• Journal of the Korean Data and Information Science Society
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• 제26권4호
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• pp.801-812
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• 2015

본 연구에서는 H/W 전공자들의 수학 관련 전공교과목의 관심도 증대와 학업성취도 향상을 목적으로, 첫째, H/W 전공자들이 선호하지 않는 수학을 활용하는 전공분야에 학습자의 수학적 역량을 발전시켜 취업 관심도를 높이고 위의 분야로 취업을 도모하기 위한 교육사례를 제시하였다. 둘째, 향후 H/W 분야에서 컴퓨터프로그래밍을 도구로 한 효율적인 수학 관련 교과목의 교수법을 개발하여 실제 교육현장에 적용해서 전공자들의 학습에 대한 동기 부여와 교육적 효과를 파악하였다. 마지막으로 학업성취도와 설문조사를 실시하고 통계적으로 분석하여 수학 교육에 대한 효과적 운영방안을 제시하고자 하였다.

• 한국도로학회논문집
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• 제20권2호
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• pp.127-135
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• 2018

PURPOSES : This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS : Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS : Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.

• 공학교육연구
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• 제20권3호
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• pp.25-31
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• 2017

As the world enters the era of the Fourth Industrial Revolution, which is represented by advanced technology, it not only changes the industrial field but also the education field. In recent years, Smart Learning has enriched learning by using diverse forms and technologies that utilize vast amount of information about learners' individual knowledge through the emergence of realistic and intelligent contents that combine high technology such as artificial intelligence, big data and virtual reality and there is an increasing interest in intelligent adaptive learning, which can customize individual education. Therefore, the purpose of this study is to explore intelligent adaptive learning method through recent smart education environment, beyond traditional writing-based communication education which is highly dependent on the competency of instructors. In this study, we analyzed the various learner information collected in the communication course and constructed a concrete teaching and learning method of intelligent adaptive learning based on the instructor's intended smart contents. The result of this study is expected to be the basis of highly personalized teaching and learning method of digital method in communication education which is emphasized in the fourth industrial revolution era.

• 컴퓨터교육학회논문지
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• 제16권3호
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• pp.31-39
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• 2013

본 연구는 교수자와 학습자들이 소유하고 있는 여러 장치들을 활용한다는 개념을 이용하여 스마트러닝 환경을 지원할 수 있는 학습자 평가시스템을 개발하여 수업에 적용하였다. 또한, 인터페이스, 상호작용, 애플리케이션, 기술지원, 평가 영역을 통해 학습자의 만족도를 분석하였다. 개발된 시스템은 태블릿 PC와 스마트폰용 애플리케이션 프로그램, 프로젝터를 지원하는 전자교탁용 프로그램, 서버 프로그램으로 구성된다. 수업자료 및 학습자에 대한 평가, 피드백 자료는 모두 서버에 저장되며, 학습자는 이를 이용하여 스마트폰, 데스크탑 PC를 통해 학습하거나 수업에 대한 피드백을 실시간 받을 수 있게 하였다. 제안된 시스템을 이용할 경우 학습자의 학업성취도와 학습에 대한 흥미를 높일 수 있음을 보이고 있다.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제14권2호
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• pp.173-194
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• 2010

This study examines the differences and similarities of mathematics teachers' subject matter knowledge among England, the Chinese mainland and Hong Kong. Data were collected from a ten-item test in the SKIMA subject matter audit instrument [Rowland, T.; Martyn, S.; Barber, P. & Heal, C. (2000). Primary teacher trainees' mathematics subject knowledge and classroom performance. In: T. Rowland & C. Morgan (eds.), Research in Mathematics Education, Volume 2 (pp.3-18). ME 2000e.03066] from over 500 participants. Results showed that participants from England performed consistently better, with those from Hong Kong being next and then followed by those from the Chinese mainland. The qualitative data revealed that participants from Hong Kong and the Chinese mainland were fluent in applying routines to solve problems, but had some difficulties in offering explanations or justifications.

• Journal of Information Technology Applications and Management
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• 제21권3호
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• pp.65-77
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• 2014

Ubiquitous learning has aroused great interest and is becoming a new way for foreign language education in today's society. However, how to increase the learners' initiative and their community cohesion is still an issue that deserves more profound research and studies. Emotional intelligence can help to detect the learner's emotional reactions online, and therefore stimulate his interest and the willingness to participate by adjusting teaching skills and creating fun experiences in learning. This is, actually the new concept of smart education. Based on the previous research, this paper concluded a neural mechanism model for analyzing the learners' emotional characteristics in ubiquitous environment, and discussed the intelligent monitoring and automatic recognition of emotions from the learners' speech signals as well as their behavior data by multi-agent system. Finally, a framework of emotional intelligence system was proposed concerning the smart foreign language education in ubiquitous learning.

• Journal of the Korean Data and Information Science Society
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• 제25권3호
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• pp.501-512
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• 2014

본 연구에서는 H/W 전공자들의 프로그래밍 학업성취도 향상을 목적으로, 첫째, H/W 전공자들이 선호하지 않는 프로그래밍 분야에 학습자의 역량을 발전시켜 취업 관심도를 높이고 프로그래밍 분야로 취업을 도모하기 위한 교육사례를 제시하였다. 둘째, 향후 H/W 분야에서 학과차원의 특수성과 실정을 반영한 프로그래밍 교수법에 관하여 제안하였다. 마지막으로 교육사례와 설문조사를 실시하고 통계적으로 분석하여 프로그래밍 교육의 질 향상과 발전의 계기로 삼고자 하였다.

• STI Policy Review
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• 제8권2호
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• pp.49-74
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• 2017

What are some of the explanations for cross-national diversity of foresight performance among technological followers? Why are some countries more successful than others in learning how to develop national innovation system foresight? This paper argues that the answers are linked to organizational capacities at three different levels: governmental, policy network and social learning. To corroborate this argument, the paper chose Iran and Korea as benchmarking partners, and attempts to find out what makes Iran a slow learner in building innovation system foresight. The conceptual model is an improved model of Saritas's, by integrating Borras' and Andersen's conceptions and classifications. The data are collected from comprehensive interviews in both countries and second-hand data of international indexes. The paper, finally, concludes that it is the weakness of analytical-systemic capacity that impedes and delays the emergence of systemic foresight in Iran, and that this weakness stems from the adverse impacts of the dominant institutions, surrounding the innovation system. The final point is that it is not sufficient for Iran to learn the methods and techniques of foresight from Korea. It should learn how to open its macro-policy towards the global market and design appropriate industrial strategy in a coherent policy-strategy portfolio.

• The Journal of Asian Finance, Economics and Business
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• 제8권10호
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• pp.259-267
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• 2021

Both structural transformation and education are the predominant subjects in the literature of development economics. This study examines the relationship between education before the tertiary level and the structural transformation of provinces by using Vietnam as a case study. In this study, education before the tertiary level would be disaggregated into three groups: primary, lower secondary, and upper secondary, then analyzed simultaneously on three-panel data models. Research data is taken from the statistical yearbook of provinces in Vietnam for 2015-2018. Research results show that education before the tertiary level plays a vital role in structural transformation. The enrolment rate of various education levels has a different influence on economic structure, and the lower secondary level has more significant effects than the upper secondary level. This reflects that participating in lower secondary is a fundamental requirement for taking some jobs in the non-agriculture sector, while upper secondary helps to upgrade the learner's abilities to respond to higher requirement jobs. The high rate of repeaters in upper secondary education will slow down the structural shift towards non-agriculture, and changing the traditional attitude about repeaters plays an essential role in improving this rate.

• ETRI Journal
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• 제42권6호
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• pp.886-898
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• 2020

Unusual data patterns or outliers can be generated because of human errors, incorrect measurements, or malicious activities. Detecting outliers is a difficult task that requires complex ensembles. An ideal outlier detection ensemble should consider the strengths of individual base detectors while carefully combining their outputs to create a strong overall ensemble and achieve unbiased accuracy with minimal variance. Selecting and combining the outputs of dissimilar base learners is a challenging task. This paper proposes a model that utilizes heterogeneous base learners. It adaptively boosts the outcomes of preceding learners in the first phase by assigning weights and identifying high-performing learners based on their local domains, and then carefully fuses their outcomes in the second phase to improve overall accuracy. Experimental results from 10 benchmark datasets are used to train and test the proposed model. To investigate its accuracy in terms of separating outliers from inliers, the proposed model is tested and evaluated using accuracy metrics. The analyzed data are presented as crosstabs and percentages, followed by a descriptive method for synthesis and interpretation.