• 컴퓨터교육학회논문지
• /
• 제10권1호
• /
• pp.31-40
• /
• 2007

직업 생활에서 공통적으로 필요한 자질과 변화하는 직업 세계에 능동적으로 대처할 수 있는 능력의 필요성이 대두되면서 직업기초능력의 중요성이 인식되기 시작하였다. 이에 본 연구에서는 상업계 고등학교 컴퓨터 교과의 홈페이지 제작 학습에 프로젝트 학습 모형을 적용하여 프로젝트 학습 방법이 직업기초능력 중의 정보능력에 미치는 효과를 알아보고자 하였다. 연구 결과, 프로젝트 학습 집단과 전통 학습 집단의 차이가 유의미하여 프로젝트 학습 방법 적용이 학생들의 정보능력 신장에 긍정적인 효과를 나타내었다. 이 연구에서 직업기초능력을 신장시킬 수 있는 효과적인 교육 방법이 제안되었으며, 앞으로 정보능력 뿐 아니라 다른 하위 능력의 신장에 관한 연구가 필요할 것으로 생각된다.

• 한국간호교육학회지
• /
• 제14권1호
• /
• pp.30-37
• /
• 2008

Purpose: This study proposed to examine the effects of a blended-learning orientation program executed for nursing students' clinical practice. Method: The participants were 61 nursing students in the experimental group and 57 in the control group. For the experimental group, a blended-learning orientation program was executed by e-learning (on-line) and lecture-led training (off-line) from two-week before the start of clinical practice in medical-surgical nursing. For the control group, orientation was given in the traditional lecture-led training by distributing printed materials before clinical practice. A pre-test was conducted on the experimental and control group before clinical practice, and a post-test was conducted after two-week of clinical practice in order to examine the effects of the orientation program. Results: After two-week of clinical practice, differences were observed between the experimental group and the control group in adaptation to clinical practice (F=10.242, p=.002), communication skills (F=4.305, p=.040) and clinical competence (F=6.823, p=.010). Conclusions: The blended-learning orientation program enhanced nursing students' adaptation to clinical practice, improved their communication skill and increased their clinical competence. Accordingly, it is recommended to develop and apply practical education using blended-learning in the area of nursing science.

• 의학교육논단
• /
• 제17권3호
• /
• pp.97-104
• /
• 2015

This literature review explores relevant research and evaluation on pedagogy and physical learning spaces. This study also is intended to encourage discussion among stakeholders on the best medical school developments, in light of emerging learning trends relevant to their institutions. The study has revealed that new environments for learning are being designed or reshaped in response to changing pedagogical approaches, to incorporate new information technology, and to accommodate the changing abilities of new generations of learners. Formal teaching spaces for large groups with a 'sage on a stage' are becoming less common than smaller lecture rooms, although classrooms form a large component of universities and will continue to dominate in the future. However, the traditional layout of these spaces is being transformed to incorporate multiple learning modes. Classrooms should be profound places of revelation and discovery. A well-designed space has the ability to elevate discourse, encourage creativity, and promote collaboration. Within the classroom walls, a learning space should be as flexible as possible, not only because different teachers and classes require different configurations, but because in order to fully engage in learning, students need to transition between lectures, group study, presentations, discussions, and individual work time.

• 정보교육학회논문지
• /
• 제7권2호
• /
• pp.189-197
• /
• 2003

WBI(Web Based Instruction)는 교수 학습 자료의 개발 부담으로 특정 교과에 국한되어 있다. 본 논문은 WBI를 워드프로세서의 수업에 적용하여 인터넷 기반의 개별화된 교수-학습 시스템을 구현하였다. WBI를 적용한 워드프로세서 수업 방식은 전통적 수업 방식에 비해 학생들이 더욱 흥미를 느끼게 하고, 워드프로세서의 수준별, 능력별, 단계별 학습 선택으로 인해 학생 중심의 학습을 가능하게 하였다. 또한 개별학습 과제를 통해 학습내용을 실시간 평가 할 수 있으며 피드백이 가능하여 학습 효과를 극대화시킬 수 있었다.

• 한국수학교육학회지시리즈C:초등수학교육
• /
• 제21권1호
• /
• pp.1-17
• /
• 2018

최근 플립드 러닝, 블렌디드 러닝 등 전통적인 강의식 수업에 변화를 꾀하는 다양한 시도가 이루어지고 있으며, 다양한 분야에서 그 효과성이 검증되고 있다. 한편, 2015 개정 교육과정에서는 학생 참여형 수업을 활성화하여 자기주도적 학습 능력을 기를 수 있도록 하고 있다. 이러한 시대적 요구에 맞게 교수자 역시 수업 방식의 변화를 시도하여야 하고, 그러한 새로운 수업 방식의 장단점과 효과를 확인하면서 더 나은 수업으로의 개선을 꾀하여야 할것이다. 본 연구에서는 교육대학 2학년 학생들이 필수로 이수하는 초등수학교육 이론 수업에 플립드 러닝을 적용한 사례를 분석하였다.

• 한국초등과학교육학회지:초등과학교육
• /
• 제25권2호
• /
• pp.141-148
• /
• 2006

The purpose of this study is to examine the efforts of cooperative loaming through a student team-achievement division(STAD) model on elementary school students' learning achievements and science ,elated attitudes toward the field of astronomy. This study was conducted using 72 students of the fifth-grade class in a elementary school in Busan. The 18 science lessons of the 'Family of the sun' were executed over 6 weeks in the fifth-year students classes. In this study, the experimental group were exposed to cooperative learning through STAD and the contrast group were exposed to a traditional teacher-centered class. The results show that the STAD class of the experimental group had a greater effect upon the elementary school students' science learning achievement and science related attitudes toward the field of astronomy than those of the comparison group. Additionally, the students recognized that cooperative learning provokes both interest in loaming and in their studies generally and also they expressed a desire to continue with cooperative teaming methods.

• 전자공학회논문지CI
• /
• 제48권5호
• /
• pp.83-87
• /
• 2011

나이브 베이시안은 기계학습에서 많이 사용되고 상대적으로 좋은 성능을 보인다. 하지만 전통적인 나이브 베이시안 학습의 환경은 두 가지의 가정을 기반으로 학습을 수행한다: (1) 각 속성들의 값은 서로 독립적이다. (2) 각 속성들의 중요도는 동일하다. 본 연구에서는 각 속성의 중요도가 동일하다는 가정에 대하여 새로운 방법을 제시한다. 즉 각 속성은 현실적으로 다른 중요도를 가지며 본 논문은 나이브 베이시안에서 각 속성의 중요도를 계산하는 새로운 방식을 제안한다. 제안된 알고리즘은 다수의 데이터를 이용하여 기존의 나이브 베이시안과 SBC 등의 다른 확장된 나이브 베이시안 방법들과 비교하였고 대부분의 경우에 더 좋은 성능을 보임을 알 수 있었다.

• International Journal of Computer Science & Network Security
• /
• 제21권9호
• /
• pp.125-131
• /
• 2021

Detecting fraudulent insurance claims is difficult due to small and unbalanced data. Some research has been carried out to better cope with various types of fraudulent claims. Nowadays, technology for detecting fraudulent insurance claims has been increasingly utilized in insurance and technology fields, thanks to the use of artificial intelligence (AI) methods in addition to traditional statistical detection and rule-based methods. This study obtained meaningful results for a fraudulent insurance claim detection model based on machine learning (ML) and deep learning (DL) technologies, using fraudulent insurance claim data from previous research. In our search for a method to enhance the detection of fraudulent insurance claims, we investigated the reinforcement learning (RL) method. We examined how we could apply the RL method to the detection of fraudulent insurance claims. There are limited previous cases of applying the RL method. Thus, we first had to define the RL essential elements based on previous research on detecting anomalies. We applied the deep Q-network (DQN) and double deep Q-network (DDQN) in the learning fraudulent insurance claim detection model. By doing so, we confirmed that our model demonstrated better performance than previous machine learning models.

• International Journal of Computer Science & Network Security
• /
• 제21권8호
• /
• pp.308-316
• /
• 2021

During the past two years, the education systems in the world witnessed unprecedented turmoil due to the coronavirus (Covid-19) pandemic, as most schools and universities in the world closed their doors to more than 1.5 billion students, or more than 90% of the total learners, according to recent figures issued by the UNESCO Institute for Statistics. Education experts have agreed that post- coronavirus education will not be the same as before, especially with the increasing use of modern technology in education. One of the most important new patterns with a structure digital in education is distance education, this style has been used, in many countries of the world, as an alternative to traditional education, since the beginning of the pandemic. In Saudi Arabia, this type of education has been used in all educational institutions, starting from kindergarten until the postgraduate level, as an alternative to face-to-face education to preserve the health and safety of students and workers in educational institutions. This study aimed to explore the level of satisfaction of preparatory year students on distance learning in their first year of study at Umm Al-Qura University. The findings of this study showed that students in the preparatory year were satisfied with their online learning experience. In addition, the results revealed that there was no effect for gender and location of study on students' level of satisfaction. Saudi universities should continue to work to create a suitable learning environment for students at the e-learning level.

• 인터넷정보학회논문지
• /
• 제21권6호
• /
• pp.33-39
• /
• 2020

The paper is to build recommendation systems leveraging Deep Learning and Big Data platform, Spark to predict item ratings of the Amazon e-commerce site. Recommendation system in e-commerce has become extremely popular in recent years and it is very important for both customers and sellers in daily life. It means providing the users with products and services they are interested in. Therecommendation systems need users' previous shopping activities and digital footprints to make best recommendation purpose for next item shopping. We developed the recommendation models in Amazon AWS Cloud services to predict the users' ratings for the items with the massive data set of Amazon customer reviews. We also present Big Data architecture to afford the large scale data set for storing and computation. And, we adopted deep learning for machine learning community as it is known that it has higher accuracy for the massive data set. In the end, a comparative conclusion in terms of the accuracy as well as the performance is illustrated with the Deep Learning architecture with Spark ML and the traditional Big Data architecture, Spark ML alone.