• Educational Technology International
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• v.14 no.1
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• pp.41-53
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• 2013

On the basis of two premises and embodied cognition theory, the vibration tactile learning is proposed as an effective method for foreign language learning. The premises are: the real nature of language is sound and the source of sound is vibration. According to embodied cognition theory, cognition is inherently connected to bodily sensation rather than metaphysical and independent. As a result, the vibration tactile learning is: people are able to learn foreign language better by listening to sound and experiencing its vibration through touch rather than solely listening to sound. The effectiveness of vibration tactile learning is tested with two instructional media theories: media comparison and media attribute. For the comparison, an experiment is conducted with control and experimental groups. The attributes of vibration tactile media are investigated in points of relationships with the learning process. The experiment results indicate a small effect on the increased mean score. Three kinds of relationships are found between the media attribute and learning process: enforced stimulus, facilitated pronunciation, and assimilation of resonance to sound patterns through touch. Finally, this paper proposes a new theoretical development for instructional media research: an embodied cognition based media research and development.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2543-2545
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• 2003

This paper presents a web-based virtual classroom which can be creating efficiencies in the learning process of PHP language. The proposed flash animations which explain the important principles of several topics for PHP language are designed for the learners to easily understand by executing them through simple mouse clicks. The proposed flash animations enables the learners to achieve efficient and interesting self-learning since the learning process is designed to enhance the multimedia capabilities on the basis of various educational technologies. Also, internet-based on-line voice presentation and its related texts together with moving images are synchronized for efficient, language learning process. Through the proposed virtual classroom, the learners will be capable of learning the concepts related to PHP language and its coding. The results of this paper are to allow the implementation of an efficient virtual classroom, and are also expected to make a contributions to the activation of internet-based educational systems.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.2
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• pp.1-8
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure non-homogeneous Poisson process models presented and the life distribution applied extreme distribution which used to find the minimum (or the maximum) of a number of samples of various distributions. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.201-207
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• 2021

Deep learning, a type of machine learning, performs learning while changing the weights as it progresses through each learning process. Tensor Flow and Keras provide the results of the end of the learning in graph form. Thus, If an error occurs, the result must be discarded. Consequently, existing technologies provide a function to roll back learning results, but the rollback function is limited to results up to five times. Moreover, they applied the concept of MLOps to track the deep learning process, but no rollback capability is provided. In this paper, we construct a system that manages the intermediate value of the learning process by blockchain to record the intermediate learning process and can rollback in the event of an error. To perform the functions of blockchain, the deep learning process and the rollback of learning results are designed to work by writing Smart Contracts. Performance evaluation shows that, when evaluating the rollback function of the existing deep learning method, the proposed method has a 100% recovery rate, compared to the existing technique, which reduces the recovery rate after 6 times, down to 10% when 50 times. In addition, when using Smart Contract in Ethereum blockchain, it is confirmed that 1.57 million won is continuously consumed per block creation.

• Educational Technology International
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• v.25 no.1
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• pp.27-65
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• 2024

The purpose of this study was to identify differences in learning patterns according to content complexity in video-based learning environments and to derive variables that have an important effect on learning achievement within particular learning contexts. To achieve our aims, we observed and collected data on learners' cognitive processes through perceived affordances, using behavioral logs and eye movements as specific indicators. These two types of reaction data were collected from 67 male and female university students who watched two learning videos classified according to their task complexity through the video learning player. The results showed that when the content complexity level was low, learners tended to navigate using other learners' digital logs, but when it was high, students tended to control the learning process and directly generate their own logs. In addition, using derived prediction models according to the degree of content complexity level, we identified the important variables influencing learning achievement in the low content complexity group as those related to video playback and annotation. In comparison, in the high content complexity group, the important variables were related to active navigation of the learning video. This study tried not only to apply the novel variables in the field of educational technology, but also attempt to provide qualitative observations on the learning process based on a quantitative approach.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.1-10
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• 2012

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and the life distribution applied exponential and log shaped type hazard function. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model could be confirmed. This paper, a failure data analysis of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and coefficient of determination.

• Transactions of Materials Processing
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• v.30 no.4
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• pp.186-194
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• 2021

Finite element simulation is a widely applied method for practical purpose in various metal forming process. However, in the simulation of elasto-plastic behavior of porous material or in crystal plasticity coupled multi-scale simulation, it requires much calculation time, which is a limitation in its application in practical situations. A machine learning model that directly outputs the constitutive equation without iterative calculations would greatly reduce the calculation time of the simulation. In this study, we examined the possibility of artificial intelligence based constitutive equation with the input of existing state variables and current velocity filed. To introduce the methodology, we described the process of obtaining the training data, machine learning process and the coupling of machine learning model with commercial software DEFROM^TM, as a preliminary study, via rigid plastic finite element simulation.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.7-13
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• 2018

Recent advancement in data gathering technique improves the capability of information collecting, thus allowing the learning process between gathered data patterns and application sub-tasks. A pattern can be associated with multiple labels, demanding multi-label learning capability, resulting in significant attention to multi-label feature selection since it can improve multi-label learning accuracy. However, existing evolutionary multi-label feature selection methods suffer from ineffective search process. In this study, we propose a evolutionary search process for the task of multi-label feature selection problem. The proposed method creates large set of offspring or new feature subsets and then retains the most promising feature subset. Experimental results demonstrate that the proposed method can identify feature subsets giving good multi-label classification accuracy much faster than conventional methods.

• Journal of Engineering Education Research
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• v.8 no.1
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• pp.71-83
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• 2005

This paper presents an internet-based self-learning educational system which can be enhancing efficiency in the learning process of Java language. The proposed self-learning educational system is called Java Web Player(JWP), which is a Java application program and is executable through Java Web Start technologies. Also, three important sequential learning processes : concept learning process, programming practice process and assessment process are integrated in the proposed JWP using Java Web Start technologies. This JWP enables the learners to achieve efficient and interesting self-learning since the learning process is designed to enhance the multimedia capabilities on the basis of various educational technologies. Furthermore, internet-based on-line voice presentation and its related texts together with moving images are synchronized for efficient language learning process. Also, a simple and useful Java compiler is included in the JWP for providing language practice environment such as coding, editing, executing and debugging Java source files. Finally, repeated practice can make the learners to understand easily the key concepts of Java language. Simple multiple choices are given suddenly to the learners while they are studying through the JWP and the test results are displayed on the message box. This assessment process is very essential to increase the learner's academic capability.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.93-98
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• 2021

The change of programming language learning experience on learning motivation was analyzed. Learning a programming language is generally evaluated as a difficult process even for majors. Measuring psychological changes related to programming learning at this point in expanding to non-majors is necessary for learner analysis. The overall learner attitude change was investigated by measuring achievement goals, academic interest, academic self-efficacy, cognitive involvement, and academic self-regulation, which are motivation-related factors. All factors related to learning attitude showed a decrease in the post-test results. This result is interpreted that the difficulty of the learning process decreased the motivation to learn programming. It was found that the greater the difficulty perceived by the learner, the greater the decrease in the motivation to learn. Based on the results of this study, it has implications that a learning environment and learning process that can give feedback and a situation that can reduce the level of learning difficulty felt by learners should be systematically given.