• Journal of Information Technology Applications and Management
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• 제24권4호
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• pp.57-69
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• 2017

Due to the development of technology even in learning and education area, many studies have begun to make a new attempts to research by using SNS, breaking away from traditional learning methods. However, the limitations of these studies are restricted only to the use of wireless Internet and writing on Web sites. This study aims to conduct a research on English learning activities that utilize various technologies such as Bigdata, Facebook, Social Network Services (SNS) and English applications. In addition, this study looks into how these modern technologies can be integrated in the classrooms and which activities can be applied in the English classroom. This research is to suggest effective English learning methods through a thorough investigation on the effectivity of various technologies based on the Web 2.0 such as Flickr, blogs, MySpace, and online discussion board within the context of the English learning. To verify the effect of the study, the subjects are divided into experimental and control group. The experiment is proceeded with pre- and post-test. The experimental group is designed to verify the effects using SNS tools such as Facebook, Bigdata, and Online Massive Learning. A survey is conducted to determine the preference of utilizing social networking sites and to analyze the effects in class. The result is that the average scores for experimental group have improved more than the average of control group. The comparison of pre and post-test of the experimental group shows that the significance of the higher and median group was statistically significant at the p<0.01.

• 한국가정과교육학회지
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• 제10권1호
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• pp.137-151
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• 1998

The purpose of this study is (1)to develop the teaching plan based on Cooperative Learning approach and (2)to investigate the effect of students'Interest on Subject matter and Teaching method and Attitudes to others of the area of Foreign food in Home Economics class. Among those various types of Cooperative Learning's models, this study adopted 'Learning Together'developed by Johnsons. To investigate these purpose, subject matter were analyzed and reconstructed for Cooperative Learning. The tests were developed to evaluate the interest on the Subject matter and teaching methods, and the attitude to others of the students. 108 femail high school students were divided into two groups with 54 students-traditional learning condition, Cooperative Learning condition-and had a 5 session. The subject of the class was Foreign food including Western, Chinese, and Japanes food. Before and after the class, students were tested. The statistical methods used for the study methods used for the study were t-test. The research findings are as follows : When the students in the Cooperative Learning classes were compared before and after the test, (1)Interest on Subject matter were improved considerably(p〈.001) (2)Interest on Teaching methods were improved considerably(p〈.05) (3)Attitude to Others were improved considerably(p〈.001) Therefore when the teaching-learning model based on Cooperative Liarning was used in Home Economics class, their interest on the subject and teaching methods and attitude to others were improved.

• 한국초등과학교육학회지:초등과학교육
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• 제35권1호
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• pp.78-88
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• 2016

The purpose of this study was to examine the effects of science lesson with the application of Flipped Learning on science academic achievement and scientific attitude of students. The experimental group was composed of 50 students and the comparative group was composed of 50, both in $6^{th}$ grade. The two groups were statistically equivalent in their science academic achievement and scientific attitude when pre-tests were conducted. The experimental group received science instruction applied with Flipped Learning and the comparative group took typical science lesson according to a teacher's guide. The results of this study can be summarized as follows: First, the science lesson with the application of Flipped Learning was more significantly effective in improving students' science academic achievement than traditional science lesson. Second, the science lesson combined with Flipped Learning enhanced scientific attitudes of students with meaningful difference more than typical science lesson. Third, a survey research was conducted to the experimental group about their cognition on the lessons with the application of Flipped Learning. Many students had positive thoughts on this lesson and they thought the lesson was very interesting and understandable.

• 한국컴퓨터정보학회논문지
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• 제18권8호
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• pp.141-148
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• 2013

본 논문은 질적연구방법론을 적용하여 다양한 형태의 블렌디드 러닝 수업 모델을 설계 적용하여 2개 학기에 걸쳐 온라인 대학과 오프라인 대학을 대상으로 연구하였다. 블렌디드 러닝의 학습효과에 대한 실험 참가자들의 반응을 설문조사 하였으며, 인터뷰를 실시하여 블렌디드 러닝에 직접적으로 발생되는 원가와 학습 성과를 파악하였다. 실험을 통해 블렌디드 러닝은 온라인 대학에서는 교육의 질 제고 측면에서, 오프라인 대학에서는 직 간접적 원가 절감 효과가 두드러지게 나타남을 파악하였다. 그밖에 다양한 학습성과와 원가발생에 대하여 검증하고 시사점을 도출하였다.

• Investigative Magnetic Resonance Imaging
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• 제23권2호
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• pp.81-99
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• 2019

Recently, deep learning methods have shown great potential in various tasks that involve handling large amounts of digital data. In the field of MR imaging research, deep learning methods are also rapidly being applied in a wide range of areas to complement or replace traditional model-based methods. Deep learning methods have shown remarkable improvements in several MR image processing areas such as image reconstruction, image quality improvement, parameter mapping, image contrast conversion, and image segmentation. With the current rapid development of deep learning technologies, the importance of the role of deep learning in MR imaging research appears to be growing. In this article, we introduce the basic concepts of deep learning and review recent studies on various MR image processing applications.

• International Journal of Computer Science & Network Security
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• 제21권2호
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• pp.21-39
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• 2021

The acceptance of smartphone applications in the learning field is one of the most significant challenges for higher education institutions in Saudi Arabia. These institutions serve large and varied sectors of society and have a tremendous impact on the knowledge gained by student segments at various ages. M-learning is of great importance because it provides access to learning through a wide range of mobile networks and allows students to learn at any time and in any place. There is a lack of quality requirements for M-learning applications in Saudi societies partly because of mandates for high levels of privacy and gender segregation in education (Garg, 2013; Sarrab et al., 2014). According to the Saudi Arabian education ministry policy, gender segregation in education reflects the country's religious and traditional values (Ministry of Education, 2013, No. 155). The opportunity of many applications would help the Saudi target audience more easily accept M-learning applications and expand their knowledge while maintaining government policy related to religious values and gender segregation in the educational environment. In addition, students can share information through the online framework without breaking religious restrictions. This study uses a quantitative perspective to focus on defining the technical aspects and learning requirements for distributing knowledge among students within the digital environment. Additionally, the framework of the unified theory of acceptance and use of technology (UTAUT) is used to modify new constructs, called application quality requirements, that consist of quality requirements for systems, information, and interfaces.

• 로봇학회논문지
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• 제17권1호
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• pp.1-7
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• 2022

Robots are widely used in industries and services. Traditional robots have been used to perform repetitive tasks in a fixed environment, and it is very difficult to solve a problem in which the physical interaction of the surrounding environment or other objects is complicated with the existing control method. Reinforcement learning has been actively studied as a method of machine learning to solve such problems, and provides answers to problems that robots have not solved in the conventional way. Studies on the learning of all physical robots are commonly affected by noise. Complex noises, such as control errors of robots, limitations in performance of measurement equipment, and complexity of physical interactions with surrounding environments and objects, can act as factors that degrade learning. A learning method that works well in a virtual environment may not very effective in a real robot. Therefore, this paper proposes a weighted sum method and a linear regression method as an effective and accurate learning method in a noisy environment. In addition, the bottle flipping was trained on a robot and compared with the existing learning method, the validity of the proposed method was verified.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.99-106
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• 2011

Recent demands from construction industry have emphasized the capability for graduates to have improved skills both technical and non-technical such as problem solving, interpersonal communication. To satisfy these demands, problem-based learning that is an instructional method characterized by the use of real world problem has been adopted and has proven its effectiveness various disciplines. However, in spite of the importance of field senses and dealing with real problem, construction engineering education has generally focused on traditional lecture-oriented course. In order to improve limitations of current construction education and to satisfy recent demands from construction industry, this paper proposes a new educational approach that is Failure-Based Learning for using combination of the procedural characteristics of the problem-based learning theory in construction technology education utilizing failure information that has the educational value in the construction area by reinterpreting characteristics of construction industry and construction failure information. The major results of this study are summarized as follows. 1) Educational effect of problem-based learning methodology and limitation of application in construction area 2) The educational value of the information on construction failure and limitation in application of the information in construction sector 3) Anticipated effect from application of the failure-based learning 4) Development and application of the failure-based learning model

• 과학교육연구지
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• 제38권2호
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• pp.302-316
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• 2014

본 연구는 6학년 1학기 산과 염기 단원 중 5차시를 Small-Scale Chemistry를 적용한 실험 수업 프로그램으로 개발하였다. 개발한 프로그램 적용을 경남 창원시에 소재한 Y초등학교 6학년 3개반은 SSC를 활용한 과학수업(n=86)을, 3개 반은 전통적인 실험 수업(n=87)을 진행한 후 학생들의 과학 학업성취도와 과학 학업성취도에 미치는 영향을 알아보았다. 개발한 수업 프로그램을 학생들에게 적용하기에 앞서, 중간학력평가 과학 학업성취도 점수에 대한 t검증을 통해 실험집단과 비교집단 간의 동질성을 확인하였고 실험집단은 2인 1조 또는 개별로, 비교집단은 6명 1모둠으로 구성하여 5차시에 걸쳐 수업을 진행하였다. 그 결과 t-검증을 통한 과학 학업성취도에서 유의확률 0.034로 유의수준 0.05에서 실험집단과 비교집단 사이에 유의미한 차이가 있었다. 추가적으로 전통적인 실험을 한 1개 반과 2명 1조 SSC 적용 실험 수업을 한 1개 반, 개별 SSC 적용 실험 수업을 한 1개 반의 과학 학업성취도를 살펴보았다. 일원배치 분산분석을 통해 살펴 본 결과 F 통계값 3.759, 유의확률 0.027로 유의수준 0.05에서 유의미한 차이가 있었으며, 전통적인 실험반의 평균은 67.58, 2인 1조 SSC 적용 실험반은 75.86, 개별 SSC 적용 실험반은 80.89로 개별 SSC 적용 실험반에서 과학 학업성취도가 가장 높았다. 또한 SSC를 적용한 실험 수업 프로그램을 준비할 때 교사는 수업 준비 및 수업 시간에 대한 부담이 줄었으며, 수업시간 동안 학생활동을 적극적으로 도와 줄 수 있었을 뿐 아니라 학생들의 실험활동도 적극적으로 이루어졌다. 이러한 결과를 통해 SSC 적용 실험 수업 프로그램 개발은 의미가 있으며 기존의 전통적인 실험 방법보다 학생들의 과학 학업성취도를 향상시킬 수 있음을 제시하였다.

• Genomics & Informatics
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• 제17권4호
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• pp.41.1-41.12
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• 2019

Survival analysis mainly deals with the time to event, including death, onset of disease, and bankruptcy. The common characteristic of survival analysis is that it contains "censored" data, in which the time to event cannot be completely observed, but instead represents the lower bound of the time to event. Only the occurrence of either time to event or censoring time is observed. Many traditional statistical methods have been effectively used for analyzing survival data with censored observations. However, with the development of high-throughput technologies for producing "omics" data, more advanced statistical methods, such as regularization, should be required to construct the predictive survival model with high-dimensional genomic data. Furthermore, machine learning approaches have been adapted for survival analysis, to fit nonlinear and complex interaction effects between predictors, and achieve more accurate prediction of individual survival probability. Presently, since most clinicians and medical researchers can easily assess statistical programs for analyzing survival data, a review article is helpful for understanding statistical methods used in survival analysis. We review traditional survival methods and regularization methods, with various penalty functions, for the analysis of high-dimensional genomics, and describe machine learning techniques that have been adapted to survival analysis.