• International journal of advanced smart convergence
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• 제8권2호
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• pp.170-182
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• 2019

In this paper, we use scratch to design and develop non-formal learning experiences that are linked with contents of secondary science textbook to educational programs. The goal of this paper is to develop a convenient and interesting program for non-formal learning in a learning environment using various smart device. Theoretical approaches to mobile education, such as smartphones, and smart education support policies continue to lead to various research efforts. Although most of the smart education systems developed for students who have difficulty in academic performance are utilized, they are limited to general students. To solve the problem, the learning environment was implanted by combining the scratch, which is an educational programming that can be easily written. The science education program proposed in this paper shows the result of process of programming using ICT device using scratch programming. In the evaluation stage, we were able to display the creations and evaluate each other, so that we could refine them more by sharing the completed ideas.

• 영어어문교육
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• 제12권4호
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• pp.31-68
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• 2006

The present research investigates the acquisition of the English locative alternation by Korean EFL learners, which poses a learnability paradox, taking Pinker's framework of learnability theory as its basis. It addresses two questions (1) how lexical knowledge is represented initially and at different levels of interlanguage development and (2) what kinds of difficulty Korean learners find in the acquisition of English locative verbs and their constructions. Three groups of learners at different proficiency levels with a control group of English native speakers are examined by two instruments: elicited production task and grammaticality judgment task. According to different levels of proficiency, the learners exhibit gradual sensitivity to a change-of-state meaning and obtain complete perception of the meanings of locative verbs (manner-of-motion and change-of-state) and their constructions. Overgeneralization errors are observed in their performance. The errors are due to misinterpretations of particular lexical items in conjunction with the universal linking rules. More fundamental cause of difficulty is accounted for by partial use of learning mechanisms, caused by insufficient L2 input.

• 대한수학교육학회지:수학교육학연구
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• 제11권2호
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• pp.341-349
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• 2001

Infinity is one of the important concept in mathematics, science, philosophy etc. In history of mathematics, potential infinity concept conflicts with actual infinity concept. Reason that mathematicians refuse actual infinity concept during long period is because that actual infinity concept causes difficulty in our perceptions. This phenomenon is called epistemological obstacle by Brousseau. Potential infinity concept causes difficulty like history of development of infinity concept in mathematics learning. Even though students team about actual infinity concept, they use potential infinity concept in problem solving process. Therefore, we must make clear epistemological obstacles of infinity concept and must overcome them in learning of infinity concept. For this, it is useful to experience visualization about infinity concept. Also, it is to develop meta-cognition ability that students analyze and control their problem solving process. Conclusively, students must adjust potential infinity concept, and understand actual infinity concept that is defined in formal mathematics system.

• 대한화학회지
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• 제66권6호
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• pp.472-492
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• 2022

본 연구는 온-오프라인 혼합 학습환경에서 중등과학교사의 학습환경 특이적인 PCK 요소 및 하위요소 탐색을 목적으로 하였다. 중등과학교사 12명을 대상으로 설문, 개별 면담, 수업 관찰 자료를 수집하여 PCK 이론적 틀을 기반으로 연역적으로 분석하고 다시 귀납적 분석을 통해 그 범주를 정교화하였다. 온-오프라인 혼합 학습환경에서 본 연구 교사들의 PCK는 요소별로 학습환경 특이성이 다르고 학습환경 특이성에 따라 PCK 요소별 하위요소가 다른 것으로 나타났다. 온라인 학습환경 특이적인 과학 교수 지향으로 '과학 개념 학습' 목표 지향과 '강의식 수업'의 과학 교수-학습 지향이 있었다. 온-오프라인 혼합 학습환경 특이적인 교육과정에 관한 지식에는 '교육과정 재구성'이 있었으며, 온라인 학습환경 특이적인 교육과정에 관한 지식에는 '학습 목표 선정', '교육과정 자료'가 있었다. 온라인 학습환경 특이적인 과학 교수전략에 관한 지식에는 '과학 주제 특이적 전략', '과학 교과 특이적 전략', '상호작용 전략'이 있었다. 코로나 19 이후 오프라인 학습환경 특이적인 과학 교수전략에 관한 지식에는 '과학 주제 특이적 전략', '상호작용 전략'이 있었다. 온라인 학습환경 특이적인 학생의 과학 학습에 관한 지식에는 '학습을 위한 선지식', '학습 어려움', '학습 동기 및 흥미', '학습 다양성'이 있었으며, 코로나 19 이후 오프라인 학습환경 특이적인 학생의 과학 학습에 관한 지식에는 '학습 어려움'만 있었다. 과학 학습 평가에 관한 지식은 온-오프라인 혼합 학습환경 특이적인 지식과 온라인 학습환경 특이적인 지식이 있었으며, 각각 '평가 내용'과 '평가 방법'이 있었다.

• Journal of information and communication convergence engineering
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• 제16권4호
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• pp.235-241
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• 2018

Recently, deep learning has been actively studied and applied in various fields even to novel writing and painting in ways we could not imagine before. A key feature is that high-performance computing device, especially CUDA-enabled GPU, supports this trend. Researchers who have difficulty accessing such systems fall behind in this fast-changing trend. In this study, we propose and implement a library called Emulearner that helps users to utilize Emulab with ease. Emulab is a research framework equipped with up to thousands of nodes developed by the University of Utah. To use Emulab nodes for deep learning requires a lot of human interactions, however. To solve this problem, Emulearner completely automates operations from authentication of Emulab log-in, node creation, configuration of deep learning to training. By installing Emulearner with a legitimate Emulab account, users can focus on their research on deep learning without hassle.

• Korean Journal of Radiology
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• 제21권1호
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• pp.33-41
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• 2020

Artificial intelligence has been applied to many industries, including medicine. Among the various techniques in artificial intelligence, deep learning has attained the highest popularity in medical imaging in recent years. Many articles on deep learning have been published in radiologic journals. However, radiologists may have difficulty in understanding and interpreting these studies because the study methods of deep learning differ from those of traditional radiology. This review article aims to explain the concepts and terms that are frequently used in deep learning radiology articles, facilitating general radiologists' understanding.

• 한국해양공학회지
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• 제34권3호
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• pp.167-179
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• 2020

Recently, the increasing importance of artificial intelligence (AI) technology has led to its increased use in various fields in the shipbuilding and marine industries. For example, typical scenarios for AI include production management, analyses of ships on a voyage, and motion prediction. Therefore, this study was conducted to predict a response amplitude operator (RAO) through AI technology. It used a neural network based on one of the types of AI methods. The data used in the neural network consisted of the properties of the vessel and RAO values, based on simulating the in-house code. The learning model consisted of an input layer, hidden layer, and output layer. The input layer comprised eight neurons, the hidden layer comprised the variables, and the output layer comprised 20 neurons. The RAO predicted with the neural network and an RAO created with the in-house code were compared. The accuracy was assessed and reviewed based on the root mean square error (RMSE), standard deviation (SD), random number change, correlation coefficient, and scatter plot. Finally, the optimal model was selected, and the conclusion was drawn. The ultimate goals of this study were to reduce the difficulty in the modeling work required to obtain the RAO, to reduce the difficulty in using commercial tools, and to enable an assessment of the stability of medium/small vessels in waves.

• 융합보안논문지
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• 제5권1호
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• pp.75-83
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• 2005

본 논문에서 제안하는 시스템은 다양한 학습자가 가상대학에서 고정된 난이도의 강좌를 일괄적으로 학습하고 평가하는 형식이 아닌 학습자 본인이 학습하고 싶은 과정을 선택하고 자신의 능력정도를 파악하여 원하는 수준의 학습 내용과 학습할 단원(챕터)들을 선택하여 수강하는 강좌에 대해서 자발적이고 자기 주도적인 학습을 할 수 있도록 하는 것이 목적이다. 일반적인 LMS들은 교육컨텐츠의 내용 및 특정 난이도의 컨텐츠들을 구성하여 학습자에게 하나의 과정을 선택하도록 하여 학습하도록 설계되어 있어 학습자가 다양한 가상대학에는 적절하게 대처할 수 있다. 그러나 자기 주도적인 LMS는 학습자가 선택 가능한 범위 안에서 교육과정과 난이도를 선택하여 이용할 수 있도록 만들어 졌기 때문에 다양한 학습자의 수준을 맞추어 줄 수 있다.

• 한국어교육
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• 제29권4호
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• pp.93-112
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• 2018

The purpose of this study is to deal with vocabulary in KFL. As a result of this study, learners learned vocabulary on average 43 points through contextual inference and introduction of the class to activate background knowledge. In particular, the implicit method showed the highest learning rate of 52 points, and the thematic method had a 41 point-learning rate. In contrast, the semantic method was the lowest with a 25 point-learning rate. There was no significant difference in the improvement rate of upper vocabulary learners, but in the case of the lower learner, there was significant difference in the improvement rate. The difference was not significant in the post-test relative gain rate of upper learners, but there was significant in lower learners. In the delayed test relative gain rate, the difference was significant in all groups. There was correlation between vocabulary difficulty and score, but there was no correlation with the thematic method. And there was no correlation between vocabulary difficulty, improvement rate and relative gain rate in all three classes. However, content understanding, lexical grade, improvement rate, and relative gain rate showed a significant correlation.

• 창의정보문화연구
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• 제7권2호
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• pp.69-77
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• 2021

과거 프로그래밍은 컴퓨팅 관련 전공자들을 대상으로 일부의 학생들이 배우는 과목이었으나, 오늘날 소프트웨어 중심 산업이 도래함에 따라 컴퓨팅사고 교육과 함께 컴퓨팅 문제 해결의 도구로서 모든 전공 분야의 학생들에게 교육이 이루어지고 있다. 그러나 컴퓨팅 입문 과목을 필수로 이수해야 하는 학습자들은 익숙하지 않은 컴퓨팅 문제 해결 방식과 프로그래밍 언어라는 새로운 내용에 학습에 큰 어려움을 겪으며 학습 효과, 자신감, 흥미 저하와 같은 부정적인 현상으로 이어질 수 있다. 본 논문에서는 비전공자들이 프로그래밍 언어 과목을 학습하면서 겪는 어려움의 원인을 설문 조사, 일지 및 성취도를 질적 및 양적 연구로 분석하여 파악하고, 이를 최소화할 수 있도록 방안을 제시하여 향후 어려움을 최소화하는 교육 방안의 설계에 도움이 되고자 한다.