• The Journal of Korean Physical Therapy
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• v.20 no.3
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• pp.1-7
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• 2008

Purpose: Implicit motor learning is the capacity to acquire skill through physical practice without conscious awareness of what elements of performance improved. This study investigated whether subacute stroke patients can implicitly learn a perceptual-motor task. Methods: We recruited 12 patients with subacute stroke and 12 age-matched controls. All participants performed a perceptual-motor task that involved pressing a button corresponding with colored circles (blue, green, yellow, red) on a computer screen. The task consists of 7 blocks composed of 10 repetitions for a repeating 12-element sequence (total 120 responses). Results: Both groups demonstrated significant improvement in acquisition performance. Reaction times deceased in both groups at similar rate within the sequential block trials (2-5 blocks), and reaction times increased at a similar rate when the task paradigm was transferred from the sequential block trial to the random block trial (5-6-7 blocks). Conclusion: The results of this study suggest that patients with sub-actue stroke can implicitly learn a perceptual motor skill. Although explicit instructions should be used to focus the learner's attention rather than provide information about the task, the application of implicit motor learning strategies in the rehabilitation setting may be beneficial.

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.709-714
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• 2003

It is important that the interaction between learners and contents in Educational Contents. But, there is just simple interaction in traditional WBI or CAI. As it is necessary to study for interaction with learners. There is applied more multimedia elements for the fun of learners. But, it is also necessary to study for Network Educational Game Contents which can give virtual environment to learn easily and funny. In this study, Competition Learning Model is designed for network learning environment. We can look at the new view point of Educational Contents by implementation of Network Educational Game Contents and Competition Learning Model.

• Journal of The Korean Association For Science Education
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• v.24 no.1
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• pp.76-89
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• 2004

Recent studies of science and technology "in-the-making" revealed that the process of designing material artifacts is not a straightforward application of prior images or theories by one (or more) person(s) isolated from his or her (their) environment. Rather, designing is a process contingent on the social and material setting for both engineering designers and students. Over the past decade, designing technological artifacts has emerged as an important learning environment in science classrooms. Through the analyses of a large database concerning an innovative simple machines curriculum for sixth-and seventh-grade students, we accumulated valid evidence for the nature of the designing process and science learning through it. In this paper, we show that design actions intertwine with the transformation of the objectified raw materials and artifact, the designer collective, and the mediating tools enabling that transformation, which constitute the elements of an activity from the perspective of cultural-historical activity theory. We conceptualize the continuous change of relation between material artifacts, designers, and tools throughout the design activity as co-evolution. Two episodes were selected to exemplify synchronic and diachronic change of relations inherent in co-evolving activity system. Finally, we discuss the implications of co-evolution during design activity for science learning.

• Journal of the Korean Chemical Society
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• v.36 no.1
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• pp.113-124
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• 1992

The pattern recognition methods of chemometrics have been applied to multivariate data, for which ninety four Korean ancient glass pieces have been determined for 12 elements by neutron activation analysis. For the purpose, principal component analysis and non-linear mapping have been used as the unsupervised learning methods. As the result, the glass samples have been classified into 6 classes. The SIMCA (statistical isolinear multiple component analysis), adopted as a supervised learning method, has been applied to the 6 training set and the test set. The results of the 6 training set were in accord with the results by principal component analysis and non-linear mapping. For test set, 17 of 33 samples were each allocated to one of the 6 training set.

• Journal of Korean Elementary Science Education
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• v.33 no.3
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• pp.597-606
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• 2014

The purpose of this study is to survey and analyze difficulties in teaching and learning elementary school science on the chapter titled 'electric circuit'. 28 elementary school teachers who teach 5th grade science and 73 5th grade students in elementary school were taken part in this survey. The pilot questionnaire was distributed to find out both the degree and the reason of difficulties in teaching and learning. The answers are analyzed with four areas to extract elements which make class difficult; Learner factors (L), Instruction factors (I), Curriculum & textbooks factors (C), and Environment factors (E). The results are as follows. (1) It can be seen that both students and teachers feel the highest difficulty in 7th lesson 'the direction of current', while they felt little difficulty in lesson 3 'conductor and nonconductor' and lesson 8 'the safety of electricity'. (2) The most mentioned reason of difficulties in teaching and learning was Learner factors (L). (3) Teachers felt many difficulties in experimental environment. On the other hands, students didn't think experimental failures as serious trouble. (4) Students felt many difficulties in new terms and hazy concepts or expressions. (5) Teachers felt a lot of difficulties in those from Curriculum & textbooks factors.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.191-198
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• 2016

This paper aims to present how to design and implement a multimedia tutorial system for the self-learning French language using Director with additional tools. To implement a multimedia tutorial system we need to design several steps. First, we should choose the level of the users and design tutorial. Second, we should prepare all materials such as sounds, graphics, text and video. Finally, we should implement the selected elements and control the educational software. Due to the nature of the paper, it must emphasize French basic conversation to make environment that be used in each scene and the scene of the context dialog. In view of the fact that the fitness of each content utilization field of multimedia authoring tool is high, it is possible as part of the system sizing process of the manufacturing process, to impart its meaning. This learning-contents are composed of 10 units each situation, and we anticipate there are the several effects of this system on basic French students. This system helps lecturer get French students interested in lessons, and enables learner to learn French of the role of iterative practice by linking image and sound. Also this system helps learners to prepare and review French studying after a lesson and allows leaners to maximize their efficiency. The future of this work is to implement this system on the app.

• Journal of Fisheries and Marine Sciences Education
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• v.11 no.1
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• pp.43-58
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• 1999

To instruct in accordance with learner's trait & preceding knowledge, letting the learner control the learning activities is the important task of educator & major goal of the Education Department this year. This article intends to provide useful Instructional Model for the teachers in fisheries marine high school, when they design the individualized teaching model using motivation. One of the major reason for the fisheries marine high school students' low learning achievement is due to the neglecting motivation elements in teaching - learning processes. Recently, with assistance of the information communication technology development, various teaching methods such as Individualized Multimedia Mediated Instruction, Internet Instruction, have come to the major method in activating motivation and computer-mediated instruction considering the learner's individual difference is the useful tools for the instructional efficiency. Because current navigation text book of fisheries marine high school have special characteristic considering the spacial context & time series from departing port to entering port, Teachers can maximize learner's learning accomplishment by using individualized multimedia & providing similar situation like a real navigation(simulating), representing this text characteristics. Thus this paper searches for the specifications of Keller's Motivation Model & Sweeter's Tutorial Model to solve instructional efficiency problems in fisheries marine high school & developed an efficient instructional design by integrating two models.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.1055-1062
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• 2021

As face-to-face education becomes difficult due to the spread of COVID-19, the use of e-learning content and virtual training is increasing. In the case of information security education, practice to learn response techniques is important, so simulation hacking and vulnerability analysis activities have been supported as virtual training for a long time. In order to increase the educational effect, contents should be designed similar to real situation, and learning activities to achieve the learning goals should be designed. In addition, excellent functions and scalability of the system supporting learning activities are required. The researcher developed an LMS evaluation index that supports non-face-to-face education by considering the key elements of non-face-to-face education and training. The developed evaluation index was applied to the information security education platform to verify its practical utility.

• Journal of KIBIM
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• v.9 no.4
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• pp.31-40
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• 2019

With Building Information Modeling(BIM) becoming the de facto standard for data sharing in the AEC industry, additional needs have increased to ensure the data integrity of BIM models themselves. Although the Industry Foundation Classes provide an open and neutral data format, its generalized schema leaves it open to data loss and misclassifications This research applied deep learning to automatically classify BIM elements and thus check the integrity of BIM-to-IFC mappings. Multi-view CNN(MVCC) and PointNet, which are two deep learning models customized to learn and classify in 3 dimensional non-euclidean spaces, were used. The analysis was restricted to classifying subtypes of architectural walls. MVCNN resulted in the highest performance, with ACC and F1 score of 0.95 and 0.94. MVCNN unitizes images from multiple perspectives of an element, and was thus able to learn the nuanced differences of wall subtypes. PointNet, on the other hand, lost many of the detailed features as it uses a sample of the point clouds and perceived only the 'skeleton' of the given walls.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1818-1832
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• 2022

Violence in the Internet era poses a new challenge to the current counter-riot work, and according to research and analysis, most of the violent incidents occurring are related to the dissemination of violence images. The use of the popular deep learning neural network to automatically analyze the massive amount of images on the Internet has become one of the important tools in the current counter-violence work. This paper focuses on the use of transfer learning techniques and the introduction of an attention mechanism to the residual network (ResNet) model for the classification and identification of violence images. Firstly, the feature elements of the violence images are identified and a targeted dataset is constructed; secondly, due to the small number of positive samples of violence images, pre-training and attention mechanisms are introduced to suggest improvements to the traditional residual network; finally, the improved model is trained and tested on the constructed dedicated dataset. The research results show that the improved network model can quickly and accurately identify violence images with an average accuracy rate of 92.20%, thus effectively reducing the cost of manual identification and providing decision support for combating rebel organization activities.