• 대한수학교육학회지:수학교육학연구
• /
• 제12권4호
• /
• pp.473-491
• /
• 2002

This article analyzes mathematics education from dialectical materialism acknowledging the objectivity of knowledge. The thesis that knowledge is objective advances to the recognition that knowledge will be internalized, and an idea of zone of proximal development(ZPD) is established as a practice program of internalization. The lower side of ZPD, i.e. the early stage of internalization takes imitation in a large portion. And in the process of internalization the mediational means play an important role. Hereupon the role of mathematics teacher, the object of imitation, stands out significantly. In this article, treating the contents of study as follows, I make manifest that teaching and learning in mathematics classroom are united dialectically: I hope to findout the method of teaching-learning to mathematical knowledge from the point of view that mathematical knowledge is objective; I look into how analysis into units, as the analytical method of Vygotsky, has been developed from the side of mathematical teaching-learning; I discuss the significance of mediational means to play a key role in attaining the internalization in connection with ZPD and re-illuminate imitation. Based on them, I propose how the role of mathematics teachers, and the principle of organization to mathematics textbook should be.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권8호
• /
• pp.2831-2845
• /
• 2022

Compared to the significant approach of project-based learning research, a data-driven design project-based learning has not reached a meaningful consensus regarding the most valid and reliable method for assessing design creativity. This article proposes an advanced information data-interactive learning system for creative design using a service design process that combines a design thinking. We propose a service framework to improve the convergence design process between students and advanced information data analysis, allowing students to participate actively in the data visualization and research using patent data. Solving a design problem by discovery and interpretation process, the Advanced information-interactive learning framework allows the students to verify the creative idea values or to ideate new factors and the associated various feasible solutions. The student can perform the patent data according to a business intelligence platform. Most of the new ideas for solving design projects are evaluated through complete patent data analysis and visualization in the beginning of the service design process. In this article, we propose to adapt advanced information data to educate the service design process, allowing the students to evaluate their own idea and define the problems iteratively until satisfaction. Quantitative evaluation results have shown that the advanced information data-driven learning system approach can improve the design project - based learning results in terms of design creativity. Our findings can contribute to data-driven project-based learning for advanced information data that play a crucial role in convergence design in related standards and other smart educational fields that are linked.

• ETRI Journal
• /
• 제38권6호
• /
• pp.1229-1239
• /
• 2016

For efficient interaction between humans and robots, robots should be able to understand the meaning and intention of human behaviors as well as recognize them. This paper proposes an interactive human intention reading method in which a robot develops its own knowledge about the human intention for an object. A robot needs to understand different human behavior structures for different objects. To this end, this paper proposes a hierarchical behavior knowledge network that consists of behavior nodes and directional edges between them. In addition, a human intention reading algorithm that incorporates reinforcement learning is proposed to interactively learn the hierarchical behavior knowledge networks based on context information and human feedback through human behaviors. The effectiveness of the proposed method is demonstrated through play-based experiments between a human and a virtual teddy bear robot with two virtual objects. Experiments with multiple participants are also conducted.

• 창의정보문화연구
• /
• 제7권2호
• /
• pp.79-90
• /
• 2021

본 연구의 목적은 초등학교 저학년 학생을 대상으로 하는 언플러그드 교육프로그램을 연구하는 것이다. 이를 위하여 다음과 같이 연구를 진행하였다. 첫 번째로 초등학교 저학년 학생의 발달 수준에 맞게 놀이 활동 중심으로 놀이학습 기반 언플러그드 교육 방법을 발굴하였다. 두 번째로 발굴된 주제에 따라 컴퓨팅 사고력을 기를 수 있는 언플러그드 교육프로그램을 설계하였다. 각 차시는 스토리텔링으로 진행이 되며, 스토리텔링의 내용은 통합교과 '겨울'과 관련된다. 또한, 각 차시는 컴퓨팅 사고력의 핵심요소를 기준으로 분석되었다. 그리고 설계한 언플러그드 교육프로그램에서 활용할 수 있는 교육 자료를 개발하였다. 마지막으로 초등학교 저학년 학생을 대상으로 교육프로그램을 적용하고, 사례연구를 통해 교육프로그램을 분석하였다. 분석 결과 학생들의 수준에 맞게 교육프로그램이 구성되었으며, 본 교육프로그램은 초등저학년 학생의 컴퓨팅 사고력 향상에 도움이 된다는 것을 확인하였다.

• 만화애니메이션 연구
• /
• 통권32호
• /
• pp.363-381
• /
• 2013

본 논문은 모바일 웹 상에서 오프라인의 학습 내용을 복습 할 때 학습 동영상에 필요한 재학습 영역을 프레임 단위로 중요 영역만 캡처한다. 캡처된 프레임은 영상 중에서 진행된 학습 시간과 이미지의 형태로 저장하고 또한 설명에 대한 메모 기능을 함께 저장한다. 캡처 영역은 학습자에 필요한 영역만 재학습하는 학습자 중심의 맞춤형 시스템을 적용할 수 있다. 캡처 프로그램의 구성은 학습 순서에 상관없이 선택한 순서에 따라 프레임 단위 캡처로 사용자 중심의 스토리텔링형 학습을 적용할 수 있다. 캡처 시스템 효과는 전체 학습에 비해 학습 시간을 절약하고 학습자 중심의 프레임 재구성으로 맞춤형 학습에 따른 학습 효용성 향상에 긍정적인 역할을 한다.

• 디지털산업정보학회논문지
• /
• 제14권4호
• /
• pp.177-187
• /
• 2018

The purpose of this study is to investigate the influence of learning flow, learning interest, and academic achievement by dividing the time when class was taught by Havruta. The Havruta teaching method is a traditional Jewish method of learning, with a one-on-one discussion with a partner that has a positive impact on each other. Havruta teaches learners through various perspectives and perspectives, helping them to improve their learning ability by attracting new ideas and solutions. In the computer lab, there is a big difference between the students according to the learner's abilities. Therefore, it is thought that the Havruta teaching method will help the learners who have lost interest in learning and improve the learning ability in the conventional way which does not consider personal abilities. do. In this paper, based on the friendship teaching model of the Havruta teaching style, the experimental group was taught through the Havruta practice and the play. Through the pre- and post-test, the students who taught the class with the help of the verbal method improved the learning flow, the learning interest and the academic achievement.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2021년도 학술발표회
• /
• pp.134-134
• /
• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• International Journal of Internet, Broadcasting and Communication
• /
• 제14권1호
• /
• pp.44-52
• /
• 2022

With recent scientific advances and growing interest in AI technologies, AI-based chatbots have been viewed as a practical learning aid for English language development. The purpose of this study is to examine preservice teachers' perceptions on the potential benefits of employing AI chatbots in English instruction and its pedagogical aspects. 28 preservice teachers majoring in English education were asked to use Kuki chatbots for a week with a guidance of a researcher and then report on their perceptions of AI chatbots in terms of perceived usefulness after use, applicability, and educational benefits and drawbacks. Emerging codes and themes were identified and evaluated using Thematic Analysis(TA) based on qualitative data from surveys and interviews. The findings show that six emerging themes were identified, encompassing perspectives on teacher, learner, communication, linguistic, affective, and assessment. The overall findings of this study revealed that AI-based chatbots can play a significant role as learning tools for stimulating interactive communication in a target language. Most preservice primary teachers acknowledge that AI chatbots can be useful as teaching and learning aids for both teachers and students. Furthermore, when applying various learner data to chatbot technology, such as learner assessment and diagnosis, a guided approach is necessary to perform a conversation appropriate for the learner's level and characteristics. Finally, as chatbots have a variety of benefits in terms of affective aspects, they may improve EFL learners' confidence in speaking English and learning motivation.

• 한국게임학회 논문지
• /
• 제9권6호
• /
• pp.117-125
• /
• 2009

본 논문은 포석 바둑을 위해, 패턴 지식을 근간으로 바둑 용어 지식을 수행할 수 있는 뉴로-퍼지 추론에 대한 실험 결과를 설명하였다. 즉, 포석 시 최선의 착점을 결정하기 위한 뉴로-퍼지 추론 시스템의 구현을 논하였다. 또한 추론 시스템의 성능을 시험하기 위하여 시차 학습(TD($\lambda$) learning) 시스템과의 대결을 벌였다. 대결 결과에 의하면 단순한 뉴로-퍼지 추론 시스템조차 시차 학습 모델과 충분히 대결할 만하며, 뉴로-퍼지 추론 시스템이 실제 바둑 게임에도 적용될 수 있는 잠재력을 보였다.

• 한국산업융합학회 논문집
• /
• 제27권4_2호
• /
• pp.1001-1007
• /
• 2024

Recent deep learning algorithms for object detection in real-time play a crucial role in various applications such as autonomous driving, traffic monitoring, health care, and water quality monitoring. The size of small objects, in particular, significantly impacts the accuracy of detection models. However, data containing small objects can lead to underfitting issues in models. Therefore, this study developed a deep learning model capable of quickly detecting small objects to provide more accurate predictions. The RE-SOD (Residual block based Small Object Detector) developed in this research enhances the detection performance for small objects by using RGB separation preprocessing and residual blocks. The model achieved an accuracy of 1.0 in image classification and an mAP50-95 score of 0.944 in object detection. The performance of this model was validated by comparing it with real-time detection models such as YOLOv5, YOLOv7, and YOLOv8.