• 한국수학교육학회지시리즈A:수학교육
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• 제53권1호
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• pp.75-92
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• 2014

In this paper, we summarize briefly some of the most salient features of Repkina & Zaika's theory of learning action formation levels. We concretize Repkina & Zaika's theory by comparing various points of view of Uoo, Polya, Krutetskii, and Davydov et al. In this study we are able to diagnose students' learning action formation levels in the process of mathematics problem solving. In addition we use interview method to collect various information about students' levels. As a result we suggest data related with each level of learning action formation, and characteristics of students who belong to each level of learning action formation.

• 한국건축시공학회지
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• 제13권1호
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• pp.10-19
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• 2013

Companies want universities to produce graduates with creativity and problem-solving skills, and for this reason universities have extended engineering design education, including in the field of architectural engineering. This paper investigates an engineering design class in the Department of Architectural Engineering, J University. The class was taught in 2010 and 2011using an Action Learning (AL) teaching-learning strategy. The students responded that the level of participation and satisfaction was high in the Action Learning classes, and role allocation or responsibility and communication of the project teams were very effective. But it was also found that as Action Learning is such a new method for students of engineering design, an orientation session that describes what to do and what to prepare should be given before the class starts.

• Human Ecology Research
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• 제58권4호
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• pp.561-583
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• 2020

This study developed and implemented a teaching · learning process plan for Home Economics in middle school by converging Habermas's three systems of action. It also examined the effect of the class through the evaluation of students and teachers who participated in the class. This study developed 10 sessions for a teaching and learning process plan by converging three systems of action and reconstructing learning elements related to 'balanced meal plan' and 'food choice' according to the practical action teaching model. After class, we surveyed the degree of help for students, analyzed the learning activity sheets, and analyzed the reflection journals of teachers to evaluate the effects of the class. This class was found to be the most helpful in practicing the healthy dietary life of students, expanding their thoughts, understanding learning contents, and helping them change their lives. As a result of analyzing the learning activity sheet, students gained enlightenment by reflecting and evaluating their action through the class; in addition, changes in interest, awareness, and action appeared. Through the convergence of three systems of action, teachers who practiced the class criticized and realized the act that students were unconsciously accepted. In addition, it confirmed the possibility that students could change their lives, family and society by promoting optimal nutrition and health for a good life that pursues the best good.

• 한국콘텐츠학회논문지
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• 제18권5호
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• pp.525-538
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• 2018

액션러닝은 실제 문제를 찾아 해결책을 찾는 과정을 통해 학습이 이루어지는 교수방법으로 최근 대학 수업에서도 그 사례 연구가 수행되고 있다. 본 연구의 목적은 서울에 위치한 S 대학교의 아동청소년학과에 개설된 '아동미디어교육' 수업에서 액션러닝 교수법을 실시하고 그 효과성 여부를 조사하는 것이다. Marquardt(2000)가 제안한 액션러닝의 구성 요소들과 과정에 따라 학생들은 아동의 뉴스리터러시 교육이라는 과제를 도출하였으며 초등 6학년을 위한 뉴스리터러시 교육 목적과 목표, 내용을 설정하고 교수학습방법을 개발하여 교육현장에 적용하였다. 액션러닝 수업에 대한 대학생들의 반응과 평가는 설문지와 구두로 수집되었다. 그들은 액션러닝 적용 수업 방식을 통한 능동적이며 자발적인 문제 탐구와 현장에서의 적용이 아동미디어교육 수업 목표를 달성하는데 도움을 주었다고 답하였다. 마지막으로, 액션러닝 수업방식의 필요 조건으로서 교육 현장과의 긴밀한 협조와 현장 적용 시 적절한 피드백의 중요성이 논의되었다.

• 로봇학회논문지
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• 제15권4호
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• pp.404-412
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• 2020

Typically everyday human life tasks involve at least two people moving objects such as tables and beds, and the balancing of such object changes based on one person's action. However, many studies in previous work performed their tasks solely on robots without factoring human cooperation. Therefore, in this paper, we propose cooperative robot for table balancing using Q-learning that enables cooperative work between human and robot. The human's action is recognized in order to balance the table by the proposed robot whose camera takes the image of the table's state, and it performs the table-balancing action according to the recognized human action without high performance equipment. The classification of human action uses a deep learning technology, specifically AlexNet, and has an accuracy of 96.9% over 10-fold cross-validation. The experiment of Q-learning was carried out over 2,000 episodes with 200 trials. The overall results of the proposed Q-learning show that the Q function stably converged at this number of episodes. This stable convergence determined Q-learning policies for the robot actions. Video of the robotic cooperation with human over the table balancing task using the proposed Q-Learning can be found at http://ibot.knu.ac.kr/videocooperation.html.

• Nuclear Engineering and Technology
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• 제54권9호
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• pp.3283-3292
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• 2022

Based on the Deep Q-Network(DQN) algorithm of reinforcement learning, an active fault-tolerance method with incremental action is proposed for the control system with sensor faults of the once-through steam generator(OTSG). In this paper, we first establish the OTSG model as the interaction environment for the agent of reinforcement learning. The reinforcement learning agent chooses an action according to the system state obtained by the pressure sensor, the incremental action can gradually approach the optimal strategy for the current fault, and then the agent updates the network by different rewards obtained in the interaction process. In this way, we can transform the active fault tolerant control process of the OTSG to the reinforcement learning agent's decision-making process. The comparison experiments compared with the traditional reinforcement learning algorithm(RL) with fixed strategies show that the active fault-tolerant controller designed in this paper can accurately and rapidly control under sensor faults so that the pressure of the OTSG can be stabilized near the set-point value, and the OTSG can run normally and stably.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.525-530
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• 2013

The importance of engineering design increases due to the expansion of engineering education certification. But there are not much teaching methods and examples of engineering design to be referred to the college classes. This paper introduces a new teaching and learning method of Action Learning adopted to a engineering design class in the Department of Architectural Engineering, J University in Korea. The class included a team project to find problems of facilities or safety management factors in a building construction site, and to provide the alternatives to solve the problems. The Action Learning helped to improve the learning effect of students and to increase the quality of the project deliverables.

• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2007년도 춘계학술대회
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• pp.377-384
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• 2007

This paper is about how to establish the strategic teaming organization in digital age. Through the case study of action teaming, this research can give some implications to small-sized organizations who want to establish teaming culture and positive activities in their own companies. The case site was S-steel, which belongs to the steel industry. To improve and drive teaming activities, I made use of skills: action learning, fishbone analysis, creative thinking, brainstorming, creative discussion skill, and organization diagnostic method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권3호
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• pp.220-224
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• 2008

This paper presents the polygon-based Q-leaning and Parallel SVM algorithm for object search with multiple robots. We organized an experimental environment with one hundred mobile robots, two hundred obstacles, and ten objects. Then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning, and dodecagon-based Q-learning and parallel SVM algorithm to enhance the fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process. In this paper, the result show that dodecagon-based Q-learning and parallel SVM algorithm is better than the other algorithm to tracking for object.

• Journal of Radiation Protection and Research
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• 제38권1호
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• pp.10-21
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• 2013

액션러닝이란 어떠한 문제를 해결하기 위해서 팀 내 구성원이 토의 과정과 이 과정을 도와주는 퍼실리테이터와의 교감을 통해 문제를 해결하고 학습하는 교수기법이다. 액션러닝을 통해서 학습자들은 인간관계기술을 개발할 수 있으며, 이는 곧 현대사회가 추구하는 사회적 자본의 가치와 연결이 된다. 본 연구는 외국인 대상 원자력 교육에서 이러한 액션러닝과 사회적 자본의 연관성을 파악하기 위해 한국원자력연구원에서 실시한 교육과정 참가자 17명을 대상으로 Wilcoxon 부호순위 검정을 통해 그 관계를 파악하였다. 그 결과 액션러닝은 구성원의 사회적 자본 증가에 긍정적인 영향을 미친다는 결론을 얻을 수 있었다. 따라서 이러한 결과를 바탕으로 원자력 교육에서 해당 조직과 기관의 목표를 이루기 위해 액션러닝의 실시는 강력한 교수기법 중 하나임을 알 수 있었으며, 이를 더욱 발전시켜 나아가야 됨을 이해할 수 있었다.