• 통합자연과학논문집
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• 제4권2호
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• pp.158-165
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• 2011

Statistics by structural equation modeling techniques were used to assess a model of chemistry learning strategy based on performance goal orientation. In the optimal Model III of this research, Performance-approach goal was positively related to the use of learning strategy(p<.05) and achievement need(p<.05). Performance-avoidance goal was negatively related to learning strategy(p<.05) and was positively related to self-handicapping tendency(p<.15). Performance-approach goal affected learning strategy indirectly through achievement need(p<.05). Use of achievement need was positively related to learning strategy(p<.05) and self-handicapping tendency(p<.35). Self-handicapping tendency affected learning strategy negatively(p<.05). Implications of these findings for learning strategy in chemistry education are discussed.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2001년도 학술대회지
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• pp.479-482
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• 2001

건설산업은 타 산업과는 다른 특수성을 가지고 있다. 이런 특수한 건설산업에서 지식경영을 실천하기 위해서는 현장을 중심으로 한 시스템적인 접근과 기업문화적인 접근이 동시에 요구된다. 하지만 대부분의 건설기업들은 지식경영을 실천하기 위해 시스템적인 접근에만 몰두하고 있는 것이 현실이고 그러한 이유가 건설기업 지식경영 실패의 원인이 되고 있다. 이러한 구조적 모순을 해결하고자 본고에서는 CoP를 기반으로 하는 건설기업 학습조직에 대 해 연구하였다.

• Educational Technology International
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• 제14권2호
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• pp.167-187
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• 2013

Team project learning is a type of Project-Based Learning, which is an effective learning method for developing collaborative competency and interpersonal communication skills, as well as for developing cognitive competency such as critical thinking, creative thinking, and analytical skills. This research, conducted to analyze learning activities, focuses on students' creative thinking and activities in TPBL(Team Project-Based Learning). A qualitative approach including a reflective journal based on the 6 stages of TPBL, was adopted for this purpose. In this study, 69 reflective journals on the three stages (developing a theme, researching, theme-making) of 23 undergraduate students were categorized on the basis of three criteria: divergent thinking factors, convergent thinking factors and affective factors. The results show that the participants' journals demonstrated twenty-eight activities from nine cognitive factors and nine activities from three affective factors were derived from reflect journal. This finding indicates that more appropriate instructional strategies are needed for students to enhance their creative thinking skills and activities

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3790-3803
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• 2018

Content-based image retrieval is an approach used to query images based on their semantics. Semantic based retrieval has its application in all fields including medicine, space, computing etc. Semantically generated binary hash codes can improve content-based image retrieval. These semantic labels / binary hash codes can be generated from unlabeled data using convolutional autoencoders. Proposed approach uses semi-supervised deep hashing with semantic learning and binary code generation by minimizing the objective function. Convolutional autoencoders are basis to extract semantic features due to its property of image generation from low level semantic representations. These representations of images are more effective than simple feature extraction and can preserve better semantic information. Proposed activation and loss functions helped to minimize classification error and produce better hash codes. Most widely used datasets have been used for verification of this approach that outperforms the existing methods.

• 영어어문교육
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• 제11권1호
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• pp.57-76
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• 2005

This study provides a rationale for using project-based learning with Korean students of English in Korea; in addition, it describes the process of creating and implementing project-based learning in the classroom and gives examples of how this unique teaching and learning method has been used successfully to teach learners with different levels of English proficiency. The first two chapters of the study examine the nature of project-based learning by comparing it with related fields of study, such as language teaching syllabi and methods, cognitive psychology, constructivists' views and interaction theory. The latter part of the study deals with issues related to applying project-based learning in Korean English classes. It emphasizes the importance not only of motivating active group effort and participation, but also in creating a trusting, cooperative relationship between group members in order to have a successful accomplishment of a project. The study concludes with implications for future studies.

• 한국초등과학교육학회지:초등과학교육
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• 제33권1호
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• pp.140-161
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• 2014

The purpose of this study was to analyze 181 papers about brain-based learning appeared in domestic scientific journals from 1989 to May of 2012 and suggest application conditions in elementary science education. The results of this study summarizes as follows; First, learning activity suggested by brain-based learning study is mainly explained by working of brain function. Learning activity explained by brain-based learning study are divided into 'learning according to specialized brain function, learning according to brain function integration and learning beyond specialization and integration of hemispheres'. Second, it searched how increased knowledge of brain structure and function affects learning. Analysis from this point of view suggests that brain-based learning study affects learning in many ways especially emotion, creativity and learning motivation. Third, brain-based learning study suggests various possibilities of learning activity reflecting brain plasticity. Plasticity which is one of most important characteristics of brain supports the validity of learning activity as learning disorder treatment and explains the possibility of selective increment of brain function by leaning activity and the need of whole-brain approach to learning activity. Fourth, brain-based learning brought paradigm shifts in education field. It supports learning sophistication on the understanding of student's learning activity, guides learning method that reflects the characteristics of subject and demands reconstruction of curriculum. Fifth, there are many conditions to apply brain-based learning in elementary science education field, learning environment that fits brain-based learning, change of perspectives on teaching and learning of science educators and development of brain-based learning curriculum are needed.

• International Journal of Advanced Culture Technology
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• 제11권2호
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• pp.56-63
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• 2023

I proposed the architectural guideline for educational environment based on design thinking approach to integrate and enhance learners' activities and achievements. The physical environment of design education learning space should be applied by teaching methods and learning activities, especially for STEAM-based convergent education, the architectural space conditions should support the design process based on design thinking. The learning environment conditions influence design education with physical design factors and learners' communication, and the flexible environment based on design thinking, which is crucial for design education. The 3 steps of design thinking experiences also allow students to learn the context of ideas, skills and outcomes. Therefore, I argued that the learning surrounding based on design thinking needs flexible and mobile, connected, integrated, organized, and team-focused environments to support learners' understanding, participation, and collaboration, and to achieve the design process based on research findings. For spaces for convergent learning environments based on design thinking, common design principles should be reviewed, such as coexistence with technology, safety and security, transparency and spatial extension, multi-purpose space and outdoor learning.

• International Journal of Contents
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• 제14권1호
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• pp.1-6
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• 2018

Text, as one of the most influential inventions of humanity, has played an important role in human life since ancient times. The rich and precise information embodied in text is very useful in a wide range of vision-based applications such as the text data extracted from images that can provide information for automatic annotation, indexing, language translation, and the assistance systems for impaired persons. Therefore, natural-scene text detection with active research topics regarding computer vision and document analysis is very important. Previous methods have poor performances due to numerous false-positive and true-negative regions. In this paper, a fully-convolutional-network (FCN)-based method that uses supervised architecture is used to localize textual regions. The model was trained directly using images wherein pixel values were used as inputs and binary ground truth was used as label. The method was evaluated using ICDAR-2013 dataset and proved to be comparable to other feature-based methods. It could expedite research on text detection using deep-learning based approach in the future.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.254-257
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• 2009

In this paper, we propose a learning-based super-resolution algorithm. In the proposed algorithm, a multi-resolution wavelet approach is adopted to perform the synthesis of local high-frequency features. To obtain a high-resolution image, wavelet coefficients of two dominant LH- and HL-bands are estimated based on wavelet frames. In order to prepare more efficient training sets, the proposed algorithm utilizes the LH-band and transposed HL-band. The training sets are then used for the estimation of wavelet coefficients for both LH- and HL-bands. Using the estimated high frequency bands, a high resolution image is reconstructed via the wavelet transform. Experimental results demonstrate that the proposed scheme can synthesize high-quality images.

• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.107-118
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• 2024

With the seamless growth of the technology, network usage requirements are expanding day by day. The majority of electronic devices are capable of communication, which strongly requires a secure and reliable network. Network-based intrusion detection systems (NIDS) is a new method for preventing and alerting computers and networks from attacks. Machine Learning is an emerging field that provides a variety of ways to implement effective network intrusion detection systems (NIDS). Bagging and Boosting are two ensemble ML techniques, renowned for better performance in the learning and classification process. In this paper, the study provides a detailed literature review of the past work done and proposed a novel ensemble approach to develop a NIDS system based on the voting method using bagging and boosting ensemble techniques. The test results demonstrate that the ensemble of bagging and boosting through voting exhibits the highest classification accuracy of 99.98% and a minimum false positive rate (FPR) on both datasets. Although the model building time is average which can be a tradeoff by processor speed.