• 정보관리학회지
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• 제13권2호
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• pp.97-120
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• 1996

본 연구는 듀이십진분류표의 인쇄형과 전자형 비교 및 이용 연구로 60명의 문헌정보학과 학생들을 대상으로 실시한 분류기호 작성에 관해 기술하고 있다. 4개의 다른 난이도로 이루어진 자료를 프로그램화된 듀이십진분류표 소개 책자로부터 선정하여 간단한 교육과 훈련을 하고 난후에 2문제씩 1차와 2차로 나누어 분류기호를 만들어 보게 하였다. 분류기호 작성 시간을 측정하고 분류과정과 결과 및 소요 시간을 기록하였다. 정확한 분류기호의 작성이 전자분류표의 사용에서 보다 신속하게 이루어졌지만 인쇄분류표를 사용한 학생들이 보다 많은 정확한 분류기호를 제공하였다. 또한 전자분류표의 인터페이스와 시스템 사양을 학생들이 제대로 적용하지 못했음에도 불구하고 인쇄분류표보다 전자분류표를 사용하면서 분류 작업에 더 많은 흥미를 느낀 것으로 나타났다. 영어 성적과 분류결과 성적의 상관관계를 측정한 결과ㅏ, 인쇄형으로 시작한 반은 부정적인 관계로까지 나왔고, 전자형으로 시작한 반은 극히 낮은 정적 관계로 나타났다. 총평점과 분류 결과 성적과도 아주 미약한 정적 관계만이 있었고 분류 소요 시간과 분류 결과 성적은 오히려 부정적인 관 瓮\ulcorner나타났다.

• Archives of Plastic Surgery
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• 제40권3호
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• pp.214-219
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• 2013

Background We established the Microvascular Research Center Training Program (MRCP) to help trainee surgeons acquire and develop microsurgical skills. Medical students were recruited to undergo the MRCP to assess the effectiveness of the MRCP for trainee surgeons. Methods Twenty-two medical students with no prior microsurgical experience, who completed the course from 2005 to 2012, were included. The MRCP comprises 5 stages of training, each with specific passing requirements. Stages 1 and 2 involve anastomosing silicone tubes and blood vessels of chicken carcasses, respectively, within 20 minutes. Stage 3 involves anastomosing the femoral artery and vein of live rats with a 1-day patency rate of >80%. Stage 4 requires replantation of free superficial inferior epigastric artery flaps in rats with a 7-day success rate of >80%. Stage 5 involves successful completion of one case of rat replantation/transplantation. We calculated the passing rate for each stage and recorded the number of anastomoses required to pass stages 3 and 4. Results The passing rates were 100% (22/22) for stages 1 and 2, 86.4% (19/22) for stage 3, 59.1% (13/22) for stage 4, and 55.0% (11/20) for stage 5. The number of anastomoses performed was $17.2{\pm}12.2$ in stage 3 and $11.3{\pm}8.1$ in stage 4. Conclusions Majority of the medical students who undertook the MRCP acquired basic microsurgical skills. Thus, we conclude that the MRCP is an effective microsurgery training program for trainee surgeons.

• 한국항공운항학회지
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• 제17권3호
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• pp.1-6
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• 2009

Since the success of the first flight, vast advancements have been made to the aircrafts with recent developments incorporating highly complex mechanisms, placing greater emphasis on the competence of the pilot. Studies are currently being undertaken to effectively source the trainee pilots with the most ideal level of aptitude for aviation with an aim to optimise the selection process with focus on economy and time, while research into identifying the optimal human characteristics for aviation is being done. As part of the selection process, number of tests is arranged with focus on the individual competence, suitability for flight, health status, aptitude and intelligence with the results of the tests used as reference materials during the selection procedure. This study has investigated the effect the academic competence has on the aptitude for aviation amongst many other abilities of human beings and the findings show that higher levels of aptitude have been demonstrated by the students who have displayed academic excellence across all the courses with statistics pointing to a positive correlation between the two subjects. This supports the theory that students who are academically superior have higher probability of being found to possess greater level of flight aptitude. The outcome of the study iterates the fact that academic competence of the students should not be regarded lightly in the selection process. Based on the current study, it is believed that a research into determining the relationship between the SAT results, average yearly grade and flight aptitude will help identify the key factors in possessing high level of flight aptitude with greater certainty.

• 한국응급구조학회지
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• 제16권2호
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• pp.23-30
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• 2012

Purpose : This study was designed to compare the easiness and speed of insertion of three supraglottic airway devices(SADs) in a manikin setting. Methods : Three different SADs - Laryngeal Mask Classic(cLMA), I-gel and Streamlined Liner of the Pharynx Airway(SLIPA) were applied. One hundred and nineteen paramedical students with(group H) or without (group L) previous airway experience were taught brief manikin training about the use of the cLMA, I-gel and SLIPA. The students inserted each device in a randomized order. Time to effective ventilation was recorded in seconds from holding the device to the first chest inflation. Success was determined as adequate chest wall movement. Results : The insertion attempts were lesser in I-gel($1.00{\pm}0.00$) and SLIPA($1.05{\pm}0.27$) than cLMA($1.16{\pm}0.41$, p<.05). The shortest time to insertion was recorded for I-gel($10.5{\pm}3.0sec$), followed by the SLIPA($12.9{\pm}4.5sec$) and cLMA($19.6{\pm}4.1sec$, p<.05). There were no significant differences in the insertion attempts and insertion time of I-gel between group L and group H. But in cLMA, longer insertion time and more insertion attempts were recorded in group L than group H. Conclusion : Both I-gel and SLIPA were superior to cLMA in the easiness and speed of insertion. Even in novice students, I-gel showed an excellent result in a manikin.

• 정보교육학회논문지
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• 제24권6호
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• pp.597-606
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• 2020

최근 전세계가 언택트 환경에 놓임에 따라 학생들의 프로그래밍 수업도 온라인으로 이루어지게 되었고, 온라인 프로그래밍 수업을 성공으로 이끌 수 있는 영향요인들에 대한 관심이 커지고 있다. 이에 본 연구에서는 특성화 고등학교 학생들을 대상으로 웹기반 시뮬레이션 툴을 활용하여 온라인 프로그래밍 수업을 진행하였다. 그리고 온라인 프로그래밍 수업에서 학생들의 학습참여와 교수실재감에 영향을 주는 변인으로 자기조절능력과 학습 몰입을 상정하고 예측력을 분석하였다. 또한 학습참여, 교수실재감과 학습자의 자기조절능력 사이에서 학습몰입의 매개효과를 분석하였다. 연구 결과 온라인 프로그래밍 수업에서 자기조절능력과 학습몰입이 학습참여와 교수 실재감을 예측하는 것으로 나타났고, 학습몰입은 자기조절능력과 학습참여, 교수실재감 사이에서 매개역할을 하는 것으로 나타났다. 본 연구는 온라인 프로그래밍 수업에서 학습참여와 교수실재감을 높이기 위해 자기조절능력과 학습몰입이 고려되어야 함을 제안하고, 이를 위한 실천적 시사점을 제공하였다는 데 의의가 있다.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.246-256
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• 2022

Recently, parents and teachers consider physical education as a minor subject for students in elementary and secondary schools. Physical education performance has become increasingly significant as parents and schools pay more attention to physical schooling. The sports mining with distribution analysis model considers different factors, including the games, comments, conversations, and connection made on numerous sports interests. Using different machine learning/deep learning approach, children's athletic and academic interests can be tracked over the course of their academic lives. There have been a number of studies that have focused on predicting the success of students in higher education. Sports interest prediction research at the secondary level is uncommon, but the secondary level is often used as a benchmark to describe students' educational development at higher levels. An Automated Student Interest Prediction on Sports Mining using DL Based Bi-directional Long Short-Term Memory model (BiLSTM) is presented in this article. Pre-processing of data, interest classification, and parameter tweaking are all the essential operations of the proposed model. Initially, data augmentation is used to expand the dataset's size. Secondly, a BiLSTM model is used to predict and classify user interests. Adagrad optimizer is employed for hyperparameter optimization. In order to test the model's performance, a dataset is used and the results are analysed using precision, recall, accuracy and F-measure. The proposed model achieved 95% accuracy on 400^th instances, where the existing techniques achieved 93.20% accuracy for the same. The proposed model achieved 95% of accuracy and precision for 60%-40% data, where the existing models achieved 93% for accuracy and precision.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제36권4호
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• pp.511-533
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• 2022

본 연구는 학생들의 자기 주도적 학습을 지지하는 CARE 학습 코칭 모델에 수학 교과의 특징 및 수학 교수·학습 과정을 반영함으로써 수학 교과에 적합한 학습 코칭 모델을 개발하고자 하였다. 본 연구에서 개발한 수학 학습 코칭 모델은 코칭을 적용해 나가는 '단계'와 '요소' 그리고 이를 수행하기 위한 '전략'이다. 수학 학습 코칭 모델은 '편안한 분위기 조성' 단계의 요소로써 라포, 신뢰, 상태관리, 수학 사전검사를, '인식의 개선' 단계의 요소로써 문제점 인식, 초인지, 재구조화, 주도성, 수학 학습역량을, '학습 몰입의 재각성' 단계의 요소로써 자기효능감, 학습 준비성, 확인(피드백)을, '임파워먼트' 단계의 요소로써 자발적 동기와 성공 경험을 배치하고 각각의 요소를 수행하기 위한 다양한 수학학습 전략을 제시하였다. 수학학습 코칭 모델은 수학 교사들이 학생들의 학습 동기를 유발하고 학생들이 학생 스스로 자신의 문제를 해결해 나갈 수 있도록 돕는데 활용될 수 있다.

• International Journal of Computer Science & Network Security
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• 제23권10호
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• pp.135-146
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• 2023

An effective educational program warrants the inclusion of an innovative construction which enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational Decision Support System (EDSS) has currently been a hot topic in educational systems, facilitating the pupil result monitoring and evaluation to be performed during their development. Insufficient information systems encounter trouble and hurdles in making the sufficient advantage from EDSS owing to the deficit of accuracy, incorrect analysis study of the characteristic, and inadequate database. DMTs (Data Mining Techniques) provide helpful tools in finding the models or forms of data and are extremely useful in the decision-making process. Several researchers have participated in the research involving distributed data mining with multi-agent technology. The rapid growth of network technology and IT use has led to the widespread use of distributed databases. This article explains the available data mining technology and the distributed data mining system framework. Distributed Data Mining approach is utilized for this work so that a classifier capable of predicting the success of students in the economic domain can be constructed. This research also discusses the Intelligent Knowledge Base Distributed Data Mining framework to assess the performance of the students through a mid-term exam and final-term exam employing Multi-agent system-based educational mining techniques. Using single and ensemble-based classifiers, this study intends to investigate the factors that influence student performance in higher education and construct a classification model that can predict academic achievement. We also discussed the importance of multi-agent systems and comparative machine learning approaches in EDSS development.

• 의학교육논단
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• 제26권1호
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• pp.27-35
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• 2024

Medical students' career choices hold significant importance at both individual and national levels. Therefore, Chungnam National University College of Medicine aimed to systematize its revised career fair in 2022, basing its efforts on a career planning process model. Chungnam National University College of Medicine sought to formalize the design process by utilizing the ADDIE model (analysis design, development, implementation, evaluation model) in developing programs for the career fair program. Throughout the entire process, the student support center and student council actively collaborated, striving to incorporate students' requests and opinions. They designed and developed a program for all stages of the career planning process. However, a new stage ("review & ref lection") was added to the existing 4-phase model, creating a transformed framework where this stage interacts with the original 4 phases. Each stage involved portfolios, career aptitude tests, career-related lectures, posters with introductory information about majors, and booths for each major. The revised career fair attracted double the expected participants (N=589). The program evaluation survey showed overall positive responses (N=135). Additionally, some factors in the Specialty Indecision Scale showed significant differences between before and after the career fair. The success of the newly developed career fair at Chungnam National University College of Medicine can be attributed to its systematic framework and the active involvement of students throughout the process. However, for aspects with long-term implications, such as "understand yourself " and "choose your specialty," there may be a need for supplementary programs.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권4호
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• pp.270-275
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• 2016

We present an approach for acceleration actor-critic algorithm for reinforcement learning with continuous action space. Actor-critic algorithm has already proved its robustness to the infinitely large action spaces in various high dimensional environments. Despite that success, the main problem of the actor-critic algorithm remains the same-speed of convergence to the optimal policy. In high dimensional state and action space, a searching for the correct action in each state takes enormously long time. Therefore, in this paper we suggest a search accelerating function that allows to leverage speed of algorithm convergence and reach optimal policy faster. In our method, we assume that actions may have their own distribution of preference, that independent on the state. Since in the beginning of learning agent act randomly in the environment, it would be more efficient if actions were taken according to the some heuristic function. We demonstrate that heuristically-accelerated actor-critic algorithm learns optimal policy faster, using Educational Process Mining dataset with records of students' course learning process and their grades.