• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2003년도 가을 학술발표논문집 Vol.30 No.2 (1)
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• pp.589-591
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• 2003

현재 대부분 e-Learning에서 이루어지고 있는 교육은 학습(Loaming)이 아닌 단순 훈련(Trainning)만이 이루어지고 있다. e-Learning에서 진정한 학습이 이루어지기 위해서는 학습자의 수준에 맞는 적응적(Adaptive), 적시적(Just-in-Time) 학습이 단편적이 아닌 연속적, 통합적으로 이루어져야 한다. 이를 위해서는 기술적 관점뿐만 아니라, 발견적 학습(heuristic learning)관점에서 학습자원이 기술되고, 컴퓨터(에이전트)가 학습자원의 구성요소인 학습목표(Goal), 학습내용(Content), 학습맥락(Context), 학습구조(Structure), 학습전략(Strategy)의 의미(Semantic)와 관계(Relation)를 이해해 학습자에게 필요한 정보만을 검색, 추론해주고 이를 학습자 수준에 맞게 재가공해 학습자에게 지식(Knowledge)을 적응적(Adaptive), 적시적(Just-in-Time)으로 전달해주는 e-Learning 학습 환경이 필수적이다. 메타데이터(RDF), 온톨로지(Ontology), 에이전트(Agent) 매커니즘의 시멘틱 웹을 e-Learning 환경에 적용함으로써 학습자원의 구성요소의 의미와 관계를 파악해 적응적(Adaptive)으로 지식을 전달해 주어 자기 주도적 학습(Self-directed Loaming)을 실현해 줄 수 있다.

• 한국초등과학교육학회지:초등과학교육
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• 제39권1호
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• pp.117-132
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• 2020

The purpose of this study is to investigate elementary school teachers' awareness of Artificial Intelligence (AI) and find out how to apply it in elementary science education. The survey was conducted online and involved 95 teachers working in the metropolitan area. The results of this study are as follows. First, teachers need to learn about the general characteristics of AI and how to apply it to education. Second, science classes had the highest preference for AI among elementary school subjects. Third, the preference for AI application by elementary science field was 68.4% for earth and space, 54.7% for exercise and energy, 32.6% for matter, 27.4% for life. Fourth, AI-based Science Education (AISE) teaching- learning strategies were developed based on AI characteristics and the changing perspective of elementary science education, AISE's teaching-learning strategies are five: 'automation', 'individualization', 'diversification', 'cooperation' and 'creativity' and teachers can use them in teaching design, class practice and evaluation stages. Finally, the creative problem-solving Doing Thinking Making Sharing (DTMS) model was devised to implement the creativity strategy in AISE. This model consists of four-steps teaching courses: Doing, Thinking, Making and Sharing based on the empirical learning theory. In the future, follow-up research is needed to verify the effectiveness of this model by applying it to elementary science education.

• 정보교육학회논문지
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• 제15권1호
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• pp.39-49
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• 2011

프로그래밍 교육은 컴퓨터과학의 중요성이 부각됨에 따라 필요성이 증대되고 있다. 그러나 기존의 컴퓨터 교육은 문제 해결 과정보다는 상용 프로그램의 사용법에 치우쳐 있었다. 또한 초등학교에서의 프로그래밍 교육은 학생들의 수준에 맞지 않거나 흥미를 유발하지 못하였다. 본 연구에서는 초등학교 학생들에게 스크래치 프로그래밍 언어로 프로그래밍을 교육할 때 스캐폴딩 기반 학습 전략을 적용한 후 학생들의 프로그래밍 학습 태도를 관찰하였다. 스캐폴딩 기반 학습 전략을 적용한 결과 학생들은 프로그래밍에 대한 학습 태도에서 일반 학습 경향성, 학습을 통한 성과의 만족도 및 상호작용 항목에서 모두 향상된 결과를 보여주었다.

• STI Policy Review
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• 제8권2호
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• pp.49-74
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• 2017

What are some of the explanations for cross-national diversity of foresight performance among technological followers? Why are some countries more successful than others in learning how to develop national innovation system foresight? This paper argues that the answers are linked to organizational capacities at three different levels: governmental, policy network and social learning. To corroborate this argument, the paper chose Iran and Korea as benchmarking partners, and attempts to find out what makes Iran a slow learner in building innovation system foresight. The conceptual model is an improved model of Saritas's, by integrating Borras' and Andersen's conceptions and classifications. The data are collected from comprehensive interviews in both countries and second-hand data of international indexes. The paper, finally, concludes that it is the weakness of analytical-systemic capacity that impedes and delays the emergence of systemic foresight in Iran, and that this weakness stems from the adverse impacts of the dominant institutions, surrounding the innovation system. The final point is that it is not sufficient for Iran to learn the methods and techniques of foresight from Korea. It should learn how to open its macro-policy towards the global market and design appropriate industrial strategy in a coherent policy-strategy portfolio.

• 한국간호교육학회지
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• 제3권
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• pp.26-33
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• 1997

Problem-Based Learning(PBL) is at the forefront of educational reform. The acceptance of PBL as an educational approach with wide application represents a major change in thinking about educational processes and their relationships to the wider community. In 1969, PBL as a method was introduced at the Medical School of McMaster University in Hamilton, Canada. The most important advantages in PBL are acquiring knowledge that can be retrieved and applied, learning to learn(self-directed learning) and learning to analyze and solve Problems. PBL is widely used within the sector where it had its origin, namely health profession education. A generally accepted starting point in the development of a problem-based curriculum is the set of professional competencies of future graduates, which describe the typical problems professionals have to deal with. Formulating learning objectives highly depends on the format and content of the presented problems. Contrary to that, in a classic course in higher education, it is customary that teachers express objectives in a compulsory subject matter. Curricula which advocate problem-based learning generally use case studies in the form of paper cases, simulations and real patients with the intention of stimulating classroom discussion of clinical and basic science concepts within a problem-solving framework. One goal of using paper cases is to stimulate the learning of basic science within a clinical situation. Through self-directed study the students solve problems and explore the psycho-social dimensions within the cases. The general outcome based on the program evaluation research of PBL is that PBL students respond positively about the learning experience. In summary, PBL is a curriculum design and a teaching/learning strategy which simultaneously develops higher order thinking and disciplinary knowledge bases and skills by placing students in the active role of practitioners(or problem solvers) confronted with a situation(ill-structured problem) which reflects the real world.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.3104-3123
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• 2022

The development of Vehicular Ad hoc Network (VANET) has greatly improved the efficiency and safety of social transportation, and the routing strategy for VANET has also received high attention from both academia and industry. However, studies on dynamic matching of routing policies with the message types of VANET are in short supply, which affects the operational efficiency and security of VANET to a certain extent. This paper studies the message types in VANET and fully considers the urgency and reliability requirements of message forwarding under various types. Based on the diversified types of messages to be transmitted, and taking the diversified message forwarding strategies suitable for VANET scenarios as behavioral candidates, an adaptive routing method for the VANET message types based on reinforcement learning (RL) is proposed. The key parameters of the method, such as state, action and reward, are reasonably designed. Simulation and analysis show that the proposed method could converge quickly, and the comprehensive performance of the proposed method is obviously better than the comparison methods in terms of timeliness and reliability.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.475-483
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• 2023

The high-flux advanced neutron application reactor (HANARO) is a multi-purpose research reactor at the Korea Atomic Energy Research Institute (KAERI). HANARO has been used in scientific and industrial research and developments. Therefore, stable operation is necessary for national science and industrial prospects. This study proposed an anomaly detection system based on deep learning, that supports the stable operation of HANARO. The proposed system collects multiple sensor data, displays system information, analyzes status, and performs anomaly detection using deep autoencoder. The system comprises communication, visualization, and anomaly-detection modules, and the prototype system is implemented on site in 2021. Finally, an analysis of the historical data and synthetic anomalies was conducted to verify the overall system; simulation results based on the historical data show that 12 cases out of 19 abnormal events can be detected in advance or on time by the deep learning AD model.

• 반도체디스플레이기술학회지
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• 제16권3호
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• pp.127-130
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• 2017

In this research, we present a path planning method for an autonomous flight of unmanned aerial vehicles (UAVs) through reinforcement learning under simulated environment. We design the simulator for reinforcement learning of uav. Also we implement interface for compatibility of Deep Q-Network(DQN) and simulator. In this paper, we perform reinforcement learning through the simulator and DQN, and use Q-learning algorithm, which is a kind of reinforcement learning algorithms. Through experimentation, we verify performance of DQN-simulator. Finally, we evaluated the learning results and suggest path planning strategy using reinforcement learning.

• 디지털융복합연구
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• 제9권6호
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• pp.411-419
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• 2011

본 연구는 셀프리더십 전략이 학생들의 학습태도에 영향을 미치는지, 학습태도가 매개변인의 역할을 하여 학업성과에 어떤 영향을 미치는지를 연구하였다. 특히 중국, 필리핀 등으로부터 국내로 유학 온 학생들이 증가함에 따라 이들과 한국학생간의 차이점 유무를 비교 연구하여 효과적인 교육활동을 위한 프로그램 준비가 필요한 시점이다. 실증연구를 위한 표본으로 한국 대학생 64명과 유학 중인 중국 대학생 31명을 대상으로 설문조사를 실시하였다. 연구결과는 조직 구성원 혹은 학생들의 셀프리더십을 고양함으로써 과업에 임하는 태도나 수업에 임하는 바람직한 태도를 제시하여 기업 생산성이나 학업성과를 촉진할 수 있는 방안수립에 시사점을 줄 수 있을 것이다.

• 한국과학교육학회지
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• 제23권2호
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• pp.131-143
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• 2003

과학이 윤리적 특성을 지니고 있다는 말은 과학의 본성을 제대로 이해시키기 위해서는 각급 학교에서 과학의 윤리적 특성도 교수해야 함을 뜻한다. 외국에는 생명공학과 관련된 윤리적 문제를 다룰 것을 강조 한 교사용의 생명공학 지도서와 과학의 윤리적 측면에 관한 교수-학습의 원리와 방법을 제시한 교재가 있다. 현재 우리나라에서도 과학의 윤리적 특성에 관한 교육의 필요성이 제기되고 있으며, 그 교수-학습의 원리 방법 자료 등도 연구 개발되어 있다. 그러나 과학교육 현장에서는 과학의 윤리적인 특성에 관한 교수-학습이 이루어지지 않고 있다. 이는 그 교수-학습 방법과 자료를 현장에 적용할 방안이 미흡하기 때문이기도 하다. 이 연구는 특별히 연구자들이 3년간 수행한 연구의 결과를 바탕으로 과학의 윤리적 특성 교수-학습 방법과 자료를 현장에 투입할 방안을 제시할 목적으로 수행하였다.