• Educational Technology International
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• 제14권1호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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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.

• 디지털산업정보학회논문지
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• 제7권2호
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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.

• 한국정보전자통신기술학회논문지
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• 제14권3호
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• pp.201-207
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• 2021

머신러닝의 한 종류인 딥러닝은 각 학습 과정을 진행할 때, 가중치를 변경하면서 학습을 수행한다. 딥러닝을 수행할때 대표적으로 사용되는 Tensor Flow나 Keras의 경우 학습이 종료된 결과를 그래프 형태로 제공한다. 이에 과다학습으로 인한 퇴화 현상 또는 가중치의 잘못된 설정으로 인해 학습 결과에 오류가 발생하는 경우, 해당 학습 결과를 폐기해야한다. 이에 기존 기술은 학습 결과를 롤백하는 기능을 제공하고 있지만, 롤백 기능은 최대 5회 이내의 결과로 제한된다. 또한, 딥러닝의 모든 과정을 기록하고 있는 것이 아니기 때문에 값을 추적하기 어렵다. 이를 해결하기 위해 MLOps의 개념을 적용한 기술이 존재하지만. 해당 기술에서는 이전 시점으로 롤백하는 기능을 제공하지 않는다. 본 논문에서는 기존 기술의 문제점을 해결하기 위해 학습 과정의 중간 값을 블록체인으로 관리하여 학습 중간 과정을 기록하고, 오류가 발생할 경우 롤백할 수 있는 시스템을 구성한다. 블록체인의 기능 수행을 위해서 딥러닝 과정 및 학습 결과 롤백은 Smart Contract를 작성하여 동작하도록 설계하였다. 성능평가는 기존의 딥러닝 방식의 롤백 기능을 평가하였을 때, 제안방식은 100%의 복구율을 가지는 것에 비교하여 기존 기법에서는 6회 이후에 복구율이 감소되어 50회일 때 10%까지 감소하는 것을 확인하였다. 또한, 이더리움 블록체인의 Smart Contract를 사용할 때, 블록 1회 생성 시 157만원의 금액이 지속적으로 소모되는 것을 확인하였다.

• Educational Technology International
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• 제25권1호
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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.

• 디지털산업정보학회논문지
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• 제8권2호
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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.

• 소성∙가공
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• 제30권4호
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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.

• 한국컴퓨터정보학회논문지
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• 제23권9호
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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.

• 공학교육연구
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• 제8권1호
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• pp.71-83
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• 2005

본 논문에서는 자바 언어를 학습하는데 있어 효율성을 증가시키기 위해 인터넷 기반 자율학습시스템이 제안되었다. 제안된 자율학습시스템은 JWP(Java Web Player)라고 불리며 Java Web Start 기술을 활용하여 웹상에서 실행이 가능한 자바 애플리케이션 프로그램이다. 또한 본 논문에서는 컴퓨터 언어를 학습하는데 있어 3가지 중요한 일련의 과정인 개념학습과정, 프로그래밍 실습과정, 그리고 학습 성취도 평가과정을 Java Web Start 기술을 이용하여 JWP에 통합하였다. 제안된 시스템은 학습과정을 교육공학적인 측면에서 멀티미디어 요소를 강화하였기 때문에 학습자가 흥미를 가지고 자발적으로 학습을 할 수 있도록 설계되었다. 더욱이 JWP 에는 효율적인 자바 언어 학습을 위해 학습내용에 대한 설명이 음성으로 출력되며, 이때 이와 관련된 이미지와 텍스트들이 동기화되어 동시에 화면에 표시된다. 더욱이 소스파일의 코딩, 에디팅, 실행 그리고 디버깅 등을 쉽게 할 수 있는 컴파일러가 삽입되어 있어 편리한 자바 언어 실습환경을 제공한다. 마지막으로 각 단원별 돌발퀴즈와 마무리 테스트를 통하여 학습자가 자신의 학습상황을 체크하여 반복학습을 할 수 있도록 유도하였다.

• 한국융합학회논문지
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• 제12권9호
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• pp.93-98
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• 2021

프로그래밍 언어 학습 경험이 학습 동기에 미치는 변화를 분석하였다. 프로그래밍 언어 학습은 전공생에게도 어려운 과정으로 평가되는 것이 일반적이다. 비전공자에게로 확대되고 있는 현 시점에서 프로그래밍 학습과 관련된 심리적 태도 변화를 측정하는 것은 학습자 분석에 필요하다. 동기 관련 구인요인인 성취목표, 학업적 흥미, 학업적 자기효능감, 인지적 관여, 학업적 자기조절을 측정하여 전반적인 학습자 태도 변화를 알아보았다. 측정 결과 학습 태도 관련 모든 요인에서 사후 검사 값이 감소한 것으로 나타났다. 이 결과는 학습과정의 난이도가 프로그래밍 학습 의욕을 감소시킨 것으로 해석된다. 학습자가 인지하는 난이도가 클 수록 학습의욕이 더 크게 감소하는 것으로 나타났다. 이런 연구결과를 바탕으로 학습자가 느끼는 학습 난이도의 정도를 낮출 수 있는 상황과 피드백을 줄 수 있는 체계적인 학습환경과 학습과정의 중요성을 시사점으로 제시하고자 한다.