• Information Systems Review
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• v.17 no.2
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• pp.101-132
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• 2015

National technical qualifications to enhance an individual's vocational skills, the competitiveness of companies and countries have an important function to improve. Especially 'qualifications' will have a signal function to show objectively measure an individual's ability with the 'Education' The "knowledge necessary for the performance of their duties. Technology will gain knowledge about such assessment or recognition is based on certain criteria and procedures." Learning to qualify are being made through a smart learning a lot. Due to the revolution of the Internet in recent years with the development of information and communication technologies are entering into a knowledge society, the importance of information and knowledge. This contemporary smart learning education system is continuing to rapidly growing in pace with the changing time and space constraints, without teaching and learning is taking place. The purpose of this study is the ARCS motivation theory can determine a representative theory of human motivation factors and basic psychological needs dealing with the human nature of the psychological needs Interactivity and immersive learning, and to validate the empirical causality Affecting the continued use of smart learning through fun. Specifically, attention, relevance, confidence in the ARCS motivation, see their effect on the learning flow through the satisfaction we analyze empirically. Through this national technical qualifications smart learner's learning by supporting the implicit synchronization of students in learning are the degree of continued use. Therefore, to achieve the objectives of national technical qualifications and skills through a smart learning can contribute to the activation of the development and certification of course industry.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.405-408
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• 2010

문항은 지필평가의 핵심요소이다. 문항의 표현은 전통적으로 문항카드를 이용했다. 교육정보화가 발달하면서 온라인 평가 서비스는 다양한 문항의 표현 구조를 만들었으나, 새롭게 주목받고 있는 스마트 러닝 환경에 그대로 사용하기에는 한계가 있다. 이 논문은 국내의 평가 특성과 스마트 러닝의 이동성을 고려한 문항 표현 구조를 제안한다.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.217-226
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• 2021

Since Covid-19, many educational institutions no longer view online learning as an additional material, but use it as their main learning tool. In this study, we tried to summarize the definition of smart learning and examined how smart learning math classes affect academic achievement, mathematical interest, and attitudes. We manipulate groups that conducted smart learning and groups that conducted face-to-face learning, and compare academic performance, mathematical interest, and attitudes after six weeks of learning. As a result, we found that the smart learning group had a large values in all three factors compared to the face-to-face learning group. We also found moderating effect. Students with lower grades largely improved their academic achievement scores as the difference in attitude changes through smart learning compared to those with higher grades.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.401-403
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• 2021

본 연구는 한국지능정보사회진흥원에서 제공한 2018년 스마트폰 과의존 실태조사에서 사용된 11개 변수와 스마트폰 과의존과의 관계를 탐색하고, 이를 통해 딥러닝 기반 스마트폰 과의존 분류 분석 모델을 개발하고자 시행되었다. 학습데이터셋은 전국 10,000개 가구내 만 3-69세 스마트폰 이용자 25,465명의 스마트폰 이용 형태 및 개인적 특성에 관한 데이터이다. 딥러닝은 심층신경망(DNN)을 설계하였으며, 은닉층(hidden layer)은 4개층으로 구성하였다. 입력한 데이터는 각각 200개, 150개, 100개, 50개, 2개 노드를 거치면서 최종 출력 정보인 스마트폰 과의존 분류율로 나타나는 모델이다. 이때 스마트폰 과의존 분류률을 높이기 위해 학습률(learning rate)과 같은 하이퍼 파라미터를 활용하여 세부조정하면서 가장 잘 학습하는 값을 찾아내었다. 연구결과, 학습횟수가 300번으로 학습율(learning.rate)이 0.01일때 훈련데이터에서 97.43%, 검증데이터에서 98.06%로 가장 높게 나타났다.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.215-222
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• 2022

The purpose of this study was to analyze effects of blended learning on abilities to use smart-phone and applications among students with intellectual disabilities. To do this, 30 students with intellectual disabilities who were enrolled in special school and special classroom in Jellanam-do and Gwanju metropolitan city were selected for this study, and were placed experimental and control groups of 15 students. The experimental group was provided with blended learning in which direct instruction, anchored instruction, experience activities, and community-based instruction were combined, and the control group was provided with traditional teacher-centered lecture style intervention. Pre-, post-, and maintenance evaluations were conducted two weeks after intervention. The collected data was analyzed the repeated two-way ANOVA. In the result of study, the experimental group improved on abilities to use smart-phone and applications than control group. Blended learning is a teaching method that can be a usefully used when educating how to use smart-phone and applications to students with intellectual disabilities.

• Smart Media Journal
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• v.8 no.1
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• pp.74-81
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• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.169-171
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• 2016

본 논문에서는 최근 빅데이터 처리 방법으로 각광을 받고 있는 딥러닝 알고리즘을 스마트교육에 적용하는 방안을 제안한다. 디지털 교과서의 사용과 함께 교육 빅데이터가 발생하는 스마트교육의 특성 상 빅데이터를 효과적으로 처리하고 활용할 수 있는 방법이 필요하다. 따라서 그 방법으로 딥러닝을 적용하고, 이를 활용한 교육을 한다면 개별화 교육의 실현, 감성 교육에의 활용, 수업 개선에의 도움, 양질의 학습자료 선별 등의 효과를 거둘 수 있을 것이다.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.797-802
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• 2020

Over the past few years, smart devices, including smartphones, have been continuously required by users based on portability. The performance is improving. Ubiquitous computing environment and sensor network are also improved. Due to various network connection technologies, mobile terminals are widely used. Smart terminals need technology to make energy monitoring more detailed for more stable operation during use. The smart terminal which is light in small size generates the power shortage problem due to the various multimedia task among the terminal operation. Various estimation hardwares have been developed to prevent such situation in advance and to operate stable terminals. However, the method and performance of estimating the remaining amount are not relatively good. In this paper, we propose a method for estimating the remaining amount of smart terminals. The Capacity Estimation of lithium ion cells for stable operation was estimated based on machine learning. Learning the characteristics of lithium ion cells in use, not the existing hardware estimation method, through a map learning algorithm using machine learning technique The optimized results are estimated and applied.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.522-533
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• 2014

The capability of the digital communication would need to be strengthened for leveraging collaborative knowledge building and problem solving skills of the middle aged people. It was developed and implemented a smart learning model by utilizing the formative intervention based on the logic of change laboratory to target learners of 'K organization', As a results, smart learning model was composited several activities and supporting systems such as learning instructions of Smart Pad, communication games and SNS, using self-diagnosis and making posters and role-playing video by the internet applications. This research is significant that it finds efficient method to fit design of smart learning and the needs of target learners by using them as testbed which is mixed with different background and digital communication experiences.

• Journal of Service Research and Studies
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• v.11 no.4
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• pp.67-76
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• 2021

The importance of smart learning is increasing as the speed of development of non-face-to-face services increases due to the influence of COVID-19. This study is the user satisfaction evaluation model that utilizes the causal relationship between variables used for evaluation, focusing on the usability evaluation results of the learning disability intervention service (www.basic-edu.net) according to the need to evaluate the use satisfaction of the smart learning system. To this end, theoretical studies were conducted on smart learning and learning disability intervention services, www.basic-edu.net, usability evaluation of learning disability intervention systems, and use satisfaction evaluation models. And based on the results, a hypothesis was presented on the user satisfaction evaluation model of the smart learning system. The experimental method allowed 40 students and parents across the country to use the www.basic-edu.net service and was evaluated for its usability. In addition, using this data, the hypothesis was verified using regression analysis based on four variables: ease of use, interest, self-learning, and satisfaction with use. As a result of the hypothesis verification, it was found that the causal relationship of all hypotheses from H1 to H4 was significant.