rise to social demand for upskilling and reskilling and spread of alternative education. Against this backdrop, digital certification and career management tools can be used to manage various types of learning activities comprehensively. Digital badges provide various kinds of history information related to individual learning, and the reliability and transparency of the issued information can be strengthened by applying blockchain technology. There have been various discussions about digital badges for a long time, but due to the lack of standards to support the issuance and distribution of digital badges, they have been partially used in some areas. However, interest in digital badges is increasing due to the development of related technologies, establishment of standards, paradigm changes in higher education, and government policies related to nurturing digital talent. This paper deals with the use of digital badges for efficient and transparent learning management and career management in an online learning environment. The researcher analyzes the technical characteristics and use cases of digital badges, and proposes a plan for use in online higher education based on them.

e-learning 컨텐츠 품질이 사용자 만족에 미치는 영향

  • 박성택;이승준;김영기
    • 한국디지털정책학회:학술대회논문집
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    • 한국디지털정책학회 2006년도 추계학술대회
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    • pp.421-431
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    • 2006
  • 지식정보사회의 핵심 키워드인 e-learning은 많은 발전을 하고 있다. e-learning은 오프라인 교육에 비해 시간과 공간의 제약을 받지 아니하고, 비용이 저렴하며 반복 학습과 개인화된 서비스가 가능하다는 장점이 있는 반면에 아직도 파급 효과는 크지 못한 실정이다. 또한 국가적인 차원에서 많은 지원을 하고 있고 시장의 급속한 성장과 확산에 비해, 중${\cdot}$고생들을 대상으로 하는 e-learning사이트의 컨텐츠 품질에 대한 연구는 미비한 실정이다. 이에 본 연구에서는 중${\cdot}$고생 시절에e-learning의 경험이 있는 대학생들을 중심으로 실증연구를 수행하였다.

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Design and Implementation of Operating Management System for e-Learning

  • Kwak, Young-Tae
    • Journal of the Korean Data and Information Science Society
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    • 제14권4호
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    • pp.863-875
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    • 2003
  • The existing e-learning systems have short functions for learners to lead their self-directed learning activities because those systems have not been integrated with functions supporting activities of learners, instructors and operators. Therefore, we designed and implemented an efficient e-learning system having fully integrated functions to let learners induce their active learning, instructors teach learners effectively and evaluate their learning activities, and operators handle curriculum affairs and system environments.

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오토인코더에 기반한 딥러닝을 이용한 사이버대학교 학생의 학업 성취도 예측 분석 시스템 연구 (Study for Prediction System of Learning Achievements of Cyber University Students using Deep Learning based on Autoencoder)

  • 이현진
    • 디지털콘텐츠학회 논문지
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    • 제19권6호
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    • pp.1115-1121
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    • 2018
  • 본 논문에서는 사이버대학교 학습관리시스템에 누적된 데이터를 기반으로 학습 성과를 예측하기 위하여 딥러닝에 기반한 데이터 분석 방법을 연구하였다. 학습자의 학업 성취도를 예측하면, 학습자의 학습을 촉진하여 교육의 질을 높일 수 있는 도구로 활용될 수 있다. 학습 성과의 예측의 정확도를 향상시키기 위하여 오토인코더에 기반하여 한학기 출결 상황을 예측하고, 학기 진행 중인 평가 요소들과 결합하여 딥러닝으로 학습하여 최종 예측의 정확도를 높였다. 제안하는 예측 방법을 검증하기 위하여 학습 진행 과정의 출결데이터의 예측과 평가요소 데이터를 활용하여 최종학습 성취도를 예측하였다. 실험을 통하여 학기 진행중에 학습자의 성취도를 예측할 수 있는 것을 보였다.