• Journal of the Architectural Institute of Korea Planning & Design
• /
• v.34 no.3
• /
• pp.61-72
• /
• 2018

This study pursued to obtain 3 consecutive purposes. First, a conceptual model for comparing 3 constructivist teaching and learning strategies( problem-based learning[$P_bBL$], case-based learning[CBL] and project-based learning[$P_jBL$]) was developed. Relationships of these constructivist strategies with the development of expertise for learners were discussed. Second, specific differences between $P_bBL$, CBL and $P_jBL$ as applied in architectural design courses were analyzed under each of the teaching and learning category. Some analytical indexes were developed by content analysis, which are applicable effectively to reveal the differences. Based on the previous findings, third, a set of strategic guidelines for use in class were made and suggested in order to develop and improve expertise in architectural design. These guidelines were largely targeted for university design courses as well as education or reeducation of practicing architects. Expecially, combined application of $P_bBL$, CBL and $P_jBL$ was hypothesized and suggested as class management guidelines. In sum, a variety of $P_bBL$ problems, CBL cases and $P_jBL$ projects should be developed for expecting audience based on design subjects and tasks. As working domains of practicing architects, exploring/analyzing, understanding/making applications, and criticizing/self-reflecting should be considered in the development process.

• Korean Journal of Human Ecology
• /
• v.14 no.1
• /
• pp.1-13
• /
• 2005

This study has a purpose of developing a scale to evaluate maternal beliefs on preschool children's education. The subjects were 307 mothers of preschool children in Gwang-ju. The methods for data analyses included a factor analysis for construct validity, Pearson correlations between beliefs and learning-related activities for construct validity, and Cronbach's a for reliability. 4 factors were found, through literature review, in parental beliefs: passive learning, active learning, instruction, and expectation for academic-related skills acquisition. Factor analysis revealed that the 4-factor solution is the best fit. Correlations between beliefs and learning-related activities were statistically significant. Cronbach's a ranged from .65 to .87 for 4 sub-scales. It was concluded that the maternal beliefs scale is acceptable for use.

• Annual Conference of KIPS
• /
• 2018.05a
• /
• pp.183-186
• /
• 2018

In this paper, we propose the database design for skill learning service through the internet from the viewpoint of service engineering. This paper we describe the outlines for a design theory for skill learning service, which can lead to the satisfaction of both learner and instructor. Compared to other services, motion control learning takes a considerable amount of time, and this leads to a difficulty for learners to rate the quality of the service as well as for the instructors to provide consistent quality and standard of teaching. To solve these problems, we use a relational database with MongoDB which is an unstructured database allowing to flexibly incorporate the demands of both learner and instructor into the database itself.

• International Journal of Computer Science & Network Security
• /
• v.21 no.6
• /
• pp.258-268
• /
• 2021

Online learning systems are becoming an effective educational medium for many universities. The accessibility of online learning system in universities means that every student, including the visually impaired, is able use all the site's services. This research focuses on investigating the accessibility of online learning systems for visually impaired users. The paper purpose is to understand the perception of visually impaired undergraduate students towards Blackboard's accessibility and to make recommendations for a new Blackboard design with accessible features that support their needs. Impact of a new Blackboard design with accessible features on visually impaired students, using Taif University students as a case study is evaluated in this paper, as it is similar to most learning systems used by Saudi universities. A study on Taif University's utilization of Blackboard was conducted using mixed method approaches (an automatic tool and a user study). In the first phase, Taif's use of Blackboard was evaluated by the web accessibility tool called AChecker. In the second phase, we conducted a user study to verify previously discovered accessibility challenges to fully assess them according to the accessibility and usability guidelines. In this study, the accessibility of Taif University's Blackboard was evaluated by thirteen visually impaired undergraduate students. The results of the study show that Blackboard has accessibility issues, which are confusing navigation, incompatibility with assistive technologies, untitled pages or parts, unclear identification for visual elements, and inaccessible PDF files. This paper also introduces a set of recommendations that aim to improve the accessibility of Blackboard and other educational websites developed for this population. It also highlights the serious need for universities to enhance web accessibility for online learning systems for students with disabilities.

• Journal of Digital Convergence
• /
• v.18 no.1
• /
• pp.369-377
• /
• 2020

The purpose of this study is to find out the effect of e-learning quality and learner's usage motivation on e-learning satisfaction in Korea and China. In addition, by comparing and analyzing the factors influencing the satisfaction of learners between the two countries, this study aims to suggest the effective use of e-learning. This study surveyed Korean university students at Y and K universities in Gyeongsangbuk-do and Chinese university students at A university in Henan, China. As a result, for Korean university students, it is showed that learning time, learning space, learning process, usefulness, e-learning information quality, and service quality affect e-learning satisfaction. For Chinese university students, learning time, learning process and e-learning system quality, information quality, and service quality were found to affect e-learning satisfaction. Among them, service quality was an important factor influencing e-learning satisfaction in both countries, but the average score of each factor was very low. In the future, we discussed ways to improve service quality.

• 한국정보교육학회:학술대회논문집
• /
• 2011.01a
• /
• pp.271-279
• /
• 2011

With advanced technologies of information and communication technologies, ubiquitous computing becomes popular. U-learning(Ubiquitous Learning) is a new paradigm that was started with ubiquitous computing environment. U-learning has characteristics such as anytime, anywhere, any network and any device, The U-learning support system(ULSS) is the system for supporting the u-Learning. Also, with recent fashion of smart phones, their use in education becomes interested. In this paper, The ULSS is defined in smart phone environments.

• Korean Medical Education Review
• /
• v.22 no.2
• /
• pp.57-66
• /
• 2020

The purpose of this study was to examine teaching strategies from cognitive learning theory applied to medical education and to present specific applications of the strategies and cases. The results of this study yielded (1) seven teaching strategies and specific sample activities that instructors can use based on learning processes in medical schools; (2) nine instructional events to which cognitive learning strategies were applied; (3) principles of curriculum design from a cognitive perspective; and (4) instruction cases employing cognitive teaching strategies. Cognitive learning theory has two implications: first, if instructors in medical schools apply the results of the study to design a class and curriculum, it would be possible for them to minimize cognitive loading of the learners that may stem from ineffective teaching strategies or curricula; second, cognitive teaching strategies that seek improvement in thinking skills could provide useful teaching strategies for medical education, which aims to develop experts with high-level thinking processes. In this sense, cognitive learning theory is not an out-of-date learning theory, but one that can be effectively applied in current medical education.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.11
• /
• pp.4246-4267
• /
• 2020

As the network goes deep into all aspects of people's lives, the number and the complexity of network traffic is increasing, and traffic classification becomes more and more important. How to classify them effectively is an important prerequisite for network management and planning, and ensuring network security. With the continuous development of deep learning, more and more traffic classification begins to use it as the main method, which achieves better results than traditional classification methods. In this paper, we provide a comprehensive review of network traffic classification based on deep learning. Firstly, we introduce the research background and progress of network traffic classification. Then, we summarize and compare traffic classification based on deep learning such as stack autoencoder, one-dimensional convolution neural network, two-dimensional convolution neural network, three-dimensional convolution neural network, long short-term memory network and Deep Belief Networks. In addition, we compare traffic classification based on deep learning with other methods such as based on port number, deep packets detection and machine learning. Finally, the future research directions of network traffic classification based on deep learning are prospected.

• Journal of Internet of Things and Convergence
• /
• v.7 no.4
• /
• pp.29-34
• /
• 2021

In order to apply reinforcement learning to a robot in a real environment, it is necessary to use simulation in a virtual environment because numerous iterative learning is required. In addition, it is difficult to apply a learning algorithm that requires a lot of computation for a robot with low-spec. hardware. In this study, ML-Agent, a reinforcement learning frame provided by Unity, was used as a virtual simulation environment to apply reinforcement learning to the obstacle collision avoidance problem of mobile robots with low-spec hardware. A DQN supported by ML-Agent is adopted as a reinforcement learning algorithm and the results for a real robot show that the number of collisions occurred less then 2 times per minute.

• Journal of Wind Energy
• /
• v.13 no.3
• /
• pp.33-42
• /
• 2022

In this paper, a semi-supervised machine learning technique applied to actual field vibration data acquired from Jeju-do wind turbines for predictive diagnosis of abnormal conditions of offshore wind turbines is introduced. Semi-supervised machine learning, which combines un-supervised learning with supervised learning, can be used to perform anomaly detection in situations where sufficient fault data cannot be obtained. The signal processing results using the spectrogram of the original signal were shown, and external data were used to overcome the problem that disturbance reactions easily occurred due to the imbalance between the number of normal and abnormal data. Out of distribution (OOD), which uses external data, is a technology that is regarded as abnormal data that is unlikely to occur in reality, but we were able to use it by expanding it. By rearranging the distribution of data in this way, classification can be performed more robustly. Specifically, by observing the trends of the abnormal score and the change in the feature of the representation layer, continuous learning was performed through a mixture of existing and new data.