• Journal of Internet Computing and Services
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• v.11 no.2
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• pp.165-172
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• 2010

In Web-based learning systems, the techniques, as self-regulated learning, self-directed learning, are used to improve the effect of learner's study. These techniques are methods considering learner's study level but to consider the learner's study ability properly, the tailored course for learner should be applied. In this research, the learning system considering learner's study ability was proposed. To decide a learner's study ability, IRT(Item Response Theory) was applied and learning contents and question items were developed and applied by the degree of difficulty.

• International journal of advanced smart convergence
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• v.8 no.2
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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.

• English Language & Literature Teaching
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• v.12 no.4
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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.

• Journal of Educational Research in Mathematics
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• v.11 no.2
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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.

• Journal of the Korean Chemical Society
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• v.66 no.6
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• pp.472-492
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• 2022

The purpose of this study was to investigate secondary science teachers' PCK components and subcomponents that are specific to online and offline learning environment. Data collection consisted of survey, class observation, and individual interviews of twelve science teachers. This study used a theoretical framework of PCK for deductive data analysis and articulated codes and themes through the following inductive analysis. Data analysis revealed that each of PCK components showed different specificity to the online and offline learning environment. And subcomponents of each PCK component were different according to the specificity of the online and offline learning environment. Teaching orientation toward science had a specific orientation for the online learning environment, i.e., 'learning science concept' and 'lecture centered instruction.' Knowledge of the science curriculum had online-offline mixed learning environment specific knowledge, i.e., 'reorganization of curriculum' and online learning environment specific knowledge, i.e., 'development of learning goal' and 'science curricular materials.' Knowledge of science teaching strategies had online learning environment specific knowledge, i.e., 'topic-specific strategy', 'subject-specific strategy', and 'interaction strategy' and COVID-19 offline learning environment specific knowledge, i.e., 'topic-specific strategy' and 'interaction strategy'. Knowledge of student science understanding had online learning environment specific knowledge, i.e., 'student preconception', 'student learning difficulty', 'student motivation and interest', and 'student diversity' and COVID-19 offline learning environment specific knowledge, i.e., student learning difficulty'. Knowledge of science assessment had online-offline mixed learning environment specific knowledge and online learning environment specific knowledge, i.e., assessment contents and assessment methods for each.

• Journal of information and communication convergence engineering
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• v.16 no.4
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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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• v.21 no.1
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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.

• Journal of Ocean Engineering and Technology
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• v.34 no.3
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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.

• Convergence Security Journal
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• v.5 no.1
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• pp.75-83
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• 2005

A purpose of the system proposed in this paper is to help learners pursue proactive and self-oriented education by allowing learners to proactively configure their own content, that is, learners no longer have to be restricted by prescribed sequence of lectures. In general, most LMSs cannot meet every individual's educational needs because they structure their programs by letting learners simply choose from a list of available lectures at prescribed level or difficulty. However the Self-Leading LMS eliminates such boundaries by allowing learners to choose contents and difficulty within the limit set by their own educational competence.

• Journal of Korean language education
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• v.29 no.4
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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.