• 디지털융복합연구
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• 제19권6호
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• pp.11-21
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• 2021

본 연구는 인문계열 학생들에게 생소하고 어려운 프로그래밍 교육의 효과적인 학습이 가능하도록 비교과프로그램 운영을 통한 학습의 효과성을 살펴보고자 한다. 인문계열 학생들 A학과와 B학과 70명 대상으로 한 학기 수업을 통해 수집된 학습관련 데이터와 창의융합 앱개발 공모전 비교과프로그램 활동을 통해 수집한 데이터, 설문지를 바탕으로 분석한 결과 비교과프로그램 활동이 학업성취도에 영향을 미치는 것으로 나타났다. 교육과정 참여 전후에 실시한 학생들의 핵심역량 진단 검사결과는 교육과정 참여 후 핵심역량이 A학과와 B학과 모두 향상된 것으로 나타났다. 본 연구는 비교과프로그램 활동이 개인의 역량 증진에 도움이 됨과 동시에 은둔형 학생들에게 맞춤지도를 하여 학업성취도 향상을 기대할 수 있다고 본다. 향후 수업진행시 일반적인 앱개발보다는 전공과 관련된 앱을 개발할 수 있도록 학과별 맞춤지도를 하여 전공분야와 융합하여 문제를 해결할 수 있는 능력, 컴퓨팅적 사고력, 창의적 사고력 향상을 기대해 본다.

• 인터넷정보학회논문지
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• 제24권1호
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• pp.39-47
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• 2023

The development of autonomous driving and Advanced Driver Assistance System (ADAS) technology has grown rapidly in recent years. As most traffic accidents occur due to human error, self-driving vehicles can drastically reduce the number of accidents and crashes that occur on the roads today. Obviously, technical advancements in autonomous driving can lead to improved public driving safety. However, due to the current limitations in technology and lack of public trust in self-driving cars (and drones), the actual use of Autonomous Vehicles (AVs) is still significantly low. According to prior studies, people's acceptance of an AV is mainly determined by trust. It is proven that people still feel much more comfortable in personalized ADAS, designed with the way people drive. Based on such needs, a new attempt for a customized ADAS considering each driver's driving style is proposed in this paper. Each driver's behavior is divided into two categories: assertive and defensive. In this paper, a novel customized ADAS algorithm with high classification accuracy is designed, which divides each driver based on their driving style. Each driver's driving data is collected and simulated using CARLA, which is an open-source autonomous driving simulator. In addition, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) machine learning algorithms are used to optimize the ADAS parameters. The proposed scheme results in a high classification accuracy of time series driving data. Furthermore, among the vast amount of CARLA-based feature data extracted from the drivers, distinguishable driving features are collected selectively using Support Vector Machine (SVM) technology by comparing the amount of influence on the classification of the two categories. Therefore, by extracting distinguishable features and eliminating outliers using SVM, the classification accuracy is significantly improved. Based on this classification, the ADAS sensors can be made more sensitive for the case of assertive drivers, enabling more advanced driving safety support. The proposed technology of this paper is especially important because currently, the state-of-the-art level of autonomous driving is at level 3 (based on the SAE International driving automation standards), which requires advanced functions that can assist drivers using ADAS technology.

• 정보교육학회논문지
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• 제16권2호
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• pp.223-231
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• 2012

최근 스마트폰 보급에 따른 디지털 네이티브의 등장으로 교육에 있어서도 이에 걸 맞는 변화가 필요하게 되었다. 기존의 E-Learning, U-Learning 을 보다 학습자 중심, 맞춤형 교육에 근접하도록 실현할 수 있는 교수학습용 자료와 소프트웨어가 필요한 것이다. 이에 따라 초등학생의 발달 단계에 맞는 음성언어 중심의 영어 학습 프로그램을 교육과학기술부가 추천하는 초등학생을 위한 영어 단어를 기반으로 한 스마트폰에서 학습할 수 있도록 어플리케이션을 설계하고 구현하여 초등학교 학교 현장에서의 스마트러닝의 적용 및 발전을 위한 창의적인 아이디어를 제시해 보고자 한다.

• 인터넷정보학회논문지
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• 제20권5호
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• pp.79-86
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• 2019

This paper is an overview of key elements of Korea National Open University's smart mobile learning system, and an attempt to evaluate its main services relative to the FRAME model and the Mobile Learning Development Model for distance learning in higher education. KNOU improved its system architecture to one based on xMOOC e-learning content delivery while also upgrading its PC-based online/mobile learning services to facilitate an easier and more convenient access to lectures and for better interactivity. From the users' viewpoint, the upgraded 'U-KNOU Campus' allows for a more integrated search capability coupled with better course recommendations and a customized notification service. Using the new system, the students can access not only the school- and peer-issued messages via online bulletin boards but also share information and pose questions to others including to the school faculty/officials and system administrators. Additionally, a new mobile payment method has been incorporated into the system so that the students can select and pay for additional courses from anywhere. In spite of these advances, the issue of device usability and content development remain; specifically U-KNOU Campus needs to improve its instructor-learner and learner-to-learner interactivity and mobile evaluation interface.

• 드라이브 ㆍ 컨트롤
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• 제18권4호
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• pp.9-18
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• 2021

This study proposes a method for creating learning datasets to recognize obstacles using deep learning algorithms in automated construction machinery or an autonomous vehicle. Recently, many researchers and engineers have developed various recognition algorithms based on deep learning following an increase in computing power. In particular, the image classification technology and image segmentation technology represent deep learning recognition algorithms. They are used to identify obstacles that interfere with the driving situation of an autonomous vehicle. Therefore, various organizations and companies have started distributing open datasets, but there is a remote possibility that they will perfectly match the user's desired environment. In this study, we created an interface of the virtual simulator such that users can easily create their desired training dataset. In addition, the customized dataset was further advanced by using the RDBMS system, and the recognition rate was improved.

• 교육녹색환경연구
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• 제19권1호
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• pp.13-24
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• 2020

본 연구는 미래 교수-학습방법 유형과 학습 공간 유형을 분석하여 교수-학습방법 유형에 적합한 공간 유형을 연결(matching)해보고, 공간 유형별 교수-학습방법과 학습양식의 활용정도를 학교급별로 제안하고자 하였다. 그 결과, 플립 러닝, 디퍼 러닝, 협력 학습, 몰입형 가상현실 학습, 놀이 학습, OER활용 학습 등 6가지의 교수-학습방법 유형과 놀이 및 탐구 공간, 제작 및 거치 공간, 발표 및 전시 공간, 독립된 학습 공간, 학습의 장으로서의 교실, 학습의 내용으로서의 교실 등 6가지의 학습 공간 유형을 도출하였다. 아울러 Table 12와 13과 같이 미래 교수-학습방법 유형에 적합한 공간 유형을 연결해보고, 공간 유형별 교수-학습방법뿐만 아니라 22가지 학습양식의 활용정도를 학교급 또는 학년군별로 제시하였다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
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• pp.369-374
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• 2000

Despite their tilde application of some traditional project management techniques like the Program Evaluation and Review Technique, they lack of learning, one of important factors in many disciplines today due to a static view far prefect progression. This study proposes a framework for estimation by learning based on a Linear Bayesian approach. As a project progresses, we sequentially observe the durations of completed activities. By reflecting this newly available information to update the distribution of remaining activity durations and thus project duration, we can implement a decision support system that updates e.g. the expected project completion time as well as the probabilities of completing the project within talc due date and by a certain date. By Implementing such customized systems, project manager can be aware of changing project status more effectively and better revise resource allocation plans.

• 실천공학교육논문지
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• 제16권4호
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• pp.409-414
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• 2024

본 논문은 인공지능(AI)을 활용하여 장애인 직업 훈련 평가 데이터를 분석하고, 다양한 머신러닝 알고리즘을 통해 최적의 예측 모델을 선정하는 연구를 수행한다. 훈련생의 성별, 나이, 학력, 장애 유형, 기초 학습 능력 등의 데이터를 분석하여 취업 가능성이 높은 직종을 예측하고, 이를 바탕으로 맞춤형 훈련 프로그램을 설계하여 훈련 효율성과 취업 성공률을 높이는 것을 목표로 한다.

• 대한통합의학회지
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• 제9권1호
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• pp.141-150
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• 2021

Purpose : The purpose of this study was to investigate the effect of case-based learning application in human growth development classes on nursing students' problem-solving ability, self-directed learning ability, and academic self-efficacy. Methods : The research method was a self-report questionnaire before and after case-based learning for second-year nursing students who took the human growth development course at U University in K city. The collected data were statistically processed using SPSS WIN 21.0. Results : The results of the study showed that after case-based learning, problem-solving ability, self-directed learning ability, and academic self-efficacy were all significantly improved. In addition, as a result of examining the correlation between each variable after case-based learning, problem solving ability score and self-directed learning ability score (r=.54, ｐ<.01), and problem solving ability scores and academic self-efficacy scores (r=.44, ｐ<.01), were significantly correlated with self-directed learning ability scores and the academic self-efficacy reduction scores (r=.76, ｐ<.01). Conclusion : The results of this study suggested the need for various learning programs such as case-based learning to improve nursing students' problem-solving abilities and self-directed learning abilities and their application. In addition, to improve the learning self-efficacy of nursing students, a continuous and systematic study is suggested to develop and apply customized educational programs according to the learners' preferences. Since the sample group in this study was limited to one university, there were few cases and no control group, so there are limitations in generalizing the test effect, However, significant differences a were verified in the case-based learning pre-tests and post-tests.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 추계학술대회
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• pp.581-584
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• 2013

e-Learning은 기술기반학습으로 정보통신 기술을 활용하여 지식을 획득하는 과정이다. 이 과정에서 기업교육 담당자의 역할 또한 새로운 변화를 요구받고 있으며, 기업교육 현장에서 e-Learning 팀장이나 교육담당자 등을 포함한 e-Learning을 담당하고 있는 기업의 HR 담당자들 또한 e-Learning에 의한 변화를 심하게 겪고 있다. 그 이유는 기업 특성과 관련하여 내부적으로 HR 담당자의 교육 훈련에 대한 경험축적은 e-Learning 도입 및 활용에 도움을 주기 때문이며, 수많은 커리큘럼이 mass customization화 되어 있기 때문에 이를 명확하게 선정하여 정의하는 것이 HR 담당자들의 몫이기 때문이다. 본 연구는 이러한 인식을 토대로 하여 호텔업에서의 e-Learning 도입과 활용이 호텔의 HR 담당자에게 어떠한 영향을 미치며, 그들 자신의 역할에 어떠한 변화를 가져오는가에 대해 해석학적 현상학(hermeneutic phenomenology)을 채택하여 살펴보고자 하였다.