• 한국초등과학교육학회지:초등과학교육
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• 제21권2호
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• pp.241-252
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• 2002

Field learning have not well performed in elementary school for various reasons, in spite of the benefits of field study. Absence of suitable geological field courses for elementary science education is one of several reasons The purpose of this study is to develop learning materials for the field geology in Hampyeong region and apply them to the geological related units for elementary science education. The 5 observation sites for the field geology learning in study area include various rocks and geological structure such as granite, gneiss, conglomerate, sandstone, mudstone, plant fossil, fold, fault and weathering phenomenon changing rocks to soil. This study area is suitable place for the field geology learning of elementary science education in Kwangju and Chonnam province because of convenience access, fresh outcrops and distribution of various geological learning materials as rocks and structure.

• 경영과학
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• 제26권3호
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• pp.37-54
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• 2009

E-learning is a networked phenomenon allowing for instant revisions and distribution, and goes beyond training and instruction to the delivery of information and tools to improve performance. The proponents of e-learning emphasizes that students learn more effectively when they interact and are involved with other students participating in similar endeavors. The paper outlines the process of development and design of e-learning based Management Sciences course, with the aim of ensuring widespread use, in undergraduate business program. Experiences in introducing students to e-learning course are reported. Feedback from students has been very positive but also indicates the need for ongoing support and direction. In addition, a survey was used to identify the determinants of students' academic performance of Management Science, and PLS based model is developed to analyze the results. Statistical results concerning the hypothesized model are provided.

• 영어어문교육
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• 제8권1호
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• pp.39-53
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• 2002

Recently much research has investigated the role of attention in L2 learning, comparing the effects of explicit learning with those of implicit learning. With this background the research aims at examining the effects explicit focus on form has on L2 learning based on the acquisition of the English article system. The participants were 70 Korean college students who enrolled in English Composition classes. The experimental group received explicit focus on form including grammatical explanation, input enhancement, output practice, and negative evidence (corrective feedback) for two weeks, while the control group was exposed to sufficient input and negative evidence. Completion tasks were administered at the beginning and the end of the semester. In addition, errors in the use of English articles were analysed on their compositions both before and after the different treatments. The analyses of the results show that the explicit focus on form group improved significantly more than the control group, particularly for the definite article 'the', and some changes occurred in the distribution of article errors. These findings suggest that explicit teaching plays a more contributory role than implicit teaching in acquiring L2 knowledge in classroom-based L2 learning.

• The Journal of Asian Finance, Economics and Business
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• 제7권10호
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• pp.909-918
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• 2020

This study, not only investigates the important role of lifelong learning in shaping young people's knowledge and in maximizing their potential, but also aims to shed light on the influencing factors of lifelong learning of young people in Vietnam. The author applied STATA and SPSS to analyze quantitative data collected from questionnaires with 332 respondents aged between 19 years old and 24 years old. Based on a holistic review of literature, this study concludes that four driver factors affect young people's lifelong learning ability, comprising: organizational culture, motivation, human resource development, and domestic private type of enterprise. The results emphasize the positivity of organizational culture, human resource development, and the nature of work, especially organizational culture and human resource development, which are dominant reasons for young people to maintain lifelong learning. The relationship between demographics and lifelong learning was tested and it indicated that male has a stronger interest in learning than female. The result of the study also shows the impact of different types of business sectors on employees' learning intentions. It points out that the domestic private type of enterprise is the most effective factor that has a positive relationship with the lifelong learning of the individual.

• 한국수자원학회논문집
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• 제54권8호
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• pp.599-606
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• 2021

지하에 매설되어 있는 사회기반시설물 중 하나인 상수도시스템은 정수처리된 물을 수용가에게 수송 및 공급하는 기능을 가지고 있다. 최근들어, 계측능력이 향상됨에 따라 유량데이터에 의한 딥러닝기법을 적용한 누수 인지 및 탐지와 관련한 연구가 다수 수행되고 있다. 본 연구에서는 현재까지 상수도 분야에 적용되지 않은 LSTM 기반의 딥러닝 알고리즘을 활용하여 누수발생에 대한 인지 모형을 개발하였다. 가정한 데이터를 기반으로 모형에 대한 검증을 수행하였으며 2% 이상의 누수가 발생한 경우에 대하여 모두 인식이 가능한 것으로 나타났다. 향후, 제안된 모형을 토대로 유량 데이터 예측부분에 있어서 보다 정밀한 결과가 도출 될 수 있을것으로 판단된다.

• 스마트미디어저널
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• 제12권5호
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• pp.65-72
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• 2023

스마트팜은 농업과 ICT의 융복합을 통해 농업의 생산뿐만 아니라 유통과 소비를 포함한 농업과 관련된 다양한 분야로 새로운 가치를 창출하는 것을 의미한다. 국내에서도 스마트 농업 확산을 위한 임대형 스마트팜을 조성하고, 스마트팜 빅데이터 플랫폼을 구축하여 데이터 수집·활용 촉진. 스마트 APC 확대, 온라인거래소 운영 및 도매시장 거래정보 디지털화 등 산지에서 소비지까지 농산물 유통 디지털 전환을 추진하고 있다. 이처럼 농업 데이터는 다양한 출처에서 특성에 따라 정보가 생성되고 있지만, 통계 및 정형화된 데이터를 이용한 서비스로만 활용되고 있다. 이는 농업에서 생산·유통·소비까지 분산된 데이터 수집으로 인해 한계가 있으며 다양한 출처로부터의 다양한 형태의 데이터를 수집·처리하기 어렵기 때문이다. 그러므로 본 논문에서는 디지털 농업을 위한 국내 농업 데이터 수집·공유 현황을 분석하고 인공지능 서비스를 위한 데이터 수집·연계 방법을 제안한다. 그리고 제안하는 데이터를 이용하여 딥러닝 기반의 환경 인자를 추천하는 방법을 제안한다.

• 한국산학기술학회논문지
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• 제15권1호
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• pp.81-85
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• 2014

본 연구는 유아교육 관련 교재교구 산업의 과제와 전망에 대해 고찰한 연구이다. 교재교구 산업의 과제는 첫째, 분류기준 제시가 시급하다는 것, 둘째, 평가기준이 마련되어야 한다는 것, 셋째, 질 관리가 허술하다는 것, 넷째, 상품화된 자료가 부족하다는 것이며, 다섯째는 교재교구 산업에 대한 정부의 정책이 없다는 것과 여섯째, 교재교구의 활용에 대한 관리 시스템이 없다는 것, 마지막으로 일곱째, 교재교구 유통구조가 개선되어야 한다는 것이다. 교재교구산업의 전망은 첫째, 평가인증 제도의 도입되어야 한다는 것이고, 둘째 교재 교구산업이 성장 할 것 이라고 보는 시사점과, 셋째, 친환경적이며 지속가능한 소재가 확대된다는 것이다. 또한, 넷째, 멀티미디어 사용이 증가되며. 다섯째로 활용률 제고를 위한 관리 시스템 정착이 필요하다는 것이다. 이러한 전망을 근거로 교재교구 산업의 미래를 긍정적으로 보았다.

• 대한수학교육학회지:학교수학
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• 제15권1호
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• pp.15-35
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• 2013

본 연구의 목적은 중학생용 수학학습양식 판별도구를 개발하여 선호유형을 범주화하는 것이다. 개발된 수학학습양식 판별도구로 976명의 중학생을 대상으로 설문조사하여 16가지의 수학학습양식 유형이 존재하는지를 확인하였고 이를 선행 연구들과 비교 분석하였다. 또한 수학학습양식의 각 요인에 따른 양식별 남녀 학습자, 학년별 학습자의 분포에 어떠한 차이가 있는지 분석하였다. 수학학습양식 판별도구를 통해서 학습자의 인지적 정의적 학습양식을 파악함으로써 수학학습에 대한 학습자 특성을 전체적으로 파악하여 획일화된 수업형태에서 벗어나 개별화 수업으로 나아갈 수 있는 방향을 제시하고자 한다.

• Asian Journal of Business Environment
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• 제7권4호
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• pp.17-25
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• 2017

Purpose - The purpose of this study is to present a framework for determining the most appropriate business model for e-learning. Research design, data, and methodology - The Electronics Branch of Azad University has been elected as a case study in this research. This study conducted using a descriptive method. The information was obtained using interviews with experts including managers, faculty and students at the Electronics Branch of Azad University. Results - Three service-product system (product oriented system, use an oriented and result oriented system) approaches determined a framework for the formation of a portfolio. This portfolio is including three types of e-learning business models. Examining the relevant characteristics, correspondence of behaviorism learning theory with a product-oriented approach, correspondence of cognitivism theory with a user-oriented approach and in finally match correspondence of constructivist learning theory with a results-oriented approach which is evident. Conclusions - After reviewing the literature on the fields of e-learning, business model and product - service systems, we have achieved three types of e-learning business models. Then the variables in any of the business models were defined by using business model canvas tool and thus a portfolio consisting of three types of e-learning business model canvas was obtained.

• Journal of Korea Artificial Intelligence Association
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• 제1권1호
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• pp.11-16
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• 2023

Accurate hospital case modeling and prediction are crucial for efficient healthcare. In this study, we demonstrate the implementation of regression analysis methods in machine learning systems utilizing mathematical statics and machine learning techniques. The developed machine learning model includes Bayesian linear, artificial neural network, decision tree, decision forest, and linear regression analysis models. Through the application of these algorithms, corresponding regression models were constructed and analyzed. The results suggest the potential of leveraging machine learning systems for medical research. The experiment aimed to create an Azure Machine Learning Studio tool for the speedy evaluation of multiple regression models. The tool faciliates the comparision of 5 types of regression models in a unified experiment and presents assessment results with performance metrics. Evaluation of regression machine learning models highlighted the advantages of boosted decision tree regression, and decision forest regression in hospital case prediction. These findings could lay the groundwork for the deliberate development of new directions in medical data processing and decision making. Furthermore, potential avenues for future research may include exploring methods such as clustering, classification, and anomaly detection in healthcare systems.