• Dementia and Neurocognitive Disorders
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• v.17 no.3
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• pp.83-89
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• 2018

Machine learning is where a machine (i.e., computer) determines for itself how input data is processed and predicts outcomes when provided with new data. An artificial neural network is a machine learning algorithm based on the concept of a human neuron. The purpose of this review is to explain the fundamental concepts of artificial neural networks.

• The Journal of Korea Robotics Society
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• v.10 no.2
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• pp.79-89
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• 2015

The purpose of this study was to examine the concept of r-learning based on existing studies of r-learning. It also aimed to analyze r-learning environments in an effort to determine prerequisites for the successful entrenchment of r-learning in material(technology and infrastructure), human(young children and teacher) and institutional(law and policy) aspects. This study intended to suggest some of the right directions for the revitalization of r-learning. In conclusion, the position of r-learning and its interrelationship with related systems in the ecosystem of early childhood education should accurately be grasped to accelerate the integration of r-learning into kindergarten education to maximize the effects of the convergence of the two. Intensive efforts should be made from diverse angles to expedite the spread and enrichment of r-learning.

• Journal of the Korean association of regional geographers
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• v.14 no.6
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• pp.752-766
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• 2008

For all the region is the basic unit of geographical learning and the grounds of human activities, regional learning can't possible be carried out at the class. Because there are very few regional learning materials that are applicable to class and can be expanded to geographical basic concept. This paper aims to regulate the construction principles of regional learning and select the contents of regional learning. Firstly, the six basic concepts of geographical education be made a selection of the construction principles of regional learning: human-environment, location, region, interaction, change, scale. And then, I suggest the upper five subject that be based on the results of systematical geography. Those are the necessity and method of regional apprehension, the physical environment and the regional human-life, the resource and industrial activities. the regional life-space's formation and change, and the changing world and region. And I propose the subdivided the mid and the lower subject that be reflected the learner's need and the social demand, and could be experienced the results of geography and the everyday life. For the best regional learning, these subjects can be combined one or more in various scale.

• International Journal of Quality Innovation
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• v.6 no.1
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• pp.43-57
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• 2005

Action learning motivates students to solve open-ended problems by 'developing skills through doing'. This paper reviews the concept of action learning and discusses the adoption of action learning approach to teach operations management at universities. It presents the design and delivery of an action-learning course at City University of Hong Kong. The course incorporates classroom lectures, tutorials and an action-learning workshop. The experience gained proves that action learning facilitates student participation and teamwork and provides a venue of accelerating learning where enables students to handle dynamic problem situations more effectively. The paper concludes that adopting action-learning approach can help lecturers to enhance quality teaching in operations management courses, and provide an alternate means of effective paradigm other than traditional classroom teaching and/or computer-based training at universities.

• Knowledge Management Research
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• v.9 no.4
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• pp.17-33
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• 2008

This study proposes University 2.0 as a model case of open, flexible, and distributed learning environment for higher education based on theoretical foundations and perspectives. As web 2.0 technologies emerge into the field of education, ways of generating and disseminating information and knowledge have been drastically changed. Professors are no longer the only source of knowledge. Students using internet often become prosumers of knowledge who search and access information through the web as well as publish their own knowledge using the web. A concept and framework of University 2.0 is introduced for implementing the new interactive learning paradigm with an open, flexible and distributed learning environment for higher education. University 2.0 incorporates online and offline learning environments with various educational media. Furthermore, it employs various learning strategies and integrates formal and informal learning through learning communities. Both instructors and students in University 2.0 environment are expected to be active knowledge generators as well as creative designers of their own learning and teaching.

• Journal of the korean academy of Pediatric Dentistry
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• v.51 no.1
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• pp.1-10
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• 2024

Deep learning algorithms are becoming more prevalent in dental research because they are utilized in everyday activities. However, dental researchers and clinicians find it challenging to interpret deep learning studies. This review aimed to provide an overview of the general concept of deep learning and current deep learning research in dental radiographic image analysis. In addition, the process of implementing deep learning research is described. Deep-learning-based algorithmic models perform well in classification, object detection, and segmentation tasks, making it possible to automatically diagnose oral lesions and anatomical structures. The deep learning model can enhance the decision-making process for researchers and clinicians. This review may be useful to dental researchers who are currently evaluating and assessing deep learning studies in the field of dentistry.

• Journal of The Korean Association For Science Education
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• v.32 no.2
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• pp.402-414
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• 2012

This study investigated the effects of the instructions using analogies in learning the concept of saturated solution by the analogy presentation types and the verbal learning styles upon the mapping understanding, the mapping errors, and the perceptions of the instruction. Fifth graders (N=123) at an elementary school were selected and assigned to VA (n=63) and VPA (n=60) groups. As a pretest, a test on the verbal learning style was administered. The students in the VA group learned the target concept with a verbal analogy, while those in the VPA group learned it with a verbal/pictorial analogy. After the students learned it, a mapping understanding test was administered. The students in the VPA group also administered the test on the perceptions of the instruction and some of them were interviewed in depth. The results revealed that the scores of the students with strong verbal learning preference in the VPA group were significantly lower than those in the VA group in the mapping understanding test. However, the scores of the students with weak verbal learning preference were not significantly different between the two groups. Five types of mapping errors were identified: failure to map, mismapping, rash mapping, impossible mapping, and mapping of a surficial feature. According to students' verbal learning styles, there were some differences in the frequencies of mapping errors in the two groups. Many students in the VPA group, regardless of their verbal learning styles, had positive perceptions of the instruction in various cognitive and motivational aspects. However, some of them also pointed out a few difficulties of the instruction. Educational implications of these findings are discussed.

• Journal of Christian Education in Korea
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• v.61
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• pp.81-107
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• 2020

This study reviews Bandura's vicarious reinforcement in observational learning process and implies this concept into Christian education in terms of spiritual role modeling. The first part of this study answers three questions: "what is vicarious reinforcement?" "how does vicarious reinforcement take place in observational learning?" and "how does vicarious reinforcement affect observer's behavior change?" Bandura conceptualizes the learning process with observational learning and imitative or non-imitative performance. Based on this concept, Bandura define the roles of vicarious reinforcement in the four steps of observational learning process: attention, retention, motor reproduction, and motivational process. Also, the three effects of vicarious reinforcements are explained in the following categories: the observational learning effect, inhibitory or disinhibitory effects, and eliciting effect. Adapting the structure of observational learning theory in terms of the effect of vicarious reinforcement and the function of role models, the second part of this study examines the biblical concept of imitation of Christ and the modeling strategy of discipleship. Especially Paul's spiritual role model serves as positive vicarious reinforcement for the Christian believers to perform the desired behaviors. Also, Paul's condemnation serves as explicit negative vicarious reinforcement. Then, the last part of this study covers the implication of these findings from observational learning and empirical studies in terms of spiritual role modeling to Christian education.

• Journal of Educational Research in Mathematics
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• v.22 no.2
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• pp.229-259
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• 2012

The purpose of the present study is to develop instrument of mathematical belief of middle school and high school students and to analysis results of test using the instrument. Based on the results of literature review, mathematical belief is the cumulative effects of self-assessment and self-concept in mathematical learning and achievement experience. Four sub-components of mathematical belief is identified belief of school mathematics, belief of mathematical problem solving, mathematical self-concept, belief of mathematical teaching and learning. The instrument was developed to investigate mathematical belief by reflecting Korean middle school and high school students' psychological characters. To develop the appropriate items for the mathematical belief, after reviewing literature thoroughly, first version of the instrument was developed and exploratory factor analysis and confirmatory factor analysis were conducted. Then, to reduce the effect of the gender difference and achievement level difference, Correlation Analysis and 1-way ANOVA was performed. Also, using multiple group confirmatory factor analysis, this instrument was investigated to see whether this can be used for both middle school and high school. The final items for middle school students is consisted 7 items of belief of school mathematics, 9 items of belief of mathematical problem solving, 11 items of mathematical self-concept, 10 items of belief of mathematical teaching and learning. Instrument of mathematical belief for high school students is consisted 9 items of belief of school mathematics, 9 items of belief of mathematical problem solving, 11 items of mathematical self-concept, 11 items of belief of mathematical teaching and learning. This study examined the differences about mathematical belief's sub-factors shown by three groups of mathematics achievement level. Students of higher achievement level showed that the degree of most factors ware the highest excepting stereotype of belief of school mathematics. Also, Male students preferred more positive in mathematics belief than female students.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.117-134
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• 2004

This study suggests a data driven optimization approach, which simulates the models of human learning processes from cognitive sciences. It shows how the human learning processes can be simulated and applied to solving combinatorial optimization problems. The main advantage of using this method is in applying it into problems, which are very difficult to simulate. 'Undecidable' problems are considered as best possible application areas for this suggested approach. The concept of an 'undecidable' problem is redefined. The learning models in human learning and decision-making related to combinatorial optimization in cognitive and neural sciences are designed, simulated, and implemented to solve an optimization problem. We call this approach 'SLO : simulated learning for optimization.' Two different versions of SLO have been designed: SLO with position & link matrix, and SLO with decomposition algorithm. The methods are tested for traveling salespersons problems to show how these approaches derive new solution empirically. The tests show that simulated learning for optimization produces new solutions with better performance empirically. Its performance, compared to other hill-climbing type methods, is relatively good.