• 수산해양교육연구
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• 제26권1호
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• pp.156-165
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• 2014

The purpose of this study was to find research trends of smart learning. For this, we identified the research's characteristics such as the subject or keyword of research, method, data collection, and statistical analysis method. The 2,865 articles published from 1995 to 2013 were gathered from five Korean academic journals related to smart learning. Among them, research keyword, areas, research method, data collection method, and statistical analysis method were analyzed on 596 papers. The findings of this study were as follows: (a) Smart learning papers such keyword likes u-learning, m-learning, and smart-learning were emerging after 2006. Smart learning papers with ICT related topics were highly increased after 2000, but they were decreased after 2006. Smart learning papers with e-learning related keywords were steadily increased after 2000 through 2013. (b) The research field of deign had the highest portion in smart learning research, but managing had the lowest portion. (c) Development was mainly used as a research method. Both questionnaire and experiment were mainly used for collecting data methods. T-test and frequency analysis were mainly used as statistical analysis methods.

• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.286-294
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• 2023

We studied learners' perceptions and learning styles of project research activities in the chemical field conducted by 54 science high school students. In a survey of students' perceptions of task research, positive responses were found in "internal motivation," "cooperation," "task solving," and "tenacity and immersion," and statistically significant differences were found in "self-directedness," "cooperation," and "tenacity and immersion" by year. The 'lower' group responded most positively in the 'cooperation' category, and the 'higher' group responded most positively in the 'task solving' category. As a result of investigating the learning styles of the students who conducted the task research, it was found in the order of assimilator, converger, accommodator, and diverger. The assimilators showed the characteristic of systematically and scientifically approaching the problem. Convergers were found to have excellent problem-solving and decision-making ability, are practical, and have experimental-based thinking characteristics. In this study, the characteristics of science high school students showed well in the results of the learning style performed.

• Journal of Hospice and Palliative Care
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• 제18권1호
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• pp.9-15
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• 2015

말기암환자 관리를 위해서 전문인력 교육은 필수적이다. 정부에서는 암관리법을 통해 호스피스완화의료의 양적 확대를 기반으로 전문 인력을 양성하기 위해 제2기 암정복 10개년 계획에서 전문인력 확충계획을 발표하였다. 그간, 호스피스완화의료 전문인력 훈련을 위한 표준교육 과정과 의사/간호사 e-learning에 이어 이번 사회복지사 e-learning을 개발하여 운영하게 되었다. 호스피스완화의료 현장에서 사회복지사는 호스피스완화의료 대상자들의 심리 사회적 문제를 해결하는 중추적 역할을 수행해왔으며, 우리나라 호스피스완화의료가 정착되고 제도화되기까지 현장에서 전문가의 책임과 역할을 다해오고 있다. 하지만 그간 사회복지사 직종을 위한 체계적인 교육 과정이 없는 실정으로 사회복지 실천 지식과 기술을 충분히 습득하는 데 어려움이 있었다. 이번 호스피스완화의료 사회복지사 e-learning 과정 개발을 통해 말기암환자를 돌보는 사회복지사의 정체성과 전문성, 임상현장에서의 실천능력이 함양되고 교육 접근성이 향상될 것이며, 향후 보수교육 과정을 통한 지속적인 전문성 보장을 위한 교육제도가 제도적으로 도입되어 더욱 발전하길 기대한다.

• Asia pacific journal of information systems
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• 제16권4호
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• pp.179-202
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• 2006

The objective of this study is to identify the impacts of communication reinforcement on performance of learning in Web-PBL. Communication reinforcement is defined as the combination of information sharing and co-construction. As factors facilitating communication reinforcement, we propose learner's characteristics, task characteristics, and group characteristics. Learner's characteristics are collaboration-orientation, openness, holistic approach, and online community-orientation which reflects e-learning environment. Collaboration-oriented tasks as group projects were developed and given to groups with 5-6 members. The group characteristics are categorized into 'horizontal' and 'vertical', according to the patterns of communication between a group leader and members. To verify empirically the proposed research model, an experimental design was performed to learners who took on-line and off-line courses with group projects. We found important results as follows; First, field dependence has positive impacts on information sharing, and online community-orientation has positive impacts on co-construction. These results correspond with prior studies on relationship between field dependence and collaborative learning. Second, collaboration-oriented task directly impacts on information sharing, and indirectly affects co-construction, This result implicates that information sharing is pre-requisite of co-construction. Third, 'horizontal' was identified as a factor giving positive effects on information sharing and co-construction. This result implies that horizontal communication is very important to facilitate communication reinforcement.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제32권1호
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• pp.23-36
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• 2018

인공지능(Artificial Intelligence)의 잠재력에 대한 기대로 여러 분야에서 이를 활용하고자 노력하고 있으며 교육 분야에서의 적용에 대한 관심 역시 높다. 교육에 있어서 인공지능 기술에 활용되는 기계학습(machine learning)과 딥러닝(deep learning)으로 스스로 학습하는 방법에 대한 관심을 가지게 되었으며 이러한 방식이 교육에 어떻게 활용될 수 있을 지와 인공지능을 어떻게 수학교육에 적용할 수 있을지에 대한 관심이 대두되고 있다. 이에 정보통신기술의 발달에 따른 수학교육의 변화를 고찰해 봄으로써 수학교육의 변화가 인공지능과 어떠한 연과성이 있는지를 살펴보는데 의의가 있다고 할 수 있다.

• Geomechanics and Engineering
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• 제29권3호
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• pp.249-258
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• 2022

A disc cutter is an excavation tool on a tunnel boring machine (TBM) cutterhead; it crushes and cuts rock mass while the machine excavates using the cutterhead's rotational movement. Disc cutter wear occurs naturally. Thus, along with the management of downtime and excavation efficiency, abrasioned disc cutters need to be replaced at the proper time; otherwise, the construction period could be delayed and the cost could increase. The most common prediction models for TBM performance and for the disc cutter lifetime have been proposed by the Colorado School of Mines and Norwegian University of Science and Technology. However, design parameters of existing models do not well correspond to the field values when a TBM encounters complex and difficult ground conditions in the field. Thus, this study proposes a series of machine learning models to predict the disc cutter lifetime of a shield TBM using the excavation (machine) data during operation which is response to the rock mass. This study utilizes five different machine learning techniques: four types of classification models (i.e., K-Nearest Neighbors (KNN), Support Vector Machine, Decision Tree, and Staking Ensemble Model) and one artificial neural network (ANN) model. The KNN model was found to be the best model among the four classification models, affording the highest recall of 81%. The ANN model also predicted the wear rate of disc cutters reasonably well.

• Nuclear Engineering and Technology
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• 제54권11호
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• pp.3985-3995
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• 2022

The emergence of new nanoscale technologies has imposed significant challenges to designing reliable electronic systems in radiation environments. A few types of radiation like Total Ionizing Dose (TID) can cause permanent damages on such nanoscale electronic devices, and current state-of-the-art technologies to tackle TID make use of expensive radiation-hardened devices. This paper focuses on a novel and different approach: using machine learning algorithms on consumer electronic level Field Programmable Gate Arrays (FPGAs) to tackle TID effects and monitor them to replace before they stop working. This condition has a research challenge to anticipate when the board results in a total failure due to TID effects. We observed internal measurements of FPGA boards under gamma radiation and used three different anomaly detection machine learning (ML) algorithms to detect anomalies in the sensor measurements in a gamma-radiated environment. The statistical results show a highly significant relationship between the gamma radiation exposure levels and the board measurements. Moreover, our anomaly detection results have shown that a One-Class SVM with Radial Basis Function Kernel has an average recall score of 0.95. Also, all anomalies can be detected before the boards are entirely inoperative, i.e. voltages drop to zero and confirmed with a sanity check.

• Journal of Information Processing Systems
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• 제18권2호
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• pp.245-257
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• 2022

In the Internet of Things (IoT) era, the types of devices used by one user are becoming more diverse and the number of devices is also increasing. However, a forensic investigator is restricted to exploit or collect all the user's devices; there are legal issues (e.g., privacy, jurisdiction) and technical issues (e.g., computing resources, the increase in storage capacity). Therefore, in the digital forensics field, it has been a challenge to acquire information that remains on the devices that could not be collected, by analyzing the seized devices. In this study, we focus on the fact that multiple devices share data through account synchronization of the online platform. We propose a novel way of identifying the user's interest through analyzing the remnants of targeted advertising which is provided based on the visited websites or search terms of logged-in users. We introduce a detailed methodology to pick out the targeted advertising from cache data and infer the user's interest using deep learning. In this process, an improved learning model considering the unique characteristics of advertisement is implemented. The experimental result demonstrates that the proposed method can effectively identify the user interest even though only one device is examined.

• 한국융합학회논문지
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• 제10권12호
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• pp.243-250
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• 2019

디자인 분야에서 온라인, 모바일을 통한 융합교육의 보급이 빠르게 확장되고 있다. 특히 증강현실 기술을 응용한 교육 프로그램 개발이 점차 널리 사용되고 있다. 이 글은 우선, 증강현실 기술의 현재 상태와 장점을 검토함으로써 교육 응용 분야에서 증강현실의 필요성을 강조한다. 둘째, 필자는 새로운 유형의 교육 시스템인 "AR + E" 교육 클라우드 플랫폼 시스템을 제안한다. 이 시스템은 일반 종이 교과서, 범용 휴대용 이동 단말기와 APP 등 3가지로 구성된다. 본 연구는 자동차 정비 전공 학생들을 대상으로 하여 "AR + E" 교육 시스템의 유용성 및 성능 실험을 통해 "AR + E" 시스템이 학습 효과에 미치는 영향 연구 조사하였다. "AR + E"시스템은 전통적인 학습 그룹과의 비교 실험을 통해 AR 대화식 미디어를 사용하여 학습자의 학업 성과를 향상시킬 뿐만 아니라, 재미와 참여도 및 연속성을 향상시키는 결과를 얻게 되었다. 끝으로, 사용자 경험, 행위와 기호에 대한 관찰과 인터뷰를 통해 AR 기반 교육 프로그램 소프트웨어를 디자인하고 개발하여 제안하고 있다.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제34권4호
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• pp.465-484
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• 2020

본 연구에서는 수학 현장체험학습 프로그램이 학생들의 수학 학습에 대한 태도에 미치는 영향을 밝히고자 하였다. 이를 위해 2019년 제주목 관아에서 학생들이 직접 걸어 다니면서 체험할 수 있는 제주목 관아 매쓰투어(Math-Tour) 프로그램을 개발하였다. 프로그램에는 제주목 관아에서 볼 수 있는 여러 자연물과 인공물을 이용한 수학 문제를 제시하였다. 이후 제주시 A 중학교 학생들을 대상으로 체험하도록 하여 그 효과를 알아보았다. 매쓰투어에 참여한 학생들을 대상으로 사전·사후 수학 학습 태도 검사와 인터뷰를 실시하고, 소감문을 작성하도록 하여 이를 분석했다. 분석 결과, 수학 현장체험학습 프로그램인 제주목 관아 매쓰투어가 학생들의 수학 학습 태도 신장에 통계적으로 유의미한 영향을 미친다는 결론을 얻을 수 있었다. 이는 수학 현장학습 프로그램이 학생들의 수학 학습 태도를 개선하는데 유의미한 방법으로 활용될 수 있다는 것을 시사해 준다.