• The Journal of Korean Academic Society of Nursing Education
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• v.3 no.2
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• pp.207-213
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• 1997

Basic science teaching and clinical education should be integrated whenever appropriate, and the development of skills, values, and attitudes which are emphasized to the same extent as the acquisition of knowledge in nursing. Problem-based learning provides a students-centered learning environment and encourages an inquisitive style of learning. The purpose of this paper is to review and comment the role of tutors and students on problem-based learning. The use of problem-based learning places a high demand on faculty members' time and support. The role of tutors in Problem-based learning focuses primarily on issues of developing and teaching the curriculum and on organizational implementation and institutionalization. Tutors are an integral part of course planning. Tutors serve as a constant source of feedback on student needs and concerns to the course director and constitute an informal steering committee while the course is in progress. Tutors write cases, develop student evaluation methods, recommend resources, suggest modifications in lectures and laboratories. Students have a limited amount of time available to study what is traditionally defined as the core content of nursing. But, the role of students in Problem-based learning would be active, independent learners and problem-solvers rather than passive recipients of information. Students using a deep level approach attempt to integrate what they learn with what they already know, to understand the meaning underlying the material to be learned, and to look for explanations rather than facts. Students are encouraged, with appropriate guidance, to define their own learning goals, to select appropriate experiences to achieve these goals, and to be responsible for assessing their own learning progress. Problem-based learning is more flexible and meaningful, by encouraging student interaction, and by having a better emotional climate than the conventional learning.

• Smart Media Journal
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• v.12 no.1
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• pp.24-31
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• 2023

Meta-learning is metacognition that instantly distinguishes between knowing and unknown. It is a learning method that adapts and solves new problems by self-learning with a small amount of data.A few-shot learning method is a type of meta-learning method that accurately predicts query data even with a very small support set. In this study, we propose a method to solve the limitations of the prototype created with the mean-point vector of each class. For this purpose, we use the few-shot learning method that created the prototype used in the few-shot learning method as the median prototype. For quantitative evaluation, a handwriting recognition dataset and mini-Imagenet dataset were used and compared with the existing method. Through the experimental results, it was confirmed that the performance was improved compared to the existing method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.142-145
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• 2003

Many control applications using Neural Network need a priori information about the objective system. But it is impossible to get exact information about the objective system in real world. To solve this problem, several control methods were proposed. Reinforcement learning control using neural network is one of them. Basically reinforcement learning control doesn't need a priori information of objective system. This method uses reinforcement signal from interaction of objective system and environment and observable states of objective system as input data. But many methods take too much time to apply to real-world. So we focus on faster learning to apply reinforcement learning control to real-world. Two data types are used for reinforcement learning. One is reinforcement signal data. It has only two fixed scalar values that are assigned for each success and fail state. The other is observable state data. There are infinitive states in real-world system. So the number of observable state data is also infinitive. This requires too much learning time for applying to real-world. So we try to reduce the number of observable states by classification of states with Self-Organizing Map. We also use neural dynamic programming for controller design. An inverted pendulum on the cart system is simulated. Failure signal is used for reinforcement signal. The failure signal occurs when the pendulum angle or cart position deviate from the defined control range. The control objective is to maintain the balanced pole and centered cart. And four states that is, position and velocity of cart, angle and angular velocity of pole are used for state signal. Learning controller is composed of serial connection of Self-Organizing Map and two Multi-layer Feed-Forward Neural Networks.

• Knowledge Management Research
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• v.24 no.2
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• pp.1-25
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• 2023

While organizational learning (OL) is vital for ventures to build knowledge bases necessary for successful innovation, less attention has been paid to how learning organizations leverage it for performance improvement. We investigate entrepreneurial orientation's (EO) role in performance-by-learning mechanisms underpinning ventures' innovative initiatives, adopting dyadic performance indicators: technological competitiveness and business performance. Analyzing 218 Korean ventures, our study shows that firms valuing OL, characterized by acquisitive and experimental learning, exhibit high EO, facilitating productive use of knowledge-based resources and enhancing performance. Importantly, EO fully mediates the performance implications of OL. Our findings suggest that a comprehensive learning approach for knowledge acquisition and experimentation provides ventures, often facing smallness and newness liabilities, with a fertile entrepreneurial ground for increased innovation returns.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.625-641
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• 2015

Recent research shows that emotion is closely related to memory and learning. Although a growing number of educators have high interest in affective aspects of learning processes and outcomes, there are few studies to investigate systematically instructional strategies and learning environments based on learners' emotion. Despite the efforts to understand the role of emotion and to facilitate positive emotion for meaningful learning in face-to-face and online environments, it is still a challenging issue to measure emotion in a valid and reliable way. To implement emotion-based education, it is essential to overcome the limitation of self-report surveys on emotion, which rely on the memory of learners. The current study surveyed emotion measurement tools, which are recently developed in education and other domains, in terms of self-report, neurophysiology, and behavioral responses. This study also discussed how emotion measurement tools can be used in authentic learning and teaching situations. Particularly, this study focused on cutting-edge technologies that would enable educators to collect and analyze learners' emotion easily in real-world contexts. This study will contribute to the research about the role of emotion in education and the design of adaptive learning environments that consider the change of learners' emotion.

• ETRI Journal
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• v.45 no.2
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• pp.318-328
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• 2023

Recently, embedded systems, such as mobile platforms, have multiple processing units that can operate in parallel, such as centralized processing units (CPUs) and neural processing units (NPUs). We can use deep-learning compilers to generate machine code optimized for these embedded systems from a deep neural network (DNN). However, the deep-learning compilers proposed so far generate codes that sequentially execute DNN operators on a single processing unit or parallel codes for graphic processing units (GPUs). In this study, we propose PartitionTuner, an operator scheduler for deep-learning compilers that supports multiple heterogeneous PUs including CPUs and NPUs. PartitionTuner can generate an operator-scheduling plan that uses all available PUs simultaneously to minimize overall DNN inference time. Operator scheduling is based on the analysis of DNN architecture and the performance profiles of individual and group operators measured on heterogeneous processing units. By the experiments for seven DNNs, PartitionTuner generates scheduling plans that perform 5.03% better than a static type-based operator-scheduling technique for SqueezeNet. In addition, PartitionTuner outperforms recent profiling-based operator-scheduling techniques for ResNet50, ResNet18, and SqueezeNet by 7.18%, 5.36%, and 2.73%, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1743-1758
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• 2023

Automatic modulation classification is a critical algorithm for non-cooperative communication systems. This paper addresses the challenging problem of closed-set and open-set signal modulation classification in complex channels. We propose a novel approach that incorporates a self-learning filter and center-loss in Deep Residual Shrinking Networks (DRSN) for closed-set modulation classification, and the Opendistance method for open-set modulation classification. Our approach achieves better performance than existing methods in both closed-set and open-set recognition. In closed-set recognition, the self-learning filter and center-loss combination improves recognition performance, with a maximum accuracy of over 92.18%. In open-set recognition, the use of a self-learning filter and center-loss provide an effective feature vector for open-set recognition, and the Opendistance method outperforms SoftMax and OpenMax in F1 scores and mean average accuracy under high openness. Overall, our proposed approach demonstrates promising results for automatic modulation classification, providing better performance in non-cooperative communication systems.

• Studies on Life and Culture
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• v.48
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• pp.335-374
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• 2018

This study explores the influence of parents socio-economic status on their adolescent children s internet use and learning conduct based on Korean Time Use Survey of 2014, under the assumption that parents socio-economic status can function as a mechanism for reproducing inter-generational inequality due to the difference of their children s internet use and learning conduct. Upon reviewing the weekdays average hours of using internet per day for the students from the age 13, the first year of a middle school to the age 18, the third year of a high school, they spend 15 minutes for information search, and 54 minutes for computer or mobile games. They tend to spend 211 minutes for study in the school, 56 minutes for after school study, and 88 minutes for self-study. According to Tobit regression analysis, the higher the students parents socio-economic status, the bigger the total hour for self-study and after school study. On the other hand, the lower the parents socio-economic status, the bigger the total hour for their adolescents internet or mobile game. The research shows that the lower the parents socio-economic status, the bigger the risk of their adolescent children s exposure to the addiction of the internet and mobile game. This implies that the parents socio-economic status can function to reproduce the inter-generational inequality. Based on the analysis result, this study discusses the practical and policy level implications in social welfare for improving the inequality reproducing mechanism.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.3
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• pp.105-119
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• 2005

With the introduction of Internet-based education such as online learning and virtual campuses. there are increased interests and demands for electronically delivering educational contents in comparison to the traditional educational methods. Our preilminary study showed that approximately $50\%$ of virtual groups formed online for the scope of collaborative learning encountered harriers that prevented them from forming an effective learning team and making satisfactory progress toward reaching the learning objectives. In this study, we asked the undergraduate students. who were the members of the online learning team, to work on the given discussion topics through the use of emails and threaded discussion boards. Then. we investigated the roles played by two electronic communication medium during the virtual discussion with respect to the learning outcome. We also studied how information was shared amongst the virtual learning team members. The results of our study showed that the email based online learning had the advantage of individualized and friendly information transfer. However. it also caused certain difficulty in exchanging ideas due to the one-sided nature of the email-based communication. On the other hand, the threaded discussion board provided easier information sharing and broadcasting. which enabled active participation by the virtual team members. However. It also had the disadvantage of difficulty in accurate information conveyance and duplication of the posted information. In summary, our study results showed that there was a high correlation between the characteristics of the electronic communication medium and the decision that the online learners made regarding which medium to use. There was a high correlation between the type of the electronic communication medium and the online learners' experiences in using these media.

• The Mathematical Education
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• v.58 no.4
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• pp.589-607
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• 2019

The study aimed to investigate what high-school students recognize mathematics textbooks and how they use textbooks in their learning mathematics in and out-of mathematics classrooms. For this purpose, we developed a set of interview questions in order to unpack what high-school students thought about mathematics textbooks and how they intended to use the textbooks for their learning mathematics. Eleven high-school students participated in the interview; the interview lasted for about an hour for each student. The data from the interviews were analyzed. The findings from the data analysis suggested as follows: a) the students seemed to consider mathematics textbooks as crucial medium for a mathematics classroom material and thus, they were likely to obliged to use the textbooks for preparing for not only tests and examination conducted regularly in schools but college entrance examination conducted nationwide; b) however, the students appeared to use the textbooks in limited ways in which they looked into the textbooks to prepare for mid-term or final exam only, not for their understanding mathematical contents as a main resource; and c) the students seemed to realize that they rarely have had an opportunity to develop mathematical thinking capabilities and understand mathematical ideas conceptually through the mathematics textbooks.